If recent news has taught us anything, it’s that we no longer need to theorize about the possibility of AI systems going rogue. Recent episodes of AI-enabled attacks have led to warnings from prominent researchers, and calls from frontier labs to slow AI development.

However, AI isn’t just an adversary. It’s also been useful for preventing cyber incidents, which could make it harder to regulate.

All in all, cyber expert Brandon Dixon is unsure about how much slowing down will protect us against AI’s capabilities. He urged businesses to understand their own processes first and map out risks in a recent interview with Tech.co.

Recent AI Attacks Put Safety in the Spotlight

Days before Anthropic CEO Dario Amodei called for frontier labs to slow down AI model development, ex-Anthropic and ex-OpenAI researcher Jacob Coxon released a series of posts on X expressing fear for the future of humanity.

Among the passages, Coxon claimed AI leaders are “gambling with our lives” in their pursuit of superintelligence. His comments most likely would have joined the chorus of existing AI “doomers” as they’re called, had they not followed a series of highly concerning autonomous AI attacks.

Most recently, OpenAI disclosed several concerning behaviors exhibited during the testing of GPT-5.6 Sol. The model supposedly started to leave instructions for future versions of itself, telling it to conceal mistakes and misaligned behavior from users. If that doesn’t concern you, just remember what happened with Hugging Face.

To Brandon Dixon, co-founder and CTO of Ent, which helps organizations understand and protect against malicious actors and AI agents, we’ve moved beyond the theoretical stage of AI cyber attacks. This ultimately means the playing field has shifted massively, and what we do next is important, but also hard to figure out.

AI’s Positive, and Negative, Impact on Security

When I’ve interviewed cyber experts on AI, what we discuss is a kind of double bind. AI is facing both sides of the battlefield, in that it’s helping businesses detect and react to attacks faster, while mounting those attacks in the first place.

“The models being used to craft phishing lures are also being used to find bugs before they ship, improve code quality, and surface vulnerabilities in production systems before they’re exploited,” Dixon told me.

At the moment, it’s impossible to see a world where we fight AI, without using AI. “Speed and efficiency cut both ways,” Dixon told me. Essentially, the features that make AI so good at attacking us, also make it very good at protecting us.

Nevertheless, AI-powered cyber attacks are a serious concern. Using that speed and efficiency, attacks can happen faster, without giving humans enough time to detect them, and serious amounts of data can be lost.

“The limiting factor for attackers has historically been the ability to understand the data that was stolen,” Dixon noted. “But now, AI supercharges that.”

Policing AI is Becoming Increasingly Difficult

Cyber experts have been calling for a more careful consideration of AI’s security vulnerabilities for some time. However, this point in time does feel significant. Dixon said it’s because we’ve now seen these capabilities in action.

“There are documented cases of AI agents breaking out of sandboxes, taking unintended actions, violating corporate policies, or otherwise behaving adversarially. These systems have materialized and evolved extremely quickly,” he explained.

“We are only a handful of years into this technology, and its capabilities change materially every year. That makes it difficult to know where it is heading or to apply security and governance measures that will not become outdated shortly after they are deployed.” – Brandon Dixon, co-founder and CTO at Ent

Despite the technology moving faster and faster, the US government is yet to pass any federal laws around AI. Individual states like California have implemented some AI laws, but currently, AI isn’t equally regulated in the US.

And, given recent comments made by Trump following the slowdown call from AI leaders, it doesn’t look like any new laws will be passed through Congress soon. Mostly, this is because of rapidly developing Chinese AI models, which Trump has continually said the US needs to outpace.

However, many experts will say some government intervention on AI is needed, Dixon included. “I think the government should establish sensible rules that preserve innovation and progress while preventing clearly reckless or harmful uses.”

“The goal should not be to eliminate risk entirely because that would suppress legitimate research and defensive deployment. Oversight should focus on meaningful risks and measurable harms, not broad restrictions on the underlying technology,” he said.

Will Slowing Down AI Protect Organizations?

It’s difficult to think about what happens if we slow down. What’s most important to remember, for starters, is that even though AI leaders have committed themselves to slowing down, they could turn the other way, especially given the stance of the Trump administration.

For Dixon, slowing down AI won’t necessarily put us in a better place. “From my perspective, more time does not necessarily produce a better understanding of security vulnerabilities,” he said, though he does admit he can’t speak for frontier labs themselves.

While additional time could help review code, test software, or identify weaknesses, he added, organizations may not use the time as wisely as we assume they will. “If history is any indication, many will wait for attacks to begin before responding appropriately.”

It’s still not entirely certain what slower development will look like, should it happen. But, Dixon told me businesses shouldn’t use an inability to control all aspects of AI as a reason not to adopt it. To him, it doesn’t make any sense. But what also doesn’t make sense, is just “adopting AI, hoping for the best and not having any clue what people are doing.”

Instead, organizations need to understand how they actually operate. “It is not enough to identify sensitive data, intellectual property, or trade secrets,” he said.

He advises businesses to figure out “which behaviors are acceptable, which workflows deserve attention, how those workflows could be exploited, and how that exploitation would be detected.”

95% of respondents of a new study list AI fluency as a hiring requirement. However, a significant number of organizations are still reporting having made a bad AI hire.

Historically, employees have been encouraged to experiment with AI to find out how it could suit their specific needs. Now, standardized AI use is emerging, which will help hiring managers choose the right talent.

Wouter Durville, CEO of TestGorilla, spoke to Tech.co about what AI fluency means and how businesses can hire with this skillset in mind, all while avoiding common mistakes at the interview stage.

Companies Are Looking for AI-Fluent Job Candidates

TestGorilla’s State of AI Fluency study finds that 53% of hiring managers now prefer a candidate with high AI fluency over one with deep domain expertise. However, of those managers, 59% report having made a bad AI hire.

Wouter Durville, CEO of TestGorilla, highlighted how impactful an AI fluent employee can be. “I think people who are really AI fluent, the outcomes they generate are massive. It’s a big difference.”

Companies certainly want to hire with AI in mind, the study finds, but are often going about it in the wrong way. Durville explains how the study was borne from customers communicating to him how much they were struggling with the issue. Eventually, TestGorilla landed on the term “AI fluency,” one Durville knows is difficult to properly define.

“It’s really about getting those people who know how to use these tools in the right way, and in a responsible way. Who are agile, who are using different tools for different things, who are system thinkers that see the bigger picture of where to use AI and where to put the human in the loop,” he explained.

It goes without saying, though, that this definition will vary based on your company and its goals.

Businesses Are Moving Towards Standardized AI Use

The first step when AI started to make waves in companies was convincing employees to actually use it. Common advice was to let employees figure out the tool for themselves, find ways to embed it into their own workflows, and experiment.

Arguably, this could explain the rise in individual productivity compared to company-wide gains some studies reported. But, this tactic seems to have faded.

“For example, in product development, it becomes quite messy if everyone is using a different tool for coding.” – Wouter Durville, CEO of TestGorilla

Messiness aside, it makes it easier to police the technology if everyone is using it across repeatable, company-wise processes.

That’s not to say organizations should stamp out individual moments of AI brilliance, but standard practice could protect against costly data breaches or common AI mistakes.

In the case of hiring, it’s likely much more productive to have a standardized company practice when it comes to AI. That way, in interviews, hiring managers can assess exactly how a candidate has used AI, and whether it matches up to AI expectations within their organization.

How Can Companies Hire for AI Fluency?

As well as standardizing AI use, there are other tactics companies can use to test AI knowledge. The first is actually defining what AI fluency means to your organization, which 71% of respondents of the survey have already done.

Likewise, the study found 37% of organizations set the bar at tool awareness when hiring a candidate. Rather than putting a tick next to someone’s name when they mention ChatGPT or Gemini, Durville encouraged businesses to “go deeper,” and figure out exactly how the candidate has used AI.

“You want to actually test an example in an interview,” he explained. So, asking a candidate questions like, “tell me about a workflow you actually built, or something that you automated. How did you go about it, what went wrong, and how did you fix it?”

“If you ask those questions, if you peel the onion a bit or go a bit deeper, you’ll very quickly notice, okay, this person has no clue how to do this,” he said.

Furthermore, Durville said AI use — and how it’s going to be tested in interviews — should be related to the job role as much as possible. You’re likely to test a marketing executive on their knowledge of AI video editors, for example, but this is less useful when interviewing for an engineering job.

Overall, Durville has positive views about AI and how it will impact hiring. While the CV and cover letter have basically been killed, he told me, companies can use AI to give more opportunities to candidates at the interview stage.

Recently, AI leaders have been talking about slowing down AI development. In particular, Dario Amodei of Anthropic and has pledged to “pace the frontier,” in a new blog post.

While AI figures such as Amodei, Sam Altman, and Elon Musk appear to agree with each other on pacing, other major players such as Nvidia’s Jensen Huang appear to disagree. Likewise, concerns about Chinese AI one day overpowering US models remain paramount to the US government.

Experts suggest AI leaders should turn their attention to increasing trust, instead of slowing down AI. They also warn that the US slowing down won’t necessarily mean others will do the same.

Anthropic CEO Says ‘Pace the Frontier’

A few days ago, Anthropic’s CEO Dario Amodei released a blog post titled, “We Must Pace the Frontier.” The post is a call for AI leaders to slow down the rapid development of AI models. 

Safety concerns around AI have once again been pulled into headlines following comments made by researcher Jacob Coxon, who resigned from Anthropic amid fears of unrestrained development leading to the end of humanity.

In a post on X, Coxon, who previously worked for OpenAI, claimed the people building AI “earnestly believe it could kill us all by the end of the decade.” Similarly, he claimed leaders are “racing straight to self-improving superintelligence and gambling with our lives.”

AI executives including OpenAI’s Sam Altman and SpaceX’s Elon Musk shared their agreement of Amodei’s post. While the post doesn’t mention Coxon’s recent comments, it does reference the OpenAI/Hugging Face breach.

“The calls from some of the world’s leading AI researchers and technology companies to slow the pace of frontier model development reflect a growing recognition that innovation and responsibility must advance together,” said CISO of Optiv Field, Kristin Lowery.

Lowery suggests accelerating capabilities must come with a significant understanding of how to govern and safely deploy AI, suggesting the call to slow down from leaders could be a positive one.

How Realistic Is Slowing Down AI Development?

It’s one thing for leaders to say they’re going to slow down, but the real question is what exactly this will look like. Amodei’s blog post does outline some strategies for how AI companies can achieve reduced development, and said Anthropic is “unilaterally committing” to one of them. Altman has chimed in to say OpenAI will do the same.

Despite support from Altman, Musk, and Microsoft, which released a new AI code of conduct yesterday, not all leaders agree with Amodei’s plan. Jensen Huang, CEO of Nvidia, for one, made quite a public show of where he stands at the All-In Summit in Los Angeles.

Huang received and answered a call from President Trump on-stage, where the topic was Amodei’s recent post.

“They’re just playing right in the hands of a lot of people that don’t want to see it happen,” Trump went on to say to the crowd. “That could be political people. It could also be China. And we’re not going to let that happen. It’s a hoax.”

“You’re right. We’re not going to let that happen, sir,” Huang responded, and the crowd applauded them.

Chinese AI competition is a major concern for the US government, and this has only ramped up as Chinese models continue to close the performance gap to US models, all while offering a lower prices. The insistence has always been that the US needs to be first ones to crack AI and superintelligence.

From an international perspective, Lowery makes another point about why slowing down could be dangerous. “AI innovation is occurring globally, and not every nation, organization, or threat actor shares the same values regarding transparency, safety, and responsible use. This creates a complex dynamic that increasingly resembles a technology arms race.”

“If responsible organizations dramatically slow innovation while less accountable actors continue advancing without guardrails, we risk creating unintended strategic disadvantages.” – Kristin Lowery, CISO at Optiv Field

Essentially, the US slowing down its own AI development won’t lead to everyone doing the same. Threat actors and hacker organizations could still develop rapidly and cause AI cyber attacks we’re unprepared for.

Why Leaders Should Focus on Building Trust

It’s been hard to trust AI leaders. Whether it’s the constant uncertainty around job losses, the fear of global cyber attacks, or just the end of humanity in general, the AI rhetoric has been far from pretty.

Beyond negative AI messaging, publications are consistently reporting on autonomous hacks and AI data breaches, which suggests we might not be properly prepared to understand and prevent against the dangers AI poses.

Pacing frontier models could be a way to ensure we’re ready to deal with the capabilities of these models. However, experts are saying there’s no reason why we can’t have both safety and high-performing AI.

In a recent interview with Bloomberg, chief ethics scientist at Hugging Face Margaret Mitchell argued safety, privacy, and security must be built directly into AI systems, rather than being seen as a trade off to progress.

Lowery makes a similar point, and says the current debate is the wrong one. “In my view, the debate should move beyond whether to pause or accelerate AI, and focus instead on how to build trust into AI from the outset,” she said.

“History shows that transformative technologies rarely succeed through either unchecked innovation or excessive regulation alone; the most sustainable path is to encourage innovation that drives economic and societal value while implementing thoughtful safeguards that reduce risk and build trust.” – Kristin Lowery, CISO at Optiv Field

Ultimately, AI brings with it more risk the less leaders are willing to pay attention to safety and privacy. Future models should be developed through this lens, so we can reap the full benefits of AI, without risking something far greater.

This article is part of an interview with Betsy Cooper, Director of the Aspen Policy Academy. This interview was conducted for Tech.co’s AI newsletter, The AI Strat. For more interviews with AI experts on the latest trending topics, subscribe to the newsletter.

While the response to AI’s ever-evolving capabilities has been mostly excitement, the threat to cybersecurity in the form of increasing cyber incidents has been difficult to ignore.

Increasingly, experts believe businesses will need to alter internal policies, including incident response plans, to account for the fact that they won’t always be dealing with a human attacker.

I spoke to Betsy Cooper, Director of the Aspen Policy Academy, about how AI continues to change the cybersecurity landscape. Likewise, we discussed how businesses should be prepared to change their practices moving forward.

The AI Threat Hasn’t Been Fully Realized

Before becoming Director of the Aspen Policy Academy, which allows experts in cybersecurity and AI to share their knowledge, Betsy Cooper ran a cyber security program called the Center for Long-Term Cyber Security at UC Berkley. Cooper also worked for the Department of Homeland Security.

When I asked Cooper what excited her about AI, she spoke to its ability to make “it easier to do things that take up a lot of time.” From her perspective, this includes tasks like writing personalized notes to partners.

However, Cooper also has her fair share of concerns, and a lot of them she’s not alone with. She fears what our education system will look like with AI, and how jobs, particularly at the entry level, will change. And of course, she mentions the existential threat of AI.

“Obviously, there’s been a lot of buzz lately about several of the models escaping their confines and hacking others. We’ve talked about that. I wrote scenarios 10 years ago that focused on that idea, and now we’re here,” she told me.

Earlier this week, an Anthropic researcher resigned amid concerns about how the company was handling AI’s threat to humanity. In a series of social media posts, Jacob Coxon wrote: “The people building AI earnestly believe that it could kill us all by the end of the decade.”

While this incident occurred well after my interview with Cooper, it speaks to the concern many experts are feeling. In particular, Cooper voiced concerns for the future of the internet, suggesting we’ll need to ensure it remains valuable to humans in the face of these threats. “I don’t think we’ve fully grappled with that,” she said.

How Incident Response Plans Will Need to Change

Understandably, cyber incident response plans up until now have assumed a human attacker. And, most businesses today will know and have embedded best practice to protect themselves.

However, the introduction of AI agents, which are able to attack autonomously, has changed the game. As a result, Cooper believes internal policies including incident response plans, will need to change with it. In some cases, she says, the humans might be the non-malicious actors, and the agents are the malicious ones.

“That probably requires a different chapter in your incident response plan than the day-to-day. So that would be something that I would really encourage people to do, is start updating your incident response plan to try to figure out the source of the hack, and to figure out if it’s a non-malicious actor human, are you going to use the same playbook that you would as if it were a malicious actor human?” – Betsy Cooper, Director of the Aspen Policy Academy

That being said, Cooper doesn’t see AI as solely a cyber adversary. In many cases, it’s an ally, one that is able to help humans detect unusual activity more effectively.

“Most organizations are going to have to lean into AI to help them identify when something weird is going on, because the patterns may not be as obvious,” she said.

Assess Your Risk Profile and Ensure Basic Security Hygiene

Additionally, Cooper explains how organizations need to be aware of their risk profile when it comes to AI-driven attacks. Hugging Face, the company the rogue OpenAI agents breached, is at a higher risk because of the work it does, Cooper said. Whereas if you’re operating in the paint industry, for instance, your risk is probably lower.

Cooper also expressed the importance of maintaining proper cyber hygiene. AI agents will make the most of shortcuts, if the Hugging Face incident is anything to go by. So, minimizing those and ensuring you aren’t easy to hack is key.

“If you’re not on the easiest path,” Cooper explained, “then you still have hope right now. I can’t promise that’s going to stay that way.”

Ensuring you’re not on the easiest path means sticking to best cybersecurity practices. Cooper gives the example of not using passwords that have already been disclosed, and making sure data is stored in different places and compartmentalized so it can be recovered if you do suffer an attack.

“The same hygiene techniques that hopefully you’ve been already using to prevent the ordinary hacker who’s a human. Many of those techniques at least will make it less likely that you will be targeted,” she said.

However, she does sound a warning about the future of attacks. “Increasingly, this is going to happen more commonly, and it’s probably not possible to stop,” she added. For now, businesses should focus on protecting themselves under the assumption an attack will happen.

Physical AI solutions are, understandably, moving at a staggered pace when you compare them to the breakneck speeds of AI development in general.

A part of this, experts argue, is a trust problem, especially since new physical innovations can lead to more dangerous consequences if underdeveloped or misunderstood. However, there is also the issue of data management and information silos.

I spoke to Sri Teja Kolluri, product lead at Motive, about how fleet owners can upgrade their maintenance processes and ensure success when using AI.

A Trust Gap Remains for Physical AI

When I’ve spoken to logistics experts about the trajectory of physical AI, none of them have been surprised that it’s development has been significantly slower. It’s easy to sit at a laptop and understand the capabilities of Claude, but integrating AI into driver safety, for example, has real world consequences.

Sri Teja Kolluri, product lead at Motive, sees this as a problem that still needs to be solved. “There’s a general excitement about things, but beyond drafting emails, how can we actually use AI in real life?”

Motive’s latest fleet maintenance report suggests fleet owners are trusting AI more than previously. 80% of those surveyed said they would be comfortable with AI summarizing or creating reports, 67% would allow it to schedule or initiate work, and 60% would trust it to approve routine or low-risk tasks.

However, less than half (47%) said they would be comfortable with fully automated workflows without human review, suggesting human oversight remains a critical part of AI workflows.

How AI Can Help Transform Maintenance

Maintenance is one area where Motive and Kolluri feel AI can make a huge difference. Significantly, 80% of survey respondents cited rising maintenance and repair costs as their top operational challenge of the second half of 2026.

Despite the opportunity for AI in maintenance, 60% of owners surveyed aren’t using AI-based predictive or condition-based maintenance tools. Comparatively, 88% of owners are using AI-powered driver safety technology, like AI dash cams and safety programs.

I asked Kolluri about why maintenance may be lagging behind compared to other fleet processes. “With a lot of maintenance workflows, what’s happening is that they’re using different systems that don’t talk to each other. So, you have data scattered across your stack or they’re using spreadsheets, which again, it’s very hard to actually use as input for AI.”

However, Kolluri says maintenance teams are already seeing benefits by opting for a more integrated system. Watco, a transportation and logistics company, reports that problems now appear sooner, more assets stay in service, and it can identify the real cost of operating its fleet.

Hesitant maintenance teams, he continues, should prioritize the “key use cases” that will break down any informational silos in your operation. “I think that’s where you can identify the right solutions to adapt and solve that problem,” he says.

Small Steps and Integration are Key to AI’s Success

Using AI in isolated, random incidents is rarely as productive as using it as part of a connected system. Accountability and ownership are lost, and privacy and compliance decisions are made in reactive bubbles.

Integration and tackling information silos, Kolluri says, are incredibly important to get right when AI becomes involved.

“I think it’s very important that you work towards an AI operation that is well integrated and solves a lot of the data silos.” – Sri Teja Kolluri, Product Lead at Motive

Motive’s report findings confirm the problem. 80% of respondents said their fleet technology environment has some systems integrated, but with significant gaps. Overall, only 13% described their systems as well-integrated that share data automatically across platforms.

As well as integrated systems, Kolluri urges businesses to take small steps forward when introducing AI. “In general, AI might feel scary because, hey, there’s this powerful tool that we can use to automate a lot of things.”

“I think the best opportunity is just start small. Identify these opportunities and then slowly you’ll find that you have built reasonable AI operations,” he says.

Furthermore, don’t start from nothing. AI should be used to accelerate and improve your existing processes. A big part of this is understanding where AI can realistically fit, rather than forcing it.

“Audit your processes, identify where you are spending the most manual effort and where the most repetitive tasks are, and identify those opportunities to see where you can deploy AI. I think that’s the one thing, once you do that you can start taking baby steps towards adopting AI in that specific workflow,” Kolluri says.

A significant number of enterprise marketers are approaching AI in a “disconnected” way, according to a new study.

Adobe Business categorized marketers based on their ability to scale and control customer experiences, through its CX AI Maturity Index. Enterprises were grouped as either Orchestrated, Constrained, Unbalanced, or Disconnected in their approach.

In order for businesses to get the most out of their AI use, they need to use it as part of connected, repeatable systems. Opting to organize clear ownership and shared governance is the best way forward.

Marketers Are Failing to Leverage AI in a Connected Way

68% of marketers are “disconnected” in their AI strategy, according to a new study from Adobe Business. Disconnected, in the study’s sense, is understood as AI being used to produce content and launch experience, but removed from a connected, repeatable system.

According to Adobe, this translates to a lack of clear ownership and shared governance. Similarly, risk and compliance are reactive, rather than proactive within an established system.

Overall, the study concludes repeatable systems and shared ownership across teams is vital to AI’s marketing success.

Adobe Reveals CX AI Maturity Index

Adobe categorized enterprise marketers based on how effectively they have integrated their infrastructure at scale with AI. Marketers fell into the following ranks:

• Disconnected (low execution, low control): Operations like content, data, and journeys happen in silos, so there’s no consistent way to use AI to improve the customer experience. AI does exist, but only in isolated instances.
• Unbalanced (high execution, low control): Execution is scaling quickly, but is lacking the governance and controls needed to keep operations safe.
• Constrained (low execution, high control): The governance is in place to scale safely, but there is a lack of capabilities to deliver the right omnichannel experiences.
• Orchestrated (high execution, high control): Experiences are overall connected, controlled, and continuously optimized. AI is orchestrating experiences across channels at the individual customer level.

The majority of enterprises (68.3%) surveyed fell into the Disconnected category. Orchestrated enterprises (15.3%) were second, with Constrained (9.8%) and Unbalanced (6.6%) following.

The Index draws on 501 completed enterprise assessments and over 6,800 responses across 12 questions.

Repeatable AI Systems Ensure a Connected Customer Experience

Ultimately, businesses need to allow AI to integrate itself into their workflows if they’re to see real results. This means building systems around ownership, governance, and compliance. One individual using ChatGPT to write an email might save some time, but for real scalability, AI needs to be practically invisible.

The study found 64% of enterprise marketers cannot fully trace how their AI-driven content and decisions were generated. Likewise, customer journeys are described as equally siloed or partially coordinated for 74% of marketers.

Additionally, as AI poses serious threats to businesses if not properly governed, risk and compliance needs to be integrated into decision-making. Having it be purely reactive puts your business at risk.

Getting your hands on a grant for your small business provides an immediate boost. Maybe you want to try something new, like infuse your marketing strategy with AI, or upskill an employee. Or maybe, you want to start a completely new venture.

Either way, small business grants offer a vast amount of support. Of course, you’ll get your hands on cash you can implement directly into your business, but some grants include additional benefits, like one-on-one business advice or social media coverage.

Our round-up of small business grants in September includes who’s best positioned to apply, the amount you’ll get, and any deadlines. I’ve also dug into the application process of each grant to give you a head start on your application.

Encouraging Development, Growth, and Expansion (EDGE) Grant

• For: STEM (science/technology/engineering/math)-based companies and Entrepreneur Class (non-STEM) businesses
• Amount: Up to $750K split among STEM winners, up to $400K split among non-STEM winners
• Deadline to apply: September 11

This grant is a great choice for STEM businesses, though there is also a significant pot available for non-STEM entrants.

To apply for this grant, your business needs to be located mostly in Delaware. Likewise, you’ll need to have been in business for less than 7 years, have 15 or fewer full-time employees, have less than $700K in assets, and have a 3:1 match for funding.

Likewise, the website states funding “must be used to expand a business’s viability and sustainability.” The areas it picks out in particular are: market analysis assistance, advertising assistance, building infrastructure/cosmetic enhancements, essential equipment, website design, and rent assistance for lab space.

In terms of the application, you’ll be judged on business need case, competitive advantage gained, business viability and likelihood of permnance, job creation/revenue growth, and the quality of your pitch.

Apply here

High Five Grant

• For: Mom entrepeneurs looking to grow their business
• Amount: $10,000 grand prize (other prizes available)
• Deadline to apply: September 30

Being a mom is already an all-consuming job. But add a growing or new business into the mix, and the task can look downright impossible. This grant from The Mama Ladder is designed to help with a hefty $10,000 grand prize.

The beneficiary of the grant isn’t only the business that wins, however. $5,000 is given to the first runner-up, $2,500 is given for the second runner-up, and five honorable mentions also receive $1,000 each.

Unsurprisingly, applicants must be mothers or expectant mothers, who own at least 50% of a for-profit business. Likewise, you’ll have to have annual revenue between $10,000 and $500,000, and reside in the US or Canada.

The Mama Ladder recommends setting aside 30-60 minutes to complete your application. Think closely about the “why” behind your businesses, because you’ll need to share this on social media. Don’t forget to tag the title sponsor, @usbank, and @highfivegrant with the hashtag #highfivegrant.

Apply here

Business Freedom Grant

• For: Ambitious entrepreneurs looking to start, launch, or scale their business
• Amount: $1,000
• Deadline to apply: September 30

This grant is for passionate and ambitious individuals with a business idea. Coach Darcy, the founder of the grant, says she was inspired to help others “bridge the gap between surviving and thriving, between having a dream and finally getting the opportunity to build it.”

You can use the grant to launch essentials, accelerate growth, build capability, invest in knowledge, create operational foundations, and for financial stability.

Applying individuals should have: a clear business idea with an actionable plan, a business in any industry (product-based, service-based, or digital), and the commitment to complete a brief application sharing your vision.

Similarly, the website lays out a 10-point evaluation system for applications, which applying businesses should focus on. Structuring your application around these points is definitely a good start:

• Clarity of business idea (3 points)
• Feasability of the plan (3 points)
• Impact of the grant (2 points)
• Passion and commitment (2 points)

Apply here

The Freed Fellowship Grant

• For: Micro or small business owners
• Amount: $500
• Deadline to apply: Rolling basis (this round September 30)

Freed Fellows are selected on a monthly basis, and each month, micro or small business owners are invited to apply by Eastern US time on the last day of the month. Be aware, though, you’ll need $19 to apply for this one.

Selected fellows aren’t just given $500 to spend, but they’re also considered for a $2,500 grant given at the end of the year. Funds can be used for any business-related expense, whether that’s new hires or a new ecommerce set up.

Additionally, fellows receive access to a strategy call with a team of business experts, a one year membership to Freed’s online community, Freed Studio, and are typically features on the Freed Stories podcast.

Applications are assessed through what Freed calls its “5C Framework.” Again, keep these in mind when applying:

• Context – your market
• Content – your story
• Chemistry – your audience and community
• Chemistry – your product, people, and process
• Commerce – your business model

Apply here

The Benefits of a Small Business Grant

Given the difficulties facing small businesses today, a grant can be a real life line. It can help you develop your business in an area you haven’t been able to, such as training employees on AI systems.

Furthermore, plenty of grants offer support beyond some extra dollars. In some cases, you’ll get access to business experts or other professional services, or help with visibility such as social media coverage.

Being awarded a top grant also labels you a business to look out for, particularly to investors. If you’ve already been chosen for a grant, others will see you as a business to bet on.

Recent studies have suggested that leaders believe they need more AI training than they currently have. As AI continues to have an impact on daily processes, gaining a firm understanding of how AI works will ensure its continued success.

Free, online AI courses are a great way to level yourself up. And luckily, there are plenty out there every month. Whether you want to better understand the regulatory conversation surrounding AI, or understand how generative AI can help with strategic decision-making, this month’s roundup of the best free AI courses has you covered.

AI Content Strategy – Performance, Ethics, and Adaptability with LearnQuest Network

Summary:

• Marketers and content professionals learn how to use AI in their strategy
• 5 modules, taking around 3 hours to complete
• Beginner-friendly
• Shareable certificate available upon completion
• Available on Coursera

Marketers and content professionals are increasingly turning to AI to brief and monitor campaigns, as well as handle routine communications. If your team is looking to explore AI further in their work, this course is a great option.

In this course from LearnQuest Network, you’ll move through five different practical modules: measuring real content performance, converting prompting skill into shared team knowledge, governing content (for copyright, disclosure, and bias), evaluating AI tools by true cost and fit, and protecting brand voice from AI-driven homogenization.

Widely, you’ll also gain access to the AI Content & Creative Tools Specialization when you sign up, giving you options for further development.

Strategic Decision-Making with Generative AI with Harvard Business Review

Summary:

• Managers and executives learn how to incorporate generative AI into their decision-making process
• 8 modules, taking around 2 weeks to complete if studying 10 hours per week
• Intermediate level
• Shareable certificate available upon completion
• Available on Coursera

This course says it shows users “how to bring generative AI into that harder, more strategtic layer of your work.” If you find yourself in need of a partner in your thinking, particularly around decisions, this course is a good fit for you.

Similarly, users will use generative AI to search for information and analyze data, generate and validate customer insights, and build stronger business cases by pressure-testing stakeholder perspectives, trade-offs, and risks.

Ultimately, you’ll come to see generative AI as a co-pilot for fast analysis, and a co-thinker for stress-testing reasoning before you make a decision. Experienced leaders who want to make the most out of what AI can offer should consider this course.

Skills to Succeed in the AI Era with International Supply Chain Education Alliance

Summary:

• Individuals learn to build long-term resilience in the AI era
• 4 weeks to complete at 2-8 hours per week
• Intermediate level
• Certificate available for additional price
• Available on edX

It’s understandable to be anxious about AI’s impact on jobs, especially since the full consequences are yet to be seen. This course gives users the tools and knowledge they need to thrive in this new job market.

The course will explore the job market in the wake of AI, AI literacy, data management, personal AI tools, and the rise of new-collar tools. Similarly, you’ll learn human skills, including understanding future job scenarios, and strategies for freelancing, entrepeneurship, and long-term career resilience.

Whether you’re a student, professional, or aspiring leader, this course promises value. By the end, it says, “participants will be better prepared to navigate the evolving labor market, continously adapt to technological change, and build a future-ready career in the AI era.”

AI Regulation and Law with KULeuvenX

Summary:

• Individuals learn about the regulatory environment surrounding AI
• 4 weeks to complete at 3-5 hours per week
• Beginner-friendly
• Certificate available for additional price
• Available on edX

As exciting as AI is, leaders and businesses need to be aware of the risks involved. Not only could improper AI use lead to costly data breaches, but failing to remain compliant to regulation could harm your company’s reputation.

By the end of this course from KULeuvenX, you’ll be able to describe key regulatory frameworks including the AI Act, understand the basics of AI, machine learning, and deep learning, and recognize how data is used in AI-driven systems and applications.

Additionally, the course explores important questions, such as why AI regulation is necessary, and how we should be regulating the technology. This is an essential course for anyone looking to explore AI in their professional life.

Why You Should Keep Up with AI Courses

It can be a pretty daunting task to try and keep up with the current pace of AI development. AI companies are moving fast to develop new products, and existing systems are incorporating AI rapidly to keep up with demand.

So far, businesses are seeing gains in productivity. However, adopting AI blindly is proving to be one of the biggest mistakes, with companies adopting AI for the sake of it without understanding how it fits into their current practices.

Free AI courses are a great way to keep up with how the industry is changing. Most of the time, they don’t take long to complete, and you’ll be leaving with a much better understanding of not only how the tech works, but how it fits in with your goals.

These workflows are from Tech.co’s weekly newsletter, The AI Strat. To receive free weekly workflows tried and tested by industry experts, subscribe to the newsletter. 

AI is a powerful addition to workflows. It has proven to speed up productivity, standardize and improve the accuracy of routine processes, and free up humans for the work that really matters.

But, I wouldn’t advise you to just add AI to every workflow your business uses. It’s much better to take a look at your existing processes and see whether AI can make a difference. Our monthly list prioritizes results: real workflows, created by real business owners.

This month’s workflows are:

• Morning briefing workflow
• Content gaps from customer queries workflow
• Improve AI customer support workflow
• Streamline team communication across locations workflow

Morning Briefing Workflow

Recommended by Gretchen Terry-Leonard, co-founder and chief strategy and impact officer at The Center for Deeply Human Leadership

Gretchen uses this workflow to get herself ready for the working day ahead. The first step is critical one: defining absolute rules for the AI, to ensure you’re getting the right information. Then, you can connect whatever sources you need.

Gretchen recommended your email and calendar, and I added the weather, as this has worked for me in my morning briefing.

The workflow helps Gretchen prioritize in the mornings, especially when she’s not only organizing her day, but her family’s day as well.

Identify Content Gaps from Customer Questions Workflow

Recommended by Harpal Singh, founder of blimpp

This workflow takes real customer questions and search queries to identify content, PR, community, and partnerships opportunities.

AI has completely shifted the search landscape, and a workflow like this one ensures you’re providing content that users are genuinely asking for, making sure that you are more likely to land with audiences.

Harpal uses this workflow with DTC, B2B, and SaaS brands to identify the publishers, comparison pages, buyer guides, and community discussions influencing AI recommendations. This repeatable system has replaced a manual, disconnected search process within his business.

Improve AI Customer Support Workflow

Recommended by Konstantin Bukin, director of AI at Saritasa

Customer support is one of the more popular uses of AI for businesses. This workflow allows you to level up your current set up. AI gets direct access to your database, so queries can be answered with concrete facts.

If the AI can’t solve a query, a human is ready to take over, so your customers won’t have to wrestle with a robot.

Bukin says the workflow was implement by sports management platform, Sports Thread. The company reduced staff time on addressable support cases by 83%.

Streamline Team Communication Across Locations Workflow

Recommended by Kevin Turpin, founder and CEO at Weavix

This workflow is targeted at teams that want to improve their communication channels and streamline the flow of information. In particular, Turpin recommends it for international teams that might be communicating in different languages.

According to Turpin, Aspire Bakeries saw 8% faster response times and prevented hundreds of thousands of dollars in losses by implementing this workflow.

Why Use AI Workflows

Businesses can reimagine entire processes by implementing AI into their workflows. The technology works best when it frees up humans to do what they do best. For example, AI can handle routine, time-consuming tasks, like inbox organization or basic communications.

Similarly, with AI, you can reduce errors and scale processes, as well as ensure these processes remain consistent and repeatable.

Every week, I take an AI workflow that has led to genuine business impact from experts across industries, and create a ready-to-implement graphic so anyone can get started. If you’d like this in your inbox every Wednesday and more, subscribe to The AI Strat newsletter.

A senior leader at OpenAI said in a recent interview that people should be prepared to defend themselves against AI-powered cyber attacks as the technology continues to advance.

The interview arrives over a month after OpenAI discovered its systems had autonomously breached another organization, Hugging Face.

Cybersecurity experts warn that the comments made by senior OpenAI leadership represent a critical moment in AI development. Organizations need to remain vigilant and be aware of the potential damage attacks cause.

AI Cyber Attacks Will Be ‘Ongoing’ and ‘Persistent’

Chris Lehane, chief global affairs officer at OpenAI, said people should be prepared to defend themselves against AI cyber attacks. He claimed attacks will be “ongoing” and “persistent,” in an interview with the Guardian.

“We are hitting a different chapter, a different moment within AI, in terms of what the capabilities of this technology can do,” Lehane said.

Similarly, Lehane warned against open-source models, many of them Chinese-owned. These models have gained coverage in recent months because of their low prices, and it’s believed they’re only a few months behind frontier models like ChatGPT and Claude when it comes to performance.

“People are going to be able to access these open-source models and be able to have ongoing, persistent attacks on you, and you’re going to need to have really superior models to fend them off and defend [yourself],” Lehane commented.

More on OpenAI/Hugging Face Breach

Lehane took this interview over a month after an OpenAI agent autonomously breached the AI learning platform, Hugging Face. Since the incident, the AI firm has given further details about how the attack unraveled.

To complete the hack, TechCrunch explains the OpenAI model chained together “previously undiscovered exploits” to bypass security measures, after it was given an impossible task during testing. Through the compromised package management tool, Artifactory, the model accessed the internet, and then compromised various systems including OpenAI and Hugging Face.

According to the independent AI research firm METR, before the attack, agents that were meant to be kept apart found a way to start communicating. The agents exchanged more than 70,000 messages on an “unsanctioned message board,” which would lead to more than 700 agents collectively attacking Hugging Face.

METR believes the agents communicated because they had “unintentionally been given an impossible task” during testing. Therefore, the agents banded together to try and find ways to cheat, which included exchanging messages and gaining access to the internet.

As well as providing more details on the Hugging Face incident, OpenAI’s report outlines its new security measures for its models. The company is increasing its monitoring of an agent’s “chain of thought,” a space where systems report short-term reactions and goals. It will also implement 24/7 escalation systems and new tooling to stop unsafe workflows.

On August 18th, OpenAI also announced it had paused training on some of its frontier AI models to implement new safeguards.

OpenAI Warning Is a ‘Significant Moment’

The alarm bells around security and AI have been ringing for some time now. Cybersecurity experts continually warn against the threat these systems pose.

However, the OpenAI/Hugging Face breach represented a shift. Yes, we’d seen AI speed up attacks and create new ones. But for an agent to attack an organization without being instructed to and dodging human awareness in the process, future incidents seem pretty terrifying.

Especially since OpenAI isn’t the only company reporting these kinds of incidents. Not long after disclosing the Hugging Face attack, other major players such as Anthropic and Meta revealed their own agents had been involved in autonomous hacks.

“The interview with The Guardian comes days after the company paused training on its most advanced models and disclosed that a test system reached production infrastructure it was never meant to touch.” Darren Guccione, CEO and co-founder at Keeper Security, tells me. “The admission reinforces that offensive AI capability is arriving faster than organization defenses are dispatched to meet it.”

Similarly, Guccione called the incident behind the warning “illustrative and stark.”

“A model operating with expanding permissions inside a testing environment found a path to open the internet, and from there, to real credentials. That points directly to a governance failure rather than the perceived capability of the model in question. Any system holding standing access and network reach, whether a production service account or a research sandbox, is functionally a privileged identity and needs to be governed as such.” – Darren Guccione, CEO and co-founder at Keeper Security

Likewise, Oliver Simonnet, lead cybersecurity researcher at CultureAI, told Tech.co all organizations should be preparing for persistent attacks from autonomous AI systems. And, AI developers should be investing in “significant R&D” to prevent these attacks.

“If the future is as AI-pervasive as it seems it will be, both attack and defense activities will happen at a scale and speed we’ve never seen before or had to operate within,” Simonnet said. “Organizations will need to ensure they have access to tools and technologies that provide the appropriate visibility and defensive capabilities to successfully operate in that type of landscape.”

This article is part of an interview with Alexander Berger, chief operations officer at Bolt.new. This interview was conducted for Tech.co’s AI newsletter, The AI Strat. For more interviews with AI experts on the latest trending topics, subscribe to the newsletter. 

There’s a lot on your plate as a business leader. When it comes to AI, the temptation might be to sign off on a ChatGPT or Claude subscription, alert your chief technology officer, and call it a day. You might be wondering, do I need to know how to use these tools myself?

Alexander Berger, chief operations officer at Bolt.new, believes this is a valid question to ask. Especially if you’re not the person who’s going to get hands-on with these tools every day, he said, during an interview with Tech.co.

However, he believes leaders should develop what he calls the right “mental models” when their company adopts AI, as they could be missing out on key benefits. Likewise, if businesses are looking to reimagine themselves completely with AI, then leader knowledge becomes vital.

Business Leaders Should Learn Some AI, Expert Says

As a business leader, you might believe putting AI in the hands of your tech team is enough. And yes, while your tech experts will have the best AI knowledge, that doesn’t mean leaders shouldn’t interact with the technology themselves.

Alexander Berger, chief operations officer at Bolt.new, believes leaders should take a different approach. “I strongly believe that if you want to be a leader in an organization that’s very AI-focused, you can benefit immensely by getting into the tools and prompting yourself.”

“Not necessarily because you’re going to be the one doing the work or squeezing the value out of the tools,” Berger adds. “But because developing the mental models around what is even possible to do with the tools and how you work with them is very hard without actually going and using the tool yourself.”

Building the ‘Mental Models’ Around AI Use

Bolt.new is a vibe coding tool, which allows users to build websites by prompting AI with natural language. Berger tells me he has built websites since he was a teenager, so when he joined Bolt, he wasn’t completely in the dark about how it all worked. He had, as he calls it, the right “mental models.”

The first time Berger tried to build something agentic was Valentine’s Day weekend of this year. “It wasn’t until I actually built that, that I really understood what an agent is, and how to construct it.”

You can read about it and get the general gist, Berger explains, but you won’t develop that mental model by just observing. You need to get stuck in. “Until I had those mental models, it was shocking to me how much I really didn’t understand.”

Some studies have suggested AI expertise is concentrated. Companies have what is called “AI champions,” or, people that know AI best. These individuals are usually where wider AI integration starts, and many experts suggest empowering those that know AI leads to business success.

According to Berger, being able to use AI tools as a leader makes it easier to know who to uplift. You get the ability to “actually identify” those AI champions, “and I think that’s really important because you should elevate those people in the organization.”

Backing the wrong people could lead to bad outcomes, Berger adds. They’ll leak data, emails get sent to the wrong client, agents go off the rails, and so on.

Similarly, another benefit of knowing these tools as a leader is being able to get the maximum out of them. “Just understanding these tools, even if you’re not the best person on your team skill-wise, it will give you the ability to ask your team for things like this operational platform tool, that does XYZ.”

“You’ll have enough knowledge about what’s possible with the tools to provide some direction,” Berger says. Without this leadership direction, AI use becomes much more trivial.

Should All Leaders Know How to Use AI?

Learning a new tool like AI takes time. Though Berger recommends leaders get to grips with AI, he admits in some cases, it might not be necessary. If, for example, you’re only looking to build a website with Wix’s AI builder, then you don’t need to get too deep on how that works.

If, however, you want to build more advanced tools, then learning AI becomes more important.

“If you want to build more complex tools… you probably, as a leader, are going to need to build some mental models to even be able to work with your team and understand what’s possible.” – Alexander Berger, chief operations officer at Bolt.new

Some businesses are reimagining entire processes with AI, by understanding new ways to automate tasks and enhance productivity. To do this in the most effective way, direction is needed, and this is where leadership knowledge becomes especially important. Otherwise, you’ll end up with a new tool, and nowhere to put it.

Although, there is evidence to suggest that leaders themselves feel they haven’t received enough AI training. This could lead to companies not using AI to its full potential, or worse, failing to keep themselves and their data safe. All the more reason for leaders learn as much as possible.

You’ve probably heard of how AI has changed hiring. Candidates are using AI to generate and fine-tune resumes. Simultaneously, HR leaders are using it to screen those resumes. However, sentiment from leaders on the technology appears to be mixed, according to a recent study.

On the one hand, AI is helping candidates beyond resume construction. Some AI tools offer real-time interview support, allowing candidates to respond to interview questions with generated answers, or even manipulate video and voice footage.

Ultimately, human contact remains the surest way to decide whether a candidate is suited to a role. Where the role suggests, leaders should aim to meet in-person with candidates, to see whether there is a culture fit as well as a capability perspective.

HR Leaders are Unsure About Candidates Using AI

In a recent study from HireVue, HR leaders appeared mixed on candidates using AI. While 62% of leaders considered the use of AI smart, 31% viewed it as cheating. 

However, the report concluded 71% of candidates use AI to write resumes, indicating the technology is becoming a common tool for those seeking roles.

Some might say it’s contradictory for HR leaders to discourage the use of AI among candidates. Especially since HireVue also found 77% of HR leaders use AI weekly or daily. Most likely, AI is now commonplace on both sides.

AI Is Allowing Candidates to Cheat at Interviews

Before AI, candidates were still exaggerating applications. AI has enabled them to do this faster, and even generate entire resumes without writing a single word. Beyond this, AI has led to the development of new tools that help candidates in a new way.

In one extreme example, recounted by Miki Blasko on LinkedIn, a candidate was suspected of using AI to generate real-time answers to interview questions. Suspicions were confirmed after the candidate’s AI notetaker, on accident, shared the meeting notes with the recruiter at the end of the meeting.

Then, Blasko explained, the candidate forgot to leave the call, and was heard speaking in Hindi and laughing with their colleagues about being caught. The candidate had originally stated they were Polish. At this point, Blasko suspected the candidate was using a voice/accent changer and visual filter to make themselves appear more European.

Following an analysis of over 19,000 AI interviews conducted on its platform, Fabric found 38.5% of candidates were flagged for cheating behavior. Fabric describes cheating as using invisible overlays on screens and using ChatGPT or Gemini’s voice mode and reading the answers it generates.

The report suggests candidates see AI assistance as a standard interviewing tool. This argument does carry some weight, especially if there’s evidence the person interviewing you is also using AI.

In fact, HireVue found 35% of hiring teams use AI for candidate screening, and 43% use it for resume screening. Although, whether AI should be used in interviews, where culture fit and professionalism is also tested, is up for debate.

Likewise, candidates in the Fabric study said they believed their competition was using AI anyway, so they needed to use it in order to stay competitive in today’s bleak hiring landscape.

How to Adapt to AI in Hiring

HR leaders need to adapt to AI being part of the hiring process, according to Alon Pearl, founder and CEO of recruitment agency VA Masters.

Pearl advises leaders to treat the resume as a guide. Leaders should ask follow-up questions to validate achievements, and use a short, role-relevant work sample to decide whether a candidate is capable of doing the job.

Similarly, Pearl says leaders should set clear rules from the start about AI use within their hiring processes.

“Tell candidates in advance whether AI is allowed during applications and assessments. If it is, ask them to explain what they accepted, changed, or fact-checked in the output.” – Alon Pearl, founder and CEO at VA Masters

Asking candidates how they used AI, and why they used it a certain way, could be a good way to generate trust between hiring teams and potential hires.

Plus, AI skills are now an attractive quality to potential employers. Understanding how a candidate has used AI could indicate their overall fluency. Obviously, there are limits to this, which will depend on your company’s own AI policy.

Human Understanding Still Provides the Best Judgement

Additionally, Pearl says HR leaders shouldn’t be focused on trying to detect whether a candidate has used AI. He describes a kind of nuance when it comes to AI use, especially as individuals can use the technology in different ways.

“A candidate may use it to tidy up their wording and still be excellent at the job. Another person may write every word themselves and exaggerate their experience. The better question is whether they can explain what they have done and show that they can do the work.” – Alon Pearl

Pearl ultimately suggests hiring should focus on whether candidates can do the work and explain their experience. While AI has enabled candidates to appear competent, “presenting yourself well has never been the same thing as doing the job well,” he explains.

Instead, “employers now need a clearer line between what candidates claim and what they can demonstrate.”

For roles that are hybrid or in-person, this should mean getting to know someone beyond a video interview and resume screening. Often, hiring leaders should be looking at how candidates fit in to their company culture and goals, as well as whether they can do the job they’ve applied for. This is where in-person, human understanding is most valuable.

The leaders of the world’s top organizations most likely have a horror story or two about their safety being compromised. Sam Altman, CEO of OpenAI, for example, recently had a Molotov cocktail thrown at his house.

Social media has made executives more visible online, as has the changing nature of leadership. Similarly, AI makes gathering personal information easier, and impersonation and voice scams have become more sophisticated through AI use.

I spoke to Olga Polishchuk, vice president of investigations at ZeroFox, who deals directly with digital exposure and how it can compromise organizational and personal safety. The point isn’t to be invisible, she says. Instead, what’s most important is removing and monitoring what’s available online.

Digital Environments Can Advance Executive Attacks

The issue of executive attacks is nothing new, Polishchuk tells me. “What’s different is how much we can learn about somebody without getting physically close to them,” she says.

Across social media platforms like Instagram or LinkedIn, individuals are encouraged to share their lives online. What started as a point of connection, however, has evolved to become a larger ground on which to stage an attack.

Everything from corporate appearances to family social outings can be used to establish a pattern of predictability. Whatever criminals are missing, it’s likely they can get from data brokers, who provide information like residential history and personal information like date of birth, at a very low cost.

Polishchuk says when you look at the information out there on an independent level, it’s not so concerning. But, when it’s used to together, to build what she calls “a pattern of life,” then it becomes a problem.

AI Is Accelerating Threats, Human Instincts are Dwindling

The tools attackers are working with have also improved. AI is frequently employed in impersonation attacks, through the creation of deepfakes and for voice phishing scams. Similarly, Polishchuk points out how consumer AI tools can also be used to crawl the internet for information on executives.

“It’s so easy to bypass ChatGPT or Claude’s more ethical barriers and guidelines,” she says. By choosing the right prompt, for example, you can get AI to generate what would be a very convincing spam email.

Polishchuk works with executives to help them deal with these new threats. She tells me a lot of them are clicking on these emails, convinced by what they’re telling them. “Human instincts no longer work at this point,” she says.

We’re no longer in a world where it was easy to discern what is AI, and what isn’t. The models have developed, and they’ve done it fast.

Our old methods of discerning what is trustworthy through human instinct may be increasingly void. Polishchuk points out that a lot of things we used to use to determine trust, like someone’s face on a call, or their voice, can be easily fabricated using AI.

However, Polishchuk does believe human instinct will still play a role in safety. “I don’t think human judgement is obsolete, but I think that familiarity as a form of authentication might be becoming that.” What we’ll have to do, she explains, is change the way we’re identifying threats.

Navigating Modern Leadership with Increased Online Visibility

Despite these threats, it’s unrealistic to tell modern day leaders to be invisible online. The demands of the role have changed; consumers like brands and leaders they can relate to, and a lot of this comes with having a unique voice. Similarly, executives still need to make public appearances, and even write the occasional press release or take an interview.

I asked Polishchuk how executives can manage their visibility. “I would tell them to be intentional about what is visible,” she says.

“There’s a big difference between professional visibility and personal predictability. If people know you’re speaking at a conference, they don’t need to know what hotel you’re staying at, or if you ran a marathon.” – Olga Polishchuk, VP of investigations at ZeroFox

On the topic of marathons, she explains instances where executives have been targeted on their local running route, after they had posted it to online fitness apps. This is the kind of visibility you might not think of as a threat initially.

Polishchuk isn’t telling executives not to live their lives. It’s important, for both personal and professional wellbeing, to be visible. Instead, executives shouldn’t let it get to a point where their personal movements and routines can be mapped out. Like through their morning run, for example.

“What we’re trying to help them understand is which information creates exposure risk and which serves a legitimate purpose. Visibility isn’t always a problem. It’s the predictability that is,” she says.

How to Protect Your Leaders and Organization

Preparation is key. Polishchuk recommends that businesses should “start thinking like an adversary” before any threats reveal themselves. “Pick your top five executives and look at their online ecosystem: what surrounds them, what kind of information is publicly available,” she says.

From the information you find, determine if it can be used to establish a person’s routine. “It’s really more about eliminating unnecessary exposure,” she adds. Once you’ve reduced what’s not needed, continue to monitor the situation.

“Digital exposure is not a one-time thing. It’s a condition that you have to manage.” – Olga Polishchuk, VP of investigations at ZeroFox

Similarly, when I asked Polishchuk what’s most important for businesses today, education was her top choice. Understanding what’s out there, and what kind of information threat actors are going to go after.

This extends beyond the organization and the leader as well. “We meet with children, we meet with spouses, and we just use examples of their exposure to provide different scenarios.”

All of this will ensure everyone involved understands the risks and will help protect your leaders and your business, in the long run.

This article is part of an interview with Jena Wuu, writer, speaker, and advisor on trust and expertise online. This interview was conducted for Tech.co’s AI newsletter, The AI Strat. For more interviews, with AI experts on the latest trending topics, subscribe to the newsletter.

AI is speeding things up. Email marketing is automated, cyber attacks work on a bigger scale, and more content proliferates social platforms. In turn, users have responded and continue to respond with dismay, annoyance, and sometimes outright hostility.

Trust, arguably, is eroding online. Swaths of AI-generated posts make it difficult to know who is authentic and genuine. However, recent moves made by LinkedIn and Substack could help users pinpoint what content is AI-generated, but should we start being honest from the get-go?

I spoke to Jena Wuu, previously Global Policy Programs Head for Social Impact and Information Ecosystem at Meta. In the age of AI content, transparency and trust are more important than ever, and how we choose who to trust is changing.

There Is More Content Online Than There Used to Be

You wouldn’t get any strange looks if you said it’s harder than ever to get attention online. Social platforms are drowning in content, from cute cat videos to tech bros advertising productivity regimes. Part of this is because of AI.

AI tools, mostly generative ones, have made it easier for individuals and companies to produce content en masse. There are AI brainstorming tools, AI script writers, AI video editors, even AI actors.

Most recently, a study from Pangram found almost half of all LinkedIn long posts are AI-generated.

Shortly after these findings became public, LinkedIn announced a ‘seems like AI slop’ button, that users could click if they felt a post used AI. Just over a week before this, online publishing and blogging platform Substack released an AI detection tool.

“I think there is a common misperception out there that platforms want to be perpetuating low-quality content,” says Jena Wuu, a writer, advisor, and speaker on trust online.

Previously, Wuu was a Global Policy Programs Head for Meta, and pitched its Global Information Ecosystem program. She tells me AI content poses a lot of risk to today’s platforms, “because users don’t want to engage with inauthentic content, and advertisers don’t want to be on platforms where there are inauthentic users.”

For Wuu, these new tools from Substack and LinkedIn are a positive thing, provided people use them. “If we could all be active in telling platforms about what kind of content we want to see, that’s where platforms are going to prioritize.”

These tools are forcing AI users out of the shadows. The people scrolling past will know if you’ve used AI, or not. What’s most interesting, Wuu argues, is how people will interpet content that is flagged as AI-generated.

AI Is Generally Disliked and Called Out Online

NBC News reported in March that people generally like AI less than they like ICE in the US. From an online perspective, one doesn’t have to look very far to find an instance of a user being called out for using AI, and reactions are rarely positive.

Wuu thinks there are quite a few reasons why AI sentiment is mostly negative. First, AI companies haven’t done a good job of building trust with users. Secondly, people feel a loss of control, and that the technology is being forced upon them.

“I think that there’s a feeling of a loss of control about it, and people feel like it’s being forced on them. And so if they’re on a platform where they’re there for leisure and relaxation, or they’re genuinely trying to look for information, then of course it’s going to be agitating when you’re seeing all this and having all of this forced on you again.” – Jena Wuu, writer, advisor, and speaker on trust online

Likewise, the impact on jobs is still pretty uncertain. “We don’t know what the impact of AI is going to be on our jobs,” Wuu says. All of this would contribute to why someone seeing AI-generated content, on a platform they’re on for leisure, would feel frustrated.

This is another way using Wuu’s call for people to participate, by using the LinkedIn AI slop button, for example, could lead to a shift away from AI content on social platforms. However, the black-and-white nature of these tools is a point of concern.

In my opinion, not all crimes created with AI are equal. On one end of the spectrum, you have people generating entire content suites with AI. On the other, you might have someone who uses AI as part of their research process, or as a way to ask for constructive feedback. The LinkedIn AI slop button, for instance, doesn’t state how someone has used AI.

From Wuu’s perspective, this is why human judgement remains critical. Everyone has a different tolerance for AI, she explains. Some people won’t mind entire posts generated by AI, others will. Over time, people will figure out their preferences, and this will shape the future of social platforms.

Giving People Context for How You’re Using AI

There are legitimate reasons why someone might use AI to create content. A lack of social media experience, or a lack of a budget, for example. Not everyone is a social media star, and in some way, AI has allowed everyone entry into the world of content, despite their background.

Content isn’t the exception, either. Vibe coding platforms allow non-coders to make websites. Anyone can have any concept explained to them in simple terms by just asking a chatbot.

Overall, I believe everyone should be transparent about AI use. It would remove the guesswork, and inspire transparency and trust. LinkedIn, with its new button, and Substack with its detection tool, are giving users this opportunity. Like many things, Wuu agrees AI use is nuanced, and that context is critical for how we approach it.

“What I would love to see is for entities and creators to have some kind of transparency about how they use AI. And that’s something that Substack is doing, they’re offering writers a way to make a statement about how they approach the use of AI. I think that’s a really good thing to have because we need context.” – Jena Wuu

Additionally, disclosing how you’ve used AI will provide some protection. If your content does get flagged as AI, for example, you’ll have details to back up how exactly you’ve used AI, if you have at all.

Recently, Anthropic announced all of the content generated by its Claude models would include a watermark. This is a feature already done by Google’s Gemini, and more AI companies may have to follow suit with similar approaches to stay in line with the recent EU AI Act, which includes a Code of Practice on Transparency of AI-Generated Content.

So, there’s a future where all AI-generated content needs to be identified as such. This certainly promises to foster a culture of trust we’ve lost on social platforms.

Ultimately, when people are browsing online, they are drawn to content they can trust. Wuu says building this trust involves having a human element to what you’ve created, “at the end of the day, people trust people,” she says.

The most important thing for brands to do in 2026 is be authentic and trustworthy. This might not mean getting AI to generate posts for you. It might mean using AI to some extent, but truthfully, nobody wants to hear from AI. They want to hear from people.

A new study finds organizations haven’t redesigned jobs around AI yet, despite the technology making massive waves across the industry.

Currently, companies are focused on employee training and education, encouraging workers to become AI fluent. However, it’s still believed entry-level roles will drastically change due to automation.

Across several studies, AI has led to productivity gains for workers. Trust is also increasing from business leaders, although workers remain skeptical.

Prioritizing AI Fluency Over Job Redesign

According to a new study from Deloitte, 84% of companies haven’t redesigned jobs or changed the nature of work to fit current AI capabilities.

In reality, companies are focused on educating employees on AI. Overall, the study finds insufficient worker AI skills are the biggest barrier to AI adoption. But, less than half of companies reported making changes to their talent strategies to reflect this.

Within a year, 36% of companies said they expect at least 10% of their jobs to be fully automated. When looking ahead three years, this number increases to 82%, suggesting belief in AI as a transformative tool remains high.

AI Training Remains Key, But Entry-Level is at Risk

When introducing a new technology, it’s important to give employees the time and space to understand it. Given the speed at which AI has been developing and companies have been investing, it’s no wonder workers are falling short in their understanding of what AI can do.

In a recent study, almost 40% of employees revealed they hadn’t received any AI policy information at onboarding. Of those that did, over 1 in 10 said they’d retained little to none of it. This not only poses serious security and data risks for businesses, but it means workers could be approaching AI with little to no understanding of how it works at their companies, slowing down progress.

On the other hand, leaders in qualitative interviews with Deloitte expressed concern about the potential disruption of job trajectories. This is because entry-level jobs including data entry, reconciliation, and first-level customer support are being prioritized for automation at their companies.

Entry-level roles might be easily automated, but they’re also an important stepping stone for individuals to develop themselves within the workplace. Experts have suggested the requirements of entry-level roles will most likely change with AI. Instead of showing they can punch numbers effectively, new hires will have to demonstrate qualities such as leadership and judgement.

Employees Remain Skeptical Despite Gains

AI productivity gains have been well-reported on, and it seems plenty of workers and businesses are seeing benefits. In the study, 25% of leaders report AI is having a transformative effect on their companies.

Similarly, 84% of organizations are increasing their AI investments, and 78% of leaders report greater confidence in the technology.

Leader backing is only one side of the coin. Workers need to be actively using and supporting AI initiatives in order for true transformation to occur. And, in its report, Deloitte described worker sentiment around AI as “cautiously positive.”

Numbers-wise, 13% of non-technical workers are highly enthusiastic about AI, and are proactively trying to use it. 55% are at least open to using AI. However, 21% prefer not to use AI but will do so if required, and 4% actively distrust and avoid the tech.

There still seems to be a lack of trust in AI. Not helped, of course, by the negative portrayal of what AI will do to jobs — and humanity in general — by leaders of frontier AI labs. Likewise, with many companies reportedly replacing workers with AI, or citing AI in layoff announcements, it’s understandable workers will approach the technology with caution, and sometimes disdain.

On the extreme end, in a study from Writer and Workplace Intelligence, 29% of workers admitted to actively sabotaging their company’s AI strategy.

Ultimately, companies should strive to position AI as a co-conspirator, rather than a replacement. Organizations should provide the right training and encouraging employees to experiment and use AI in a way that makes sense to them.

As a small business owner, you’re juggling a lot. Operations, marketing, hiring, and much more. The worst thing to worry about, however, is budget.

Being awarded a small business grant gives you new opportunities to accelerate your business forward. Not only will you get funding, but some grants offer support in areas like marketing and technology, lessening these burdens on your shoulders.

Below, I’ve rounded up the grants small business owners can apply for in August, how to apply, and how much you’ll receive.

The Sky is Not the Limit Social Impact Grant

• For: organizations with a clear, measurable social or environmental mission
• Amount: up to $10,000 in services
• Deadline to apply: August 19

Bombshell Impact Design agency is offering this grant on a pro bono basis, for businesses to enhance their marketing strategy.

The money can be used for professional branding, website design, campaign strategy, content creation, and “AI for Good” services. Investing in your marketing is key if you want to stand out as a brand in 2026, especially as AI content continues to populate today’s social platforms.

The grant is ideal for nonprofits or social enterprises, for example. To apply, you’ll need to submit a 30-60 second video.

Apply here

Hey Helen Grant

• For: 100% women-owned or non-binary aligned for-profit US businesses generating under $1 million in revenue
• Amount: founder is given $10,000 in unrestricted cash each cycle
• Deadline to apply: August 30

This is a privately funded initiative from Visionaries, offering founders $10,000 each cycle to spend on whatever needs improving in their business. This could be operations and growth, or even infrastructure.

For women and non-binary individuals, this is a great opportunity to prioritize the areas in your business that could use the additional funding.

To apply, heads up, you’ll need to purchase a ticket to the MYP Money Moves Summit, which costs $300. The form does give you a $50 discount, however. The summit includes a pitch competition which will determine who gets the grant. You’ll also need to submit a 60 second reel to Instagram, and tag @_manifestyourpurpose.

Apply here

Shophand Small Business Boost Grant

• For: small business owners wanting to boost their technological understanding
• Amount: $2,500 in cash, $2,500 in Shophand technical support
• Deadline to apply: December 1

If you’re looking to integrate technology into your business, Shophand offers small business owners both cash and specialist support. This could involve AI tools and automation, creative and media support, marketing and tech support, operations overhaul, software setup, and much more.

The website encourages “non-techie small business owners” to apply for the grant, awarded three times per year. The FAQ section says they’re looking for a clear business story, a meaningful challenge, and a commitment to improving your business.

There are quite a few requirements for this one. You’ll need have fewer than 50 employees, generate under $5 million in annual revenue, and be a for-profit business actively operating. I’d double check the website before applying for a full list of requirements.

Apply here

Verizon Small Business Digital Ready Grant

• For: owners of for-profit small businesses
• Amount: $10,000
• Deadline to apply: December

Verizon has helped over 1,500 small businesses across the country since 2021 with this small business grant.

Priority is given to small businesses that have never received a grant before. So, if you’re relatively new to the game, or have been trying for a while to secure a grant, you’re at an advantage.

If you’re applying, you’ll need to have an account on Verizon Small Business Digital Ready, and have completed several courses on the Digital Ready platform between January 1 and December 7 2026. Nonprofits aren’t eligible to apply for this one either.

The application supposedly takes about half an hour to complete and you can apply online.

Apply here

The Importance of Small Business Grants

The world of small business is changing, and it can be dizzying trying to keep up with it all.

Securing a grant allows you to get ahead in the game, and improve the areas of your business budget hasn’t yet allowed for.

Likewise, it could also help you gain knowledge on an area outside of your usual expertise, like marketing or technology, and make you stand out to investors as a business worth betting on.

Luckily, many grants are free to apply for, and you lose nothing by giving it a shot.

Anthropic will now watermark AI-generated content produced by its models, in order to comply with the EU AI Act that came into effect at the beginning of this month.

The general public have increasingly soured towards AI-generated content. While some studies suggest consumers don’t mind as long as content is relevant to them, watermarks could make AI content obvious and open creators up to criticism.

Users deserve transparency around what has been involved in creating a piece of content. Not all crimes committed with Claude are equal, but we could see users start to prioritize authenticity and originality when interacting online.

Anthropic Plans to Watermark AI-Generated Output from Claude Models

Leading AI lab Anthropic announced plans earlier this week to watermark AI-generated content, coming from its Claude models. The marking applies to models launched in the EU on or after August 2, and the company have plans to add the same feature to previous models.

The move will help Anthropic comply with the EU AI Act, which came into effect earlier this month. The regulation includes a Code of Practice on Transparency of AI-Generated Content.

As well as watermarking content, Anthropic said in a supporting post it would “support users and other third parties to detect Claude’s marks.” Watermarking is done in two ways, the lab further explained: embedded watermarks in text, and signed provenance metadata for files, including images.

A Potential Solution to Allegations of AI Use

Anthropic isn’t the only company to pledge to abide by the new European AI act. OpenAI, Meta, and Microsoft have all committed to this legislation, the first of its kind when it comes to policing AI models. So, while the terms may be different for each company, similar moves around transparency of AI-content will continue.

For the record, the watermarking of AI content isn’t a new thing. If you create an image using Google’s Gemini, for example, the lab’s logo appears in the bottom corner.

However, if all AI-generated, or I should say, AI-tampered content (based on Anthropic comments I’ll talk about later) is watermarked as more companies adapt to the new legislation, it will provide a new avenue of accuracy to detect AI content.

Consumers will receive this well, especially considered AI writing isn’t always easy to identify, and AI detectors aren’t always that accurate. Yes, tools like Pangram boast a false positive rate of only 1 in 10,000, but that hasn’t stopped Reddit users from complaining about their work being wrongly flagged as AI-generated.

Similarly, with clear indications of what content has traces of AI, users won’t be wrongfully pointing fingers. A recent study found a significant number of LinkedIn posts are AI-generated, which may or may not have led to LinkedIn adding a ‘Seems like AI slop’ button to the platform.

While the tool is useful at a glance, it leaves the user to decide whether content is AI-generated or not. It’s likely to deter some people from using AI in posts, however it’ll also mean those who aren’t using AI, but maybe enjoy the occasional em dash, are at risk of being penalized. A watermark in this case becomes a stamp of innocence, or an admittance of guilt.

An Uplift for Transparency in Today’s Content Landscape

Hopefully, AI companies identifying what content came out of their models will increase trust online. Users can interact with content generated by humans, if that’s their preference, and avoid content that doesn’t suit them.

However, as more and more people use AI in content, the practice will be normalized. What will be more important is how someone has used AI. In my eyes, not all crimes committed with Claude are equal, and there’s a big difference between light edits and a fully generated text.

In some cases, using AI tools like Claude gives people the option to communicate better and share their ideas. These people shouldn’t be penalized as much as the person plugging prompts all day, and copying and pasting to publish.

Unfortunately, it doesn’t look like the watermarking system at Anthropic will consider how AI was used. In its statement, Anthropic said: “People often use Claude to proofread, translate, summarize, or convert files. The output can carry a Claude mark even if the underlying ideas, text, or data originated from another source.”

Ultimately, users have a right to know if a piece of content is AI-generated. For brands operating online, being authentic while valuing the human voice might become a badge of honor.

Employee productivity tracking isn’t new. Companies across industries have been using tools to track employee activity for decades, sometimes through simple URL and calendar monitoring, or through more extreme cases like screen recording.

AI is enhancing the capabilities of these tools. The technology can provide real-time insight into employee activity, allowing managers to monitor productivity with greater accuracy. While this can bolster performance, leadership risks diminishing employee freedom and trust.

I spoke to Sam Naficy, CEO of employee productivity software Prodoscore, and Dr. Kyle Elliott, a tech career coach, about the topic of AI-enhanced productivity tracking tools.

AI is Changing Today’s Workforce

Middle management is important to Sam Naficy. He believes these roles will become increasingly more essential as AI continues to impact work. This belief underpins his work at Prodoscore, the employee productivity monitoring software, where he is CEO.

“I think AI will make good employees very good,” Naficy tells me. His software, he says, lets managers and employees alike answer the question of: how do you replicate good?

While Naficy has spent his career focused on managers, Dr. Kyle Elliott sees both sides of the coin. For the past nine years, he’s been a tech career coach in Silicon Valley, matching clients with roles at Meta and Google, for example. He works with both tech executives and HR leaders, and so has access to not only how AI is being implemented, but how executives are reacting to it.

“The sentiment is mixed,” he tells me. “Most of them are like, this is just part of tech. Tech is constantly evolving and we’re always having some sort of new innovation, new change come out, and we have to adapt to it.”

The Case for The Ambitious Employee

Prodoscore is an employee productivity monitoring software that aggregates data from cloud-based tools. It doesn’t track URLs, mouse clicks, or access the camera. Naficy explains how it should be used for managers and employees to replicate what a good employee looks like.

During our interview, he gives an example involving the two of us. He’s an average employee, I’m a great one. If he’s a good employee, he’ll want to learn from me, to become better. Prodoscore provides what he calls a “blueprint” for how, in this case, he can become more like me.

“If you’re a good employee of any organization, you want to thrive. You want to see what good looks like, and who is doing a good job.” – Sam Naficy, CEO at Prodoscore

Increased visibility for employees could lead to better performances. It gives people exactly what they need to emulate the success of another in their role, and to get better at what they do, which is beneficial for both employee and company.

However, Elliott argues top performers might falter under a system of consistent tracking. For example, if management are monitoring key strokes, or the content of an employee’s calendar, employees may just wiggle their mouse, or fill up their calendar with meetings, for the sake of appearing productive.

In that case, ambitious employees might become complacent. No need to actually do any work when it appears you are, and are being rewarded for it. It therefore takes consideration, according to Elliott, about what’s important for your company to track.

The Importance of Transparency and Trust

In the context of AI tracking tools, Elliott believes the relationship between manager and employee is changing, and might be at risk. Not only are these kinds of tools suggesting “we don’t trust you, so we need to monitor you,” according to Elliott, but it’s giving managers a scapegoat to avoid having difficult conversations with employees.

“Instead of saying your performance is not meeting expectations, your output’s lacking, instead they can just point to keystrokes or mouse clicks instead of having a real conversation,” he explains.

These kinds of conversations are what create company culture, by growing individual relationships between workers and their supervisors. Managers aren’t just there to ensure their employees are working. Employees want to feel seen and heard by management, especially if they’re going through a hard time.

Naficy makes it clear his technology is not meant to be punitive. He acknowledges that a big reason for declines in performance at work could very well link to personal troubles, and that productivity tools provide “a coaching opportunity for the manager.” Like a nudge, he suggests, for them to speak with an employee to see what’s going on.

Where both Naficy and Elliott agree is on the topic of transparency. Naficy calls his solution deliberately “employee-centric,” which is why all of the data Prodoscore provides goes to the employee, first and foremost.

“I think there is monitoring that’s legitimate and you have to be really clear about what’s being monitored, and then communicate that to employees because they’re going to find out.” – Dr. Kyle Elliott

For Elliott, what’s most important is being honest and open with employees. “You have to be really clear about what’s being monitored,” he says. “Is it time on your computer? Is it taking screenshots?”

In fact, Naficy argues these tools can increase the amount of transparency an employee receives on company decisions. He gives the example of 360 reviews becoming more objective, based on concrete productivity data derived from the tools you’re using day-to-day.

The Kind of Work That Can’t Be Tracked

During our interview, Elliott points out with a smile that I’m not touching my keyboard.  He asks, “Does it know we’re engaging?”

This is a problem with the spine of productivity monitoring tools: what constitutes productivity? Who’s to say I’m not being productive away from my desk, having a conversation with a colleague, or even having a conversation with Elliott for this article? The laptop gets none of that productivity, from a data perspective.

Elliott mentions a recent call he had with the director at a Fortune 500 company. “During our call, she is literally wiggling her mouse the entire time because she doesn’t want to be shown as idle, because it’s a metric they track.” In this case, it’s obvious the wrong thing is being tracked.

A similar case can be made in regard to creative work, which often falls outside the confines of typing on a computer. Ideation, brainstorming, prototyping, all of this is productive work, but it can’t necessarily be tracked as easily as clicks.

“That person that’s playing pingpong with a colleague and having a conversation, that person’s going on a walk with a colleague, that person’s going on a walk by themselves… I think that’s the most important work, that human work.” – Dr. Kyle Elliott

This work, according to Elliott, is “the most important work” an individual can do. Coffee-trip conversations with colleagues can spark ideas, a problem we’ve been sitting with for weeks can unravel with an afternoon walk. This is the kind of meaningful work that moves companies, and should contribute to how valuable an employee’s day has been in the eyes of a manager.

Anything that is monitored, therefore, should take into account the whole picture. As AI changes the way that we work, and what managers and employees need within companies shift, leaders should remain flexible and open to new ways of recording wins.

In a recent study, managers were the only role to show a significant productivity lift with AI use, suggesting these roles are emerging as the biggest winners of the AI era.

Reports of individual worker productivity with AI circulate regularly. Undoubtedly, however, the decisions and tasks carried out by managers and senior leadership will impact employees, which means we could see big changes to both executives and juniors as AI becomes more integrated into workplaces.

Today’s managers are using AI in different capacities. Many are seeing productivity benefits, but all agree the real win is expanding these gains to the rest of the company. I spoke to managers across various industries to find out where the future of management lies now that AI has entered the building.

New Study Finds Managers are Seeing the Highest Productivity Lift Thanks to AI

In a new study from Prodoscore, managers recorded the highest productivity uplift resulting from AI use.

“We felt a manager’s role relies on collaboration, communication, and reviews of your subordinates. All of those activities and actions AI could really help [with], so they’re motivated to use AI,” says Sam Naficy, CEO of Prodoscore, in an exclusive interview with Tech.co.

Overall, Prodoscore recorded a 14.6 day annual uplift in productivity for AI adopters, equating to roughly three additional weeks per year. Data is from analysis of over 20,000 employees across 102 companies.

How Are Today’s Managers Using AI?

I decided to go straight to the source. And, like everyone else, managers are seeing similar gains within routine and repetitive tasks with AI. Kelsey Bailey, Senior Digital Marketing Manager at Marketri, says she uses the tech for summarizing meetings and drafting emails, for example.

Bryan Wall, Senior Competency Leader of Cloud Engineering at Experis, described using AI in a similar way. Mostly, he uses it to “get through some of the more time-consuming administrative work that can otherwise take me way from my team.”

It’s not just managers though. We’ve seen as AI has matured in the past year, it’s now being trusted more by workers. Many employees are now asking agents questions over their managers, suggesting AI has become somewhat of a non-judgemental and reliable information source, or even a colleague.

Along this vein, some managers told me they use AI to “pressure-test” certain situations. Bailey, for example, said she uses AI when she’s approaching a sensitive client conversation. Wall, too, says he uses it to test out ideas.

Philip Huthwaite, CEO at 5app, says AI helps him challenge his own assumptions and encourage new ways of thinking.

“Asking tools like ChatGPT or Claude to find faults in your current assumptions or ideas will help you achieve better outcomes and tighten up your plans, which makes them very powerful sidekicks.” – Philip Huthwaite, CEO at 5app

This shift from AI simply speeding up repetitive tasks to becoming a managerial confidante has been a productive one for managers. Bailey and Huthwaite both named productivity gains as a benefit of AI use. Likewise, Wall and Steve Fenton, Director of Developer Relations at Octopus Deploy, said the technology has freed them up for higher value work.

Ultimately, higher value work, when you consider managers, involves connecting and communicating effectively with the people that work for you. This task of human connection is one that needs preserving, not replacing, as AI develops.

Forget Managers, Who Else is Benefiting from AI?

AI prompted clear use cases and benefits from the managers I interviewed. However, findings were mixed on whether these gains were specifically related to their managerial status.

On the one hand, Wall said the result of the Prodoscore study “makes sense.” He added, “managers are in the intersection of gathering information and decision-making, so they can use AI across a broader range of tasks.”

And indeed, as AI becomes a higher value tool in decision-making, managers might even be able to use AI more than employees. Prodoscore’s own software, for example, helps managers complete 360 reviews, Naficy told me. While it varies across roles, the average manager likely makes more decisions than the average employee.

On the other hand, Bailey and Huthwaite didn’t necessarily agree with the survey’s results. “I think the people who benefit most put in the work to figure out how AI fits their specific role, regardless of title,” Bailey explains.

Huthwaite instead turned my attention to junior employees. Entry-level roles are tough to navigate in today’s climate, so it’s understandable that younger workers, who have more experience with technology in their day-to-day, “are pioneering new and innovate uses of AI,” as Huthwaite says.

Furthermore, both Fenton and Wall mentioned having specific AI champions within their companies, that are spreading their expertise and experimentation. Fenton’s champion discovers new ways of using AI, and then passes this on to the rest of the team, who in turn apply a “taste test,” as he describes it.

Similarly, Wall encourages teams to share what they’ve learnt from using AI, with each other. “When someone finds an AI application that saves significant time or improves the quality of their work, that can become a lesson for the broader team rather than an individual productivity hack,” he explains.

How Managers Can Extend Productivity Gains

Huthwaite believes anyone can benefit from AI in the workplace, “as long as you’re using it for a real purpose rather than using AI for the sake of it.” Research supports his claim, too, as employees tend to do better with AI when there is a clear plan in place from management.

Kriszta Grenyo, COO at Suff Digital, points out something similar. She found employees “usually aren’t hiding AI because of ill intention, it’s because they aren’t sure what’s acceptable when there weren’t clear guidelines in place on when and how to use it.”

First and foremost, therefore, managers should prioritize transparency. Provide a clear and accurate AI policy that outlines how the technology should be used, which is regularly revised and revisited as AI develops. Having a policy doesn’t just provide guidance for employees, but it also minimizes the security risks that come with using AI.

Likewise, Wall sees the role as the manager in today’s age as one of a cheerleader. “My job as a manager is to make sure AI helps the team work smarter without losing the human elements that make a team effective,” he says.

“I want my teams to feel empowered to experiment with AI and identify where it can genuinely improve their work. Of course, I also want them to identify where human judgement, accountability, and oversight are essential.” – Bryan Wall, Senior Competency Leader of Cloud Engineering at Experis

The second key step for managers is ensuring they’re encouraging employees to experiment, to give them the space to try new things with AI. In reality, every team works differently, and has different bottlenecks. Allowing teams to work within themselves to design AI for their specific use cases is the best way to ensure productivity genuinely goes up.

Wall says he doesn’t see AI making middle managers obsolete. He does say, however, “the strongest middle managers in the AI era will be the ones who can translate the intersection between technology and the workforce. These candidates must understand where AI can improve productivity and how to help their teams adapt as workflows continue to evolve.”

Even if it isn’t replaced, the role of the manager seems set to change. What will set managers apart in the future might genuinely be an ability to change – to reap the benefits AI provides for repetitive tasks and ideation, and use the time gained to connect and empower employees.

Of the employees that received an AI policy during onboarding, over 1 in 10 reported retaining little to none of the information it provided, according to a new study.

Information retained at onboarding varies across hybrid, fully on-site, and fully remote employees. Hybrid employees reported the lowest amount of retention overall.

While AI has the potential to accelerate growth for businesses, companies are putting themselves at an increased security risk when they forgo a clear and accurate AI policy at onboarding. Similarly, employees repeatedly not retaining the policy adds to this risk.

Over 1 in 10 Employees Retain Little to None of Their Company’s AI Policy

In a new study from Adobe Acrobat, almost 40% of employees revealed they hadn’t received any AI policy information at onboarding. Of those that did receive a policy, over 1 in 10 said they’d retained little to none of it. 

Onboarding can be a stressful and overwhelming time for new starters. However, employees not retaining the AI policies they’re given, or not being given them at all, poses a double threat to businesses when it comes to security and data protection.

As well as AI policies, IT information and legal & compliance guidelines ranked highest among the most-forgotten onboarding items.

Onboarding Varies Across Hybrid and Remote Employees

Exclusive data reveals some divide between hybrid, fully on-site, and fully remote employees when it comes to information retention at onboarding. 47% of hybrid employees say they retain more than half of their onboarding information, compared to 59% of fully remote and fully on-site employees.

Similarly, a higher percentage of remote employees (38%) were unable to find onboarding documents after week one of their new role, compared to hybrid (36%) and fully on-site (28%) employees.

For hybrid and fully on-site employees, it’s much easier to ask a manager or colleague for this information in-person, if it can’t be found independently. Remote employees are at a disadvantage in this sense.

This lack of understanding not only impacts confidence and clarity when moving into a new role. For businesses adopting AI, the consequences can be significant if an employee doesn’t properly understand how they are expected to use the technology.

While the study doesn’t indicate whether employees received an AI policy after onboarding, presenting this information early is key. It ensures new employees are exposed to the company’s culture and best practices when it comes to AI use.

The Impact of a Lack of AI Policy Knowledge

Businesses are reporting higher productivity, and higher levels of employee confidence, as they implement AI. To reap the full benefits of the technology today, means to understand the security risks AI poses, and to ensure these risks are fully mitigated across operations.

A significant number of business leaders report AI mistakes have impacted their business. Moreover, as data breaches become more common and powerful (thanks in part to AI use by cyber criminals), companies need to be protecting data that becomes vulnerable when a new technology like AI is adopted.

AI use within your organization should be outlined with a clear and accurate AI policy. This gives employees guidance on how they should be using AI in their day-to-day, including sanctioned tools and the handling of sensitive information. It also creates a strong understanding of potential risks and promotes a positive AI security culture.

The above study recognizes the vast amount of information new employees reckon with during onboarding. On average, employees receive 13 individual documents, and spend an average of 12 hours reviewing onboarding materials in their first week. The top onboarding improvement recommended by employees was a single, searchable hub for all documents and materials.

Overall, businesses may want to consider pacing their onboarding process. Similarly, continually revisit important topics such as AI use regularly. Information should also be readily available for employees to review at any time, without friction.