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.

The last thing your business needs is a cyber attack. The cost alone can ruin even the most successful companies, and if that doesn’t do it, the reputational damage will.

The good news is that, even with a little bit of training, you can shore up your cybersecurity to keep your business as safe as possible from cyber threats. More importantly, that cybersecurity training doesn’t have to cost you as much as a security breach.

Below, I’ve outlined some of the best free cybersecurity courses available online this month, so you can learn exactly how to stop these attacks before it’s too late.

Foundations of Cybersecurity with Google

Summary:

• Learn how to identify how security attacks impact business operations, use common tools of the industry, and understand security ethics.
• 4 modules, 1 week to complete at 10 hours per week
• Beginner level course
• 12 language available
• Shareable certificate available on completion
• Available through Coursera

If you’re looking for a good jumping off point from one of the world’s most reputable tech companies, this is the cybersecurity training course you’re looking for.

Foundations of Cybersecurity with Google covers all the basics, including the most common threats to expect, what kind of tools you’ll use to protect your business, and what kind of negative impacts businesses see as a result of security breaches and cyber attacks.

The four-module course isn’t too long either, at only 10 hours, and it’s available in 12 different languages, so you have options if you aren’t a native English speaker.

Cyber Security Awareness Training Course For Beginners

Summary:

• Learn the basics of cybersecurity, including common threats and tools, safe internet practices, incident reporting, and AI in security.
• 10 modules, 30 minutes total
• Beginner level
• Available through Udemy

Cyber Security Awareness Training Course For Beginners is an extremely accessible way to get introduced to cybersecurity.

In just half an hour, you’ll grasp everything you need to know to get started, including online safety practices, cybersecurity tools, and the most common threats.

This course isn’t taught by a big corporation, but rather, it’s taught by Dathathreyalu TP, the Head of Cybersecurity Operations at JOYNEXT, who has extensive IT experience and has taught over 20,000 students through Udemy.

AI for Cybersecurity Specialization with Johns Hopkins University

Summary:

• Learn to use AI in a way that betters you
• 3 modules, 12 weeks at 5 hours per week
• Learn how to use advanced AI techniques to detect and prevent cybersecurity threats, ensuring robust protection against evolving digital risks.
• Intermediate level
• Available through Coursera

I’m not talking about beginners courses anymore, with the AI for Cybersecurity Specialization with Johns Hopkins University representing more of an intermediate option for those already familiar with the basics of cybersecurity.

More specifically, this course takes on AI in cybersecurity, helping learners to develop skills that use the modern technology to recognize and fend off cyber attacks that are likely using AI as well.

It is an intermediate class, which means it’s quite a bit longer than the beginner options at 60 total hours (12 weeks at five hours per week). Still, if you want to take cybersecurity seriously, you’ll need AI to get it done.

Microsoft Cybersecurity Architect

Summary:

• Learn to evaluate cybersecurity strategies and to design solutions using zero trust principles and specify security requirements for cloud infrastructure.
• 4 modules, 4 days at 8 hours per day
• Advanced, expert-level course
• Shareable certificate available on completion
• Available through Microsoft

To be clear, when they say this is an advanced-level course, they mean it. Microsoft Cybersecurity Architect is reserved for “experienced cloud security engineers who have taken a previous certification in the security, compliance and identity portfolio,” from Microsoft, so don’t start here.

If you are interested and advanced enough, though, this course can help teach you how to design security systems that fit with your particular business needs, focusing on compliance, infrastructure, and data.

Despite the advanced nature of the class, it is completely free if you are willing to partake in self-directed learning. If you’d like someone to actually train you, you’ll have to pay around $3,000 for the additional help.

The Importance of Cybersecurity Training

With all the advancements over the last few years, you may not think that your business needs to establish training procedures when it comes to cybersecurity.

Unfortunately, the reality is that 88% of cyber attacks and security breaches stem from some kind of human error. That means that training can have a huge impact on your ability to protect your business.

Suffice to say, the training courses listed above — and the thousands of others available online for specific industries and niches — could be the difference between an unbothered and successful companies and one that’s trying to pay off ransomware hackers.

Despite the countdown to paid time off on your calendar, August isn’t the time to start slacking on your AI knowledge, especially as AI companies continue to develop their tools at speed.

Not only should users be expanding their knowledge of AI, but they should also see how AI can enhance existing workplace skills, such as leadership and project management.

Recent studies have suggested leaders need more training to leverage AI’s full capabilities. Free courses like the ones below are a sure way to keep knowledge fresh and relevant, so you can make the most out of your AI investments.

Managing AI Projects with Microsoft

Summary:

• Learn how to manage and coordinate projects with the Microsoft Azure AI ecosystem
• 4 courses, taking approximately 12 weeks to complete (4 hours per week)
• Intermediate level recommended
• Shareable certificate available on completion
• Available through Coursera

Microsoft’s Copilot has become a business favorite because of its connection to the wider Microsoft ecosystem, especially as more businesses opt for AI solutions that integrate into daily workflows. With this course, you’ll learn practical use cases for the entire Microsoft Azure AI ecosystem, allowing Microsoft users to fully leverage AI within their existing tools.

Furthermore, at the end of this course you’ll be able to manage cross-functional AI initiatives using structured planning and risk coordination, and coordinate AI system delivery across data, model, deployment, and monitoring stages. Plus, it will show you how to apply responsible AI, governance, and business value frameworks within projects.

This course is targeted at leaders, and the description boasts skills such as cross-functional team leadership, business and organizational leadership, decision intelligence, and more. Some studies have suggested the managerial role is set to change as a result of AI, therefore learning to lead with AI will set you up for a future supporting yourself and your team.

Leadership knowledge is a prerequisite here, including experience leading projects or cross-functional initiatives. You won’t need to know how to code, as the program focuses more on managing AI initiatives, rather than building.

Build Anything With AI with Vanderbilt University

Summary:

• Turn any idea into working software using AI
• 4 courses, taking approximately 4 weeks to complete (10 hours a week)
• Beginner level
• Shareable certificate available on completion
• Available through Coursera

A big part of mastering AI is learning how to apply it in the right way. We’ve all been there, trying to use AI for AI’s sake, and it doesn’t work nearly as well as when you enhance or reimagine your existing processes with AI in mind.

This course teaches you to do exactly that. Taught by top instructor Dr. Jules White, Director of Vanderbilt’s Initiative on the Future of Learning & Generative AI, by the end you’ll be be able to compute, analyze, and visualize anything with AI, including new projects and ideas.

Similarly, users will gain new skills including AI product strategy, decision intelligence, prompt patterns, large language modeling, and AI and agentic workflows. You’ll also get to work with highly popular tools such as Anthropic’s Claude and OpenAI’s ChatGPT, keeping you firmly in the loop on the tools making the biggest impact.

Google AI Professional Certificate

Summary:

• Upgrade AI from a task completion engine to a professional collaborator
• 7 courses taking approximately 8 hours to complete
• Beginner level
• Employer-recognized Google certificate available on completion
• Available through Google

Those wanting to use AI to its full capabilities should be going beyond asking questions to a chatbot. According to the description of this course from Google, it was built “by mapping AI capabilities to the skills the job market demands, and validated by employers.”

This course will help you use AI in the ways that are making an impact in the workplace, in particular, across communication, data analysis, and research. It’s highly customizable and meets users where they are, encouraging them to complete practical, hands-on time using AI to complete tasks that trouble them the most at work. If this means skipping a course section or two, so be it.

Users will gain skills including project management, content creation, data visualization, and responsible AI use. You’ll also get to learn how to vibe code, allowing you to create custom apps that solve your workplace challenges.

How Smart People Use AI to Think, Lead, and Grow with ChatGPT

Summary:

• Learn to use AI in a way that betters you
• 7 sections with 7 lectures
• 33 mins of on-demand video and 1 article
• Beginner level
• Available through Udemy

This course encourages users to look beyond the surface with AI, and consider it a partner to improve your thinking, rather than replace it. “Whether you’re managing a team, making decisions, or trying to develop new habits, you’ll discover how a simple daily conversation with AI can help you gain clarity, solve challenges, and grow faster,” the course description says.

In the wake of today’s AI layoffs, this course is a breath of fresh air for professionals, creators, entrepreneurs, and learners. Mostly, you’ll learn to use ChatGPT as a thinking partner for daily tasks, allowing you to create a personal AI habit that encourages growth, reflection, clarity, and confidence. You’ll also get access to real-world examples and prompts you can use right away.

Overall, the course emphasizes AI use “in a meaningful, human-centered way, beyond just writing blog posts or summaries,” making it a vital learning opportunity for leaders wanting to adopt AI in a way that uplifts and empowers employees.

Why You Should Keep Up with AI Courses

Several studies indicate businesses are already seeing massive productivity and ROI gains with AI, suggesting it’s already making an impact on today’s workplaces.

However, there are still risks that businesses need to be aware of, especially as the technology continues to advance and integrate itself as a rapid speed. Not paying attention at this stage will not only cost you your AI investments, but your business’s profit and reputation.

That’s why leaders should stay aware of how AI is developing and continue their learning no matter what stage they’re at. Things can change quickly, and the tool you learned about last week could be out of date a week later.

Microsoft has issued a warning to users that they must update the Teams mobile app soon, or risk losing calendar access.

Users still have a few months before they need to carry out the update, with Microsoft stating that it must be done by October of this year.

The recommendation from Microsoft does not affect desktop users. Read on to find out how to ensure you have the latest version, and how to update the mobile app.

Countdown to Updating Microsoft Teams App

Microsoft has issued a statement recommending that Microsoft Teams users update their mobile apps before October. Those that don’t will lose access to the calendar function of the app, an integral feature of the tool.

The recommendation is applicable to users on iOS and Android, though doesn’t affect desktop users.

The app versions that users need to update to are:

• iOS: 8.9.0 (build 8.9.77.2026092302) or higher
• Android: 1416/1.0.0.2026122504 or higher

Want to know how to record a Teams call? Read our step-by-step guide

How to Update the Microsoft Teams Mobile App

In order to update the Microsoft Teams app, you’ll need to head to your device’s app store, whether that’s the Apple App store or the Google Play store.

• Click on the Profile Icon in the top right corner
• Locate the Upcoming Automatic Updates or Available Updates section
• Scroll to the Microsoft Teams entry
• Click Update

There will also be the option to enable automatic updates, which you may wish to do to remove any concerns like this in the future.

If you are using a company device that is locked down and you’re unable to select this option, you should speak to your tech department about the update.

Regular Updates to Microsoft Teams

If you’re on the fence about enabling automatic updates, or manually regularly updating to the most recent version, it’s worth looking at how frequently Microsoft adds to the Teams platform.

In the past couple of months, Microsoft has added new features to the iOS and Android apps, including files preview functionality, meeting impersonation alerts, and Proximity Join for Teams Rooms, to name a few.

You can see a run down of all the latest features added to Microsoft Teams on the updated official blog.

In recent weeks, we’ve had two of the biggest AI companies in the world, OpenAI and Anthropic, reveal their models were involved in security incidents within testing environments.

A combination of OpenAI’s GPT-5.6 Sol and a pre-release model breached Hugging Face a few weeks ago. Heeding a warning from its competitor, Anthropic conducted its own investigation. It revealed on Thursday its models Claude Opus 5.7, Mythos 5, and an unreleased internal research test model had breached three companies in its own security tests.

Both breaches contribute to a wider conversation about the safety of autonomous systems, especially when they sometimes act in ways their own companies can’t predict.

Both OpenAI and Anthropic Report Security Incidents

On Thursday, Anthropic revealed several of its Claude AI models had breached the systems of three organizations during cybersecurity tests. The incidents were discovered following an internal investigation by Anthropic.

The disclosure comes more than a week after OpenAI admitted its models had been responsible for a breach of Hugging Face, an online community platform where users share and test AI models, datasets, and web apps.

While a certain amount of press on a model’s power is good for AI companies, the incidents are certainly a cause for concern, particularly as more users and businesses adopt autonomous systems.

Systems are Acting Autonomously and Breaching Test Environments

The OpenAI breach of Hugging Face unfolded like a horror movie. Hugging Face revealed it had been hacked in mid-July, and nearly a week later OpenAI stepped out of the shadows, and said its own systems had been responsible after breaking out of a testing environment. The combination of models had escaped by exploiting a previously unknown zero-day vulnerability in Hugging Face’s systems.

In a blog post, Hugging Face detailed the incident: “Over roughly two and a half days inside our infrastructure, an autonomous AI agent driven by a combination of OpenAI models ran an end-to-end intrusion against our platform: it was thousands of small, automated decisions, executed at machine speed across short-lived sandbox environments, with command-and-control staged on ordinary public web services.”

Following the incident, Anthropic said it conducted its own internal assessment on its own AI, Claude. “In particular, we looked for evidence that Claude – like the OpenAI models that accessed Hugging Face – was able to access the internet from within testing environments that should have been sealed off,” it wrote.

There, the company discovered several Claude models had breached three companies during security tests. The models accessed the internet from within or while interacting with third party, Irregular, a security partner of Anthropic. From there, the models gained unauthorized access to the production infrastructure of several companies.

Despite drawing on the OpenAI/Hugging Face incident when reporting on Claude, Anthropic clearly defined the differences between the incidents. While OpenAI’s models had exploited an unknown software vulnerability to break out of its test environment, Anthropic’s models had reached the internet through a connection left open by mistake.

Likewise, Anthropic noted it had discovered the incidents itself through review, whereas OpenAI had admitted to the breach following Hugging Face’s security announcement.

AI Systems Remain a Security Risk

In a recent interview with The Economist, Elon Musk, CEO of SpaceX and force behind the Grok AI models, said AI would make the world so great that money would no longer matter. Anthropic CEO Dario Amodei and OpenAI CEO Sam Altman have made similar claims about the prosperous utopia AI will usher in.

While we’ve certainly seen a shift from these leaders on the impact of AI, security incidents like these make it difficult to imagine this fairytale. These incidents should be taken incredibly seriously, especially because they involved systems breaking free of their testing environments. 

We can take some comfort in the fact that Anthropic disclosed there was no evidence of any model “pursuing a goal of its own,” and in its case, the model was trying to complete the task it was asked to do within the testing environment. How they decided to get there is where the trouble began.

Speaking about the OpenAI hack into Hugging Face, Anup Kumar, CEO of Optiv Consulting (formerly part of Optiv Security), said: “News of autonomous agents exploiting a zero-day inside a sandboxed test environment to reach production systems should be a wake-up call for every enterprise deploying agentic AI.

“This wasn’t a model being tricked by a clever prompt. It was a frontier model independently identifying a zero-day, chaining privilege escalation across separate organizations’ infrastructure, and reaching production systems, all in pursuit of a narrow evaluation goal it was never explicitly told to pursue that way. That is a materially different risk category than the one most security programs are built for.”

Businesses should take extra caution and assign clear limitations and guardrails onto their autonomous systems. And, the incidents should be taken as a sign that AI still poses genuine security risks when it acts in an autonomous fashion.

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

It seems like everyone is adding AI to their workflows now, and with good reason. AI can help speed up productivity and produce more accurate results within workflows, leading to better business outcomes. But you shouldn’t just be blindly adding AI to every workflow.

It’s better to audit your existing processes and see where AI can make a true difference. Or, kindly steal the workflows of other AI users if you’re unsure of where it can fit in. Here’s where our monthly list can help.

This month’s workflows are:

• Generate Content Ideas AI Workflow
• Track New Model Releases AI Workflow
• Daily Organization AI Workflow
• Employee Soft Skills AI Workflow

Generate Content Ideas AI Workflow

Recommended by Jase Rodley, founder of Dialed Labs

Jase uses this workflow to create landing pages, FAQ sections, and other content that directly addresses customer pain points. Data is pulled from customer queries, which is then analyzed by AI to highlight patterns. These can then be used to create the content.

“We cover things that people are actually looking for and this has helped close the gap between what businesses want to talk about versus what customers want to actually know,” Jase says.

Jase estimates the workflow has saved him at least 50% of the time usually needed to carry out each step manually.

Track New Model Releases AI Workflow

Recommended by Adam Dalloul, CEO and founder of EmpirioLabs AI

This workflow helps businesses stay ahead of new AI model releases and start to use them. Even if you don’t want to use the models, it’s still handy to know exactly what’s out there, and evaluate how the model would stack up against your existing systems.

Adam uses this workflow at EmpirioLabs AI to give customers fast access to new models and found it has increased user retention.

Daily Organization AI Workflow

Recommended by Linda Yao, Vice President and General Manager at Lenovo

Linda shared this workflow at the end of our interview for The AI Strat newsletter. It’s a personal one she uses when navigating busy working weeks or events, to maintain organization and provide summaries for herself once the dust has settled.

“It keeps me up to date, it keeps me organized,” she says, but she can take handwritten notes the way she wants to, as this helps her remember things more. Finally, a way to tell colleagues my own handwriting habit isn’t just “vintage,” but also productive.

The workflow is a great example of how AI can help leaders retain the core of their existing rituals, but speed up and simplify overall output.

Employee Soft Skills AI Workflow

Recommended by Philip Huthwaite, CEO at 5app

Philip uses this workflow at 5app to improve employee soft skills training, by allowing them to receive instant meeting feedback.

Using this workflow, Philip has seen improvements in communication, active listening, and coaching skills. Employees and managers also no longer need to complete time-consuming self-assessments or manager observations.

Why Use AI Workflows

AI can strengthen workflows by handling routine, time-consuming tasks end-to-end, speeding up efficiency and leaving room for more complex pursuits, best done by humans. Similarly, you can reduce errors and easily scale certain 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.

In 2026, technology is advancing rapidly, and the cybersecurity landscape is shifting in response. In some sense, we are safer than we once were. And in another, threats are beginning to take on new shapes.

This doesn’t only mean AI, either. A wealth of new state-level regulations at the beginning of the year has created a more complex environment to navigate. And, despite newer threats emerging, experts are still quick to point out the danger of ransomware attacks.

I spoke to cyber experts Adam Darrah, Vice President of Intelligence at ZeroFox, and Michelle Faylo, US Cyber and Technology Leader at Lockton Companies, to get their perspectives on the current state of cybersecurity at this point in 2026.

A Changing Regulatory Environment for 2026

January 2026 saw the introduction of several state-level cybersecurity regulations. Fresh into the new year on January 1st, Indiana, Kentucky, and Rhode Island became the newest states with comprehensive privacy laws.

Likewise, California tightened data breach reporting deadlines on the same day and introduced new requirements for automated decision-making technology, risk assessments, and cybersecurity audits. The world also awaits the EU AI act, which comes into full effect in early August.

New regulations are a positive response to the changing threat landscape, but it also means businesses should be aware of any compliance changes and adjust their processes accordingly.

“Practically, this is pushing businesses to formalize AI governance policies, conduct documented risk assessments, and tighten breach notification procedures, and it’s increasingly a factor in cyber insurance applications, since carriers want to see that clients have a handle on this patchwork rather than treating compliance as an afterthought,” says Michelle Faylo, US Cyber and Technology Leader at Lockton Companies.

AI is Making Attacks Faster, But is Also Keeping Businesses Safer

AI within cybersecurity is a “two-sided story,” Faylo says. As a defensive tool to protect businesses, AI has shown promise. “Security teams are deploying AI for faster anomaly detection, automated response, and predictive threat modeling.”

However, this has meant AI governance “is becoming a security issue in its own right,” Faylo continues. “Organizations need to treat their own AI systems and AI agents as a new class of digital identity within its own attack surface… From an insurance standpoint, carriers are starting to ask how organizations are securing and governing their own AI tools, not just how they’re defending against AI enabled attacks.”

On the other hand, AI has significantly increased the scalability and speed that criminals can mount an attack. Attacks have become “more intelligent and adaptive rather than opportunistic,” Faylo says. Ultimately, AI is helping both businesses and criminals alike.

Adam Darrah, Vice President of Intelligence at ZeroFox, explains a similar development as AI has become more of an offensive tool within cyberattacks. “AI is changing how cyber operations are built and delivered, increasing the speed and sophistication of attacks,” he says.

In particular, “threat actors can automate the discovery, weaponization, and delivery process at a scale we haven’t seen before. Accessible GenAI tools are also lowering the barrier to entry for attacks, making it easier to generate targeted phishing lures and convincing synthetic media for impersonation and social engineering.

“AI is making established threat actor techniques faster, more adaptive, and more scalable,” Darrah says.

How Businesses Can Navigate 2026, and Beyond

Navigating today’s landscape can be disorienting, and Darrah acknowledges this. “We are living in strange times where reports of nation-state meddling, ever changing privacy laws, advances in technology such as AI, data extortions, and data breaches are constant.”

His advice for small businesses is to prioritize strategically. Not everything is equally important, and he recalls the earlier advice of a colleague when he says, “if everything is a priority, nothing is a priority.” Somewhat cliche, he adds, but it resonated with him.

In practice, Darrah’s advice is to follow the basics, particularly if you’re tight for security budget. “We live in a world that values new and novel, but cyber criminals exploit the basics of network security hygiene and social engineering awareness.”

Faylo, on the other hand, recommends similar. “For budget-constrained clients, we generally advise them to fix the ‘insurability gaps’ first.’ These are multi-factor authentication, endpoint detection and response, and ensuring you have restorable and tested system backups.

“The common thread is that these are governance and process failures, not just technology gaps, which is why we push clients toward treating cyber resilience as a leadership level priority, not something delegated entirely to IT.”

It’s no surprise that the more of your company exposed to best cybersecurity practice, the stronger your company will be.

This article is part of interviews with Linda Yao, Vice President and General Manager of Hybrid Cloud & AI Solutions at Lenovo, and Michael Benisch, Vice President of AI at Motive. These interviews were 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.

Undoubtedly, AI has developed fast. But, so far, progress has been mostly confined to a laptop or smartphone screen. Chatbots and agents are more powerful than before, workflows can be fused with AI for stronger efficiency, and so on.

On the physical side, progress has been slower, which isn’t unusual for an industry that usually takes a longer time to integrate new technologies.

Despite this slower pace, physical AI is still changing the way businesses are operating. AI within warehouses and transportation has developed substantially, increasing productivity across the board. But experts say physical AI has benefits beyond productivity, potentially making whole industries and professions safer for human operators.

I spoke to Linda Yao, Vice President and General Manager for Hybrid Cloud and AI Solutions at Lenovo, and Michael Benisch, Vice President of AI at Motive, to see where industries are at now with physical AI and what we can expect for the future.

Physical AI Has Been Slower to Develop

In a 2025 keynote, NVIDIA CEO Jensen Huang claimed: “The next frontier of AI is physical AI.” When I first start talking with Michael Benisch, VP of AI at fleet management solutions provider Motive, he uses similar language to talk about physical AI, calling it “one of the last frontiers,” that needs to be unlocked in the AI world.

Benisch has been working on physical AI for almost a decade. His resume includes the self-driving division at Lyft, as well as stints at Toyota and General Motors.

“When people think about AI, it’s usually the chatbots we talk to on the web or if you use Claude Code or something like that,” he says. “But then there’s the other half of the world out there, where you need to get your packages from Amazon, and you need to get your real food.”

When I asked him why progress was generally slower, he said there are a lot more obstacles you can’t overcome, when you’re dealing with the physical world. Unlike computer programs, issues can’t be fixed by “simply hacking through it in a weekend.”

How Organizations Have Been Adopting Physical AI

Plenty of companies are already seeing massive gains with physical AI. Linda Yao, VP and General Manager of Hybrid Cloud & AI Solutions at Lenovo, helps organizations adapt to emerging technologies. At one point, this was hybrid cloud, and now it’s AI.

One company, ST Logistics, wanted to, in Yao’s words, “automate as much of their warehouse as possible.” The formula for this case was physical plus digital AI, Yao explains. On the physical side, this includes robots, and they sound like the kind of robots you’d expect in a typical sci-fi movie.

One robot helps “efficiently move the equipment or move the inventory from one side of the dock into the receiving inventory warehouse,” and another does “the physical loading and unloading.” Then, there is another robot that is more “detailed,” it identifies the right boxes and stacks them in the right order.

For the digital side, Yao explains: “We are working to make sure that the systems being used, the IT systems being used to log the inventory, to track the data, to take the orders, to make sure that the orders are shipped on time. That’s all then connected back into not just the human workflow, but also the robot workflow and the AI workflow.”

Overall, Yao says ST Logistics reduced order processing time by 40%, reduced energy consumption by 30%, and increased productivity by 30%. “It really is bringing together the physical as well as the digital, as well as the human element to make this AI solution work.”

Physical AI Can Make Physical Professions Safer

Yao describes the kind of work going on in warehouses as “backbreaking,” particularly for workers that are loading and unloading, or spending an hour in cargo containers that can get to 120 degrees Fahrenheit in the summer. A lot of the time, she says, companies are struggling to find people who even want to do that work.

This obviously makes the logistics industry a prime candidate for AI. Especially since trucking is considered one of the most dangerous careers out there: according to the US Bureau of Labor Statistics, almost 800 truck drivers lost their lives in a work-related incident in 2024.

Motive’s suite of AI-powered products offer increased safety for drivers out on the road, Benisch tells me. One company, Agmark, adopted Motive’s AI dash cams, and as a result, saw a 67% reduction in accidents and a 15% reduction in unsafe driving behaviors. 

Similarly, chilled products distributor Damian’s Enterprises saw a 20% improvement in safety scores when they adopted Motive’s AI Dual-facing dash cams.

Improving safety, Benisch explains, is one of the ways fleet operators and managers can get their drivers behind them when AI is implemented. He encourages leaders to tell their team, “You have the ability now to do a better job than you did before. You can be safer. You’re more likely to come home at the end of the shift.”

What’s Next in the Physical AI Space?

At the end of our interview, I asked Benisch for his physical AI predictions in the next year. A question I sometimes feel cruel for asking, especially since one year’s progress can take place in a few days with AI.

“Physical AI isn’t moving as fast as the other AI areas… it’s not like the rocket ship growth that you see from ChatGPT or Claude Code,” he says. He does predict, however, “there will be market differences and things that are hugely improved.” Within the driving space, he predicts “the passenger space will be more and more automated, but taxis will still be there, and Lyft and Uber will still have human drivers.”

Like Benisch, other experts say the same about human contribution within the physical AI space.

“Between now and 2040, I certainly expect robotics and physical AI to create at least a trillion dollars in economic value, most of that in manufacturing and logistics. That will happen not through worker replacement and productivity but through our ability to innovate what products we make, how we make them, and what tasks humans perform versus which ones are automated, elevating the nature of work for humans to more problem-solving and to sort of a catcher role, rather than just relying on our physical dexterity.” — Ani Kelkar, in an article for McKinsey & Company

While we’ll certainly see the most gains from physical AI within logistics and manufacturing, this could lead to physical AI developments across other industries. Bloomberg reported earlier this month that OpenAI are planning to release their first hardware device, a screenless speaker with integrated AI capabilities.

The design of the product is still currently under development, but is being pitched internally as a “humanlike AI companion that lives in the home.” Though fascinating, I think most would prefer a robot that carried groceries from the store.

Adam Darrah, Vice President of Intelligence at ZeroFox, says most ransomware attacks are about building notoriety and embarassing organizations, rather than just for financial gain.

North American-based organizations were the most targeted by malicious actors in ZeroFox’s latest ransomware report, and industries including manufacturing and construction were hit the hardest.

Darrah says organizations should consolidate cybersecurity fundamentals to protect themselves, although admitted the firepower of nation-backed groups could be too difficult to stop in the long run.

Most Ransomware Attacks are About Embarassing Organizations Over Taking Their Money

ZeroFox’s Q2 2026 Ransomware Wrap-Up found five attack collectives were responsible for nearly half (49.5%) of all global ransomware and digital extortion (R&DE) attacks in Q2 of 2026.

Adam Darrah, Vice President of ZeroFox, spoke to Tech.co exclusively about how R&DE attacks are primarily about embarassing and panicking organizations, rather than financial gain, based on the findings of the report.

“What [the findings] suggests is that it’s less about financial incentive and more about appearing bigger, better, scarier. They want the civilized, law-abiding class to be scared and to be embarassed,” Darrah told us.

Manufacturing, Supply Chain, Technology Among Industries at Risk

The report identified a total of 1,885 separate R&DE incidents in Q2 of 2026, an increase in year-on-year incidents from Q2 2025 and Q2 2024, suggesting incidents around this quarter are on the rise. Notably, attacks on North American-based organizations made up nearly 45% of all incidents reported. According to Darrah, these numbers are the result of the geopolitical conflict between America and Iran.

Overall, the manufacturing industry experienced the highest number of R&DE incidents in this quarter, accounting for nearly 20% of all incidents. This too, Darrah says, is connected to the shutdown of the Strait of Hormuz, and a desire from ransomware groups gain notoriety.

“Ransomware groups, especially those aligned either as a fellow traveler or as a direct associate of a military security apparatus, they like doing a couple of things. They love notoriety, they love being obedient to their overlords, they love money,” Darrah explains. “But they also love sitting back and watching civilized, law-abiding people and organizations squirm and be uncomfortable and to watch that pain.”

Similarly, R&DE targeting patterns have shifted away from the retail sector, and have instead turned towards the technology industry. Darrah again notes this is another way of embarassing important organizations.

“There’s a lot of prestige with what’s happening in the world right now in terms of AI,” Darrah says. “I think there’s probably a bit of prestige in going after technology firms, the people associated with that, to embarass the company and the victims.”

While Darrah notes developments in AI have also made the threat landscape more unpredictable, he does say some ransomware groups are still using older technologies, and are yet to convert to AI. In this case, businesses should protect themselves from all kinds of threats.

What Should Businesses Be Worried About?

“I think businesses should be most worried about worrying too much,” Darrah says, suggesting businesses may be overcomplicating the issue. “I think we overthink the latest and greatest, and we take our eye off the fundamentals. And if you concentrate on the fundamentals, that is going to significantly decrease your risk.”

Darrah urges businesses to focus on strong password policies, a culture of reporting suspicious emails, and patching, among other best cybersecurity practices.

However, there are some vulnerabilities businesses can’t avoid. Businesses today are frequently outsourcing to clouds and third-party providers, and yes, they make our lives easier, but if they are breached, it becomes a problem. Darrah says this “affects people who are doing everything they’re supposed to do. They have all their policies… But if that third party gets hit, it’s like your brand is still dragged through the mud.”

“The interconnectivity of the world just makes it ultra likely that somebody is going to be touched by this plague,” he adds.

Moreover, sometimes organizations are targeted by much larger and more sophisticated groups than they can realistically handle. Particularly if they are backed by nations like Russia or China.

“I think we put a lot of pressure on people who love their job and who care very deeply, and we’re telling this person, defend against Russia, defend us against China,” Darrah says. In these cases, the outcomes can be much harder to prevent against, and understandably so.

Workers were more likely to turn to an AI agent for the answer to an obvious question than their own manager, in a new study.

While AI is changing hybrid, on-site, and remote workers differently, the study finds current company-wide training schemes may be insufficient, and workers are turning to other education tools.

Managerial roles and general workplace structures could change as workers turn more and more to AI, but the study shows we may not be at a place to trust AI completely yet.

Workers Would Rather Ask AI than Managers

In a new study from Adobe Business, 68% of workers reported turning to agentic AI for answers to easy questions, compared to only 4% that ask their manager. Overall, the study found workers were 17 times more likely to ask an AI agent questions they’d hesitate to ask leadership.

Similarly, more than half (54%) of respondents prefer using agentic AI to draft difficult or high-stakes messages, compared to the 23% that turn to managers or peers. Plus, 62% turn to AI for recapping an important meeting, versus 10% that turn to managers.

These findings suggest AI is becoming a trusted, judgement-free colleague for many workers. The study surveyed over 1,000 full-time employees who use AI weekly, with the goal of understanding how agentic AI has become part of every day tasks.

Agentic AI Training Is Lacking

According to the study, the next wave of AI, agents, are here, with 92% of AI users having adopted agentic AI at work. Workers, however, are using AI differently based on their work location. Hybrid and onsite workers mostly use the technology for idea generation and brainstorming, whereas remote workers use it for content creation and drafting.

Similarly, nearly three in four (73%) of workers say AI has improved their job performance, suggesting workers’ confidence as well as their efficiency has been positively impacted. 50% of workers also report freeing up time for higher-value work, and 38% say it has improved productivity.

However, the study finds a steady gap across all job levels when it comes to AI training. When asked the ways they have learned to use agentic AI, over half (54%) of workers said they had used trial and error, and 36% said YouTube. Meanwhile, only a quarter of respondents said they’d learned through collaboration.

That isn’t to say companies aren’t providing any training at all, it just may be the case that training programs aren’t providing all workers need or want to know. In fact, the study found one in three users had received formal agentic AI training, but fewer than half of those trained have gone on to build their own custom agent.

How AI Could Shift Workplace Structures

There’s a convincing argument to be made around AI shifting corporate structures. With access to more advanced tools, workers may be able to complete some tasks more quickly than their managers. Likewise, as AI skills become more and more desirable within roles, those with more knowledge may find it easier to make an impact, even if they have less experience.

Where we might also see significant change is for remote workers. Compared to on-site workers in the study, remote workers saw 17% higher productivity and a 35% greater reduction in imposter syndrome.

Traditionally, remote workers don’t always have access to managers or employees to check in with. AI could help provide this support, potentially improving employee wellbeing and lowering work stress.

However, despite these positive findings, it’s unlikely we’ll see AI replacing any structures yet. The study found 43% of workers prefer to check a risky idea with a colleague, compared to 39% who would turn to AI. This suggests trust and reassurance is still best received by a human colleague, and that AI may be too young in its current iteration for workers to fully trust its judgement.

AI is no longer just making cyber attacks cheaper and faster, but it’s now in charge of running whole operations, a new study has found.

Cybersecurity leaders have been warning about the dangers of AI for some time, and developments such as a maturing AI-enabled criminal tooling market and more sophisticated imitations of voice, face, live video, and documents pose serious concerns.

Experts are urging businesses to integrate cybersecurity practices within organizations, including cybersecurity leads and teams. Likewise, businesses should align their security protocols with the AI applications they are using to have a foundation to build from as threats continue to change.

Study Finds AI is Now Operating Attacks on Behalf of Users

In Check Point’s 2026 AI Security Report, AI has taken a leading role in cyber attacks. The technology is no longer just enhancing cyber attacks by making them cheaper, faster, and more accessible. Instead, it’s now doing the hands-on operational work itself.

In one example outlined, a human attacker carried out a breach by running two commercial tools, Claude Code and GPT-4.1, together. This led to the breach of 9 Mexican government agencies.

The report tracks how AI has reshaped the threat landscape over the past year, and is grounded in real-world incident and Check Point Research threat intelligence.

How AI Threats Have Evolved in the Past Year

Check Point found AI is now able to turn a new system vulnerability into a working exploit within hours, giving companies little time to react.

“[We] hear from the security operations center and incident respond teams [that] if a human was doing these tasks, we’d at least have some time to detect it, respond, and try to prevent it, but the agents are so fast, by the time [we] know about it the damage is already done.” Adam Ely, general manager of AI Security at Check Point Software, during a media roundtable at Check Point Engage Singapore 2026

Similarly, existing AI threat tools have matured in the past year. Phishing-as-service kits now have language models with jailbreak features built-in, and conversational AI voice-agents can run vishing and one-time passcode attacks.

Furthermore, the report notes that Virtual Identity measures can no longer be fully trusted. Thanks to AI, attackers can imitate voice, face, documents, and live video with ease, which makes communication scams more widely available across multiple platforms.

Protecting Your Business in 2026 and Beyond

Businesses are increasingly at risk as AI becomes more common in cyber attacks. The study found 1 in 17 AI prompts carry a serious data exposure risk, a particularly concerning statistic for organizations typically running 10 AI apps a month on average. Many of these AI apps, the study notes, also remain ungoverned.

Overall, high-risk prompts doubled to 4% in a year, one example of how AI is changing the cybersecurity landscape in a rapid fashion. “Enterprise data leakage through GenAI is a persistent and growing risk,” the report warns.

Not only are organizations going to have to ensure their core security principles are intact and solid, but they’ll have to continue to rework and update these principles, in order to keep up with new risks.

“Ensuring that companies are putting their protections for AI really in line with the AI applications or at the runtime level of the application is really important. As models change or functions change, that implementation can then be built on versus having to do a completely new security implementation.” Adam Ely

Adam Ely, general manager of AI Security at Check Point Software, believes organizations should also ensure cybersecurity teams and leaders are fully integrated into business operations. With these teams, businesses should have regular conversations about potential threats and how these are changing.

82% of business leaders say they are experiencing barriers preventing them from making the most out of AI, according to a new study.

The report finds that AI adoption has, however, been a positive investment for small businesses. Over half of owners said they had seen return on investment from AI, and almost half of owners saving at least 4 hours per week.

On the other hand, security and a lack of trust are the biggest barriers preventing owners from fully exploring AI. Many leaders aren’t yet confident letting AI handle low-level business tasks without human supervision.

Over 80% of SMB Owners are Experiencing Barriers with AI

In a new study from financial technology company Bluevine, leaders reported overall optimism on AI. 68% of SMB owners said they believe AI advances will help their business, up from 61% from the year above.

While sentiment is high, however, 82% of owners are encountering at least one barrier that is preventing them from exploring AI more deeply, and potentially using the technology for all it can offer. This suggests leaders aren’t yet reaping the full benefits, even after investing in and deploying the technology.

AI is moving fast, and the study suggests it may be moving faster than leaders can. Findings come from 942 small business owners and financial decision-makers across the US.

Over Half of SMBs are Seeing Return on Investments

Over half (52%) of business leaders reported seeing return on investment from AI, compared to only 24% that said they haven’t seen any gains yet. This could mean many businesses are still in the trial and error phase, testing out AI tools to see which ones benefit them the most.

On the other hand, other studies have suggested communication on whether AI has been beneficial can be fragmented across companies, leading to some uncertainty on whether AI has benefited a business or not.

Beyond ROI, business leaders are seeing gains across the board. Almost half (48%) of SMBs report getting back at least half a workday every week when using AI. 23% reported saving four to six hours per week, and 11% reported savings of seven to nine hours per week.

Distrust and Data Security Remain Big Concerns

Adoption is high – the study saw it rise 50% in just six months between September 2025 and March 2026. But, businesses are experiencing barriers beyond initial deployment. A significant 82% of leaders report at least one barrier to using AI deeply, arguably preventing them from taking full advantage of how the technology can help business operations.

33% of leaders cited data security concerns as their biggest barrier, up from 23% the year before. There remains among leaders a lack of understanding as to what these new tools are doing with their data, suggesting more training is needed to avoid costly data breaches.

Similarly, 31% of owners said a lack of trust in AI’s accuracy was another barrier. Only 22% of owners across the study said they were completely confident AI could do low-level business tasks without human supervision, with 78% not fully trusting AI in this sense, even when these tasks were those that would save them the most time.

Productivity, time savings, and ROI remain important metrics for businesses to focus on when using AI. However, this trust factor seems to be preventing businesses from reaping the most benefits.

Almost half of all LinkedIn long posts are generated by AI, a new study from Pangram finds.

While experts suggest AI can be used for researching and giving structure to ideas, it’s unable to create the authentic, personality-driven content that consumers want to see on their feeds.

Social media influencer JD Alewine spoke exclusively to Tech.co about the downsides of using AI to write content. Authenticity, he says, is something he strives for, and encourages brands to focus on their natural, human ability to tell stories in order to engage their audience.

Nearly Half of All LinkedIn Posts are Generated by AI, Study Finds

In a recent study, Pangram Labs found over 40% of long posts on LinkedIn were entirely AI-generated, contributing to the amount of AI slop now found on social media platforms.

LinkedIn was the “most AI-saturated platform,” of all the social media platforms analyzed, Pangram, the AI-detection platform, noted. Posts from LinkedIn made up 62% of content flagged as AI-generated, despite only accounting for a third of all content analyzed.

Of the LinkedIn long posts identified, 23.9% were entirely AI-generated, and 22.9% were written with the help of AI.

LinkedIn’s use of built-in AI writing tools (the “Write with AI” tool has since rebranded to “Enhance post”, but remains an AI writing tool) could have contributed to the increase in AI content on the platform.

Experts Say AI Can’t Provide an Authentic Experience

We’ve all heard the familiar tics of AI-generated writing. The “it’s not X, it’s Y” comparison, the continuous flow of em dashes, and the monotone thump of three sentence combinations: “Not this. Not that. But this.” Today’s brands need authenticity and personality on social media to earn engagement, and this structure doesn’t exactly support that.

I spoke to JD Alewine, co-owner of social media brand, Them Bites. Them Bites currently has over 200K followers across platforms including TikTok and Instagram. 

Alewine is firmly against the idea of using AI to post on LinkedIn. “We want to try to be as authentic as possible with the content we put out,” he said. “We know that at the moment AI is the current trend, but eventually people will grow tired of how it sounds, and reads. We are over the misuse of it as is.”

Them Bites’ content draws on the authentic and human experiences audiences crave, and these experiences are often missed when content is created by AI.

Alewine isn’t against using AI at all, though, describing it as “more of a tool to use as a jumping off point.” At Them Bites, they occasionally use AI to brainstorm, or to summarize a post they’ve already created. “We think of it as a tool to help the work that you’ve already put in.”

How AI is Changing Social Platforms

I asked Alewine about platforms other than LinkedIn where AI content is rife, and he gave Facebook as another example. However, LinkedIn was the main platform Alewine pointed to. “I have a hunch that it’s because people have gotten so used to flowery language,” on the platform, and as a result, “AI content was easily adapted to that type of user.”

LinkedIn by design is a “corporate communication platform,” says Grace Gosnear, Social Media Manager at LevLane. This makes it different than platforms like Instagram, Facebook and TikTok. People use it to connect in a business sense. Even before AI, content was grounded in polished, efficient corporate-speak. With AI, there’s a risk this is all content will become.

Similarly, there are longer term consequences for social media platforms becoming mostly AI-generated. Jenna Wuu, previously a Global Policy Programs Head at Meta, pointed out that this could impact how AI systems are trained in the future.

“If we enter a world where AI-generated posts become training data for future AI models, we’ll end up with a loop of AI models training themselves on themselves. That’s a risk for AI companies as well as users because it will reduce the overall quality of those systems.” Wuu points towards a future where models become entirely self-serving in the content they produce.

How Businesses Should Communicate with their Audiences in 2026

At the moment, AI can’t match the creativity and innovation humans have. Grace Gosnear used DoorDash’s recent collaboration with T-Pain for the World Cup as an example. “Could AI suggest working with a celebrity? Sure. But could it have landed on that exact execution with that timing and cultural awareness? I don’t think so.

“That’s the kind of work worth celebrating, not another three-paragraph LinkedIn post about how social media managers secretly have 20 different jobs. You can prompt AI to “make this sound more human,” “make it funnier,” or “remove the em dashes” all day long.

“People can still recognize when there’s a real person behind an idea, and the best content almost always reflects that.”

Therefore, businesses should focus on the powers of their own marketing and social media teams, rather than defaulting all creative work to AI. The technology can be useful, experts say, but for research or summarization, for example, and not the creative work.

However, studies have shown that audiences aren’t entirely against AI content, so long as it’s useful, personalized and relevant to them. Prioritizing this will help brands stay grounded in what will appeal to audiences.

At the end of our interview, I asked Alewine for his biggest tip for making content that lands with audiences: “Learn how to tell a story. Being able to tell a story is a form of communication that has been with humans throughout our entire existence. It resonates deeply within all of us.”

Zoom users have been issued with a warning after a critical vulnerability was discovered on the platform.

The issue, if not corrected, could see unauthenticated users take over affected Zoom accounts, compromising data and leaving legitimate users exposed.

In order to mitigate these risks, Zoom is urging users to ensure that they have applied the very latest update.

Zoom Security Vulnerability Discovered

According to a security bulletin issued by Zoom, the platform has been exposed to a potential flaw which could see users have their accounts compromised.

The warning, published on July 15th, informs users that they should update to the latest version of the platform to reduce risks stemming from the vulnerability. There is no evidence that this exploit has actually been targeted in a real world environment.

The flaw, CVE-2026-53412, has been given a Common Vulnerability Scoring System (CVSS) rating of 9.8, meaning it is very severe.

Which Version of Zoom is Affected by the Security Flaw?

The issue specifically affects users who are running the following versions of Zoom:

• Zoom Workplace for Windows before version 7.0.0
• Zoom Workplace VDI Client for Windows before version 7.0.10 and 6.6.15 and 6.5.18 in their respective branches

If you need to check what version of Zoom Workplace you’re currently running, click on your profile picture in the top right, then Help, then About Zoom Workplace.

To ensure your software is up to date, you’ll need to click on your profile picture, and then click Check for Updates.

Is It Safe to Keep Using Zoom?

While alarming, these sorts of critical security warnings are actually good news, as it means that the platform owners are proactive and actively tracking and discovering bug and flaws that may otherwise have gone unnoticed. Often these vulnerabilities are discovered before bad faith actors have a chance to exploit them. Good news for everyone (except the hackers).

While there have been reports of Zoom ‘hacks’ before, these are usually not direct hacks themselves, but rather criminals using social engineering methods to exploit victims, such as starting a Zoom call and then accessing their computer using remote software, unrelated to Zoom. Then there’s ‘Zoom bombing‘, which sees random people join meetings, but this is usually down to a lack of understanding of privacy settings on the users’ side.

Despite Zoom being a relatively secure platform, it’s always worth shopping around to ensure your web conferencing system is working for you. While Zoom crested the 2020 pandemic wave as the video platform of choice, others such as Microsoft Teams and Google Meet have proved more than capable rivals thanks to robust features and competitive pricing.

Despite being two of the biggest technology companies in the world, Meta and SpaceX have been outpaced by competitors so far in the AI race. However, with the release of new models, both companies are once again throwing their hats into the ring — and, they’re offering cheaper prices.

Recent data suggests these models don’t compare to frontrunners from Anthropic or OpenAI in terms of performance. But, with the amount of US businesses flocking to models like DeepSeek, it’s evident that businesses aren’t against sacrificing slight performance losses for cheaper costs.

Different AI models have different capabilities. When choosing an AI model to scale, businesses should consider which capabilities they need the most in order to supercharge their existing processes.

AI Price Competition Heats Up

Both Meta and SpaceX have announced new AI models in the past week. To mark the release of Grok 4.5 last Wednesday, founder and CEO of SpaceX Elon Musk described the model as offering “frontier intelligence at leading speeds and cost efficiency” on social platform X.

Meta, on the other hand, released Muse Spark 1.1 last Thursday, a model designed specifically for agentic tasks and coding. The model is one of the first from Meta Superintelligence Labs, headed by ex-Scale AI CEO Alexandr Wang.

Despite being relatively behind in the AI race, both Grok 4.5 and Muse Spark give SpaceX and Meta the opportunity to play catch up because of their low price offering.

With more businesses adopting AI, many will be keeping an eye on costs, making cheaper models all the more attractive. This, in turn, has the potential to shake up token prices across the industry and potentially lead to a drop.

How Do Meta and SpaceX’s New Models Compare?

Independent AI benchmarking platform Artificial Analysis rates new models Grok 4.5 and Muse Spark 1.1 lower than top competitors Claude Fable 5 and GPT-5.6 Sol. On its Intelligence Index, Grok 4.5 received a 54 score and Muse Spark recorded a 51. While this is slightly lower, it isn’t far off Fable 5 (60) and GPT-5.6 Sol (59), and is higher than models from Google and DeepSeek.

However, Grok 4.5 and Muse Spark are wildly ahead of Claude and GPT when it comes to pricing. Grok 4.5 has a lower weighted average cost per Intelligence Index task, at $0.31 per task, compared to Fable 5 ($2.75) and GPT-5.6 Sol ($1.04). Muse Spark is cheaper than all three, at only $0.26 per task.

Anthropic and OpenAI’s models are better performance-wise according to the Index. However, businesses will be increasingly concerned about pricing as they use more and more AI, and those slight gaps in performance might become negligible if it means they can take advantage of much lower token costs.

Given the popularity of models such as DeepSeek, which costs only $0.04 per task, it’s not out of the question that businesses will start to choose models based on how much they cost. US lawmakers, in fact, have reportedly been looking for ways to curb the use of Chinese models such as DeepSeek by US businesses, because many have looked to the tool as a cheaper alternative to the top players.

So, it may also be the case that businesses using DeepSeek will turn to cheaper models like Grok or Muse Spark if tighter regulation comes into play surrounding the use of Chinese models. If cheaper models start to become more popular as a result, this could have an impact on token pricing across the AI landscape.

How Businesses Should Choose the Right AI Model

Businesses around the world are already spending plenty on AI, as is evident from the tokenmaxxing trend. As more AI is deployed, cost will become a contributing factor to which models are preferred, although businesses should consider a range of factors before choosing.

According to Marina Wyss, Senior Applied Scientist at Twitch: “Businesses tend to default to the newest model from the biggest provider, and that’s rarely the right choice. Each model has a distinct profile of what they’re good at, costs, and what you can use it for. There are three main things to consider.

First, licensing: If you handle customer PII or need to fine-tune on proprietary data, you need to ensure the model you choose supports those use-cases securely.

Second, requirements like task complexity, context length, and how it will be deployed. Finally, make sure to test the finalists on your own data instead of relying solely on benchmarks. You can take 20 to 50 examples from your actual business, run them through two or three candidates, and score for accuracy, cost, and speed.

This will give you much more confidence that you’ve chosen the right model for your business and use case.”

Overall, the model that your business chooses is a significant first step. Ensuring you understand your own needs, and linking these to the tools you’ll need to make your existing processes better, is essential.

70% of small business owners admit to lacking the skills necessary to use AI effectively, according to a new study.

Businesses are, however, becoming more comfortable using AI, and are using the technology more than they did a year ago. 60% of respondents said they use AI every day.

Leaders specifically should focus on finding the correct AI training. Even if they are not using the technology as much as the departments below them, it will help them to respond and relate to teams more effectively.

Small Business Owners Need More AI Training

Thryv’s 2026 AI & Small Business Adoption 2026 report found 70% of small business owners in the US admit to needing more AI training, in order to use the technology more effectively.

“It’s clear that many SMBs are adopting AI faster than they can master it,” Grant Freeman, President of Thryv, stated. “Closing the gap between AI adoption and capability will be critical for Main Street success.”

The survey consisted of 561 small and medium-sized business owners and decision-makers, with most reporting annual revenue of between $1 million and $1.9 million.

AI Adoption Remains High

Despite some uncertainty on how to fully leverage AI’s power, businesses are still adopting the technology at a rapid rate. The study found 66% of US small businesses now use AI, compared to 55% the year before.

Likewise, one third of those surveyed are spending more on AI tools than they were a year ago, and many have already reported gains in both revenue and efficiency. Overall, 70% had increased their revenue, and 55% reported it had helped to reduce costs.

While 46% of SMBs said they would choose AI if it could perform a task equally as well as a human, the study finds AI has not yet directly impacted hiring. Only 13% of respondents said they had hired fewer people because of AI, and 45% expect AI to have no impact on hiring in the next few months.

Proper AI Training is Still Needed for Leaders

It seems AI training is being taken up by different sources. In the study, 31% of respondents turned to other AI tools like ChatGPT to tell them how to use AI. 57% said their primary source of training is YouTube and social media, while 49% cited online resources and webinars.

As adoption still remains high, the study suggests a gap between the rate at which the technology is being introduced, and how quickly it’s being mastered by employees.

“Most small businesses are comfortable using AI. But being comfortable isn’t the same as being effective and that gap is starting to show.” — Grant Freeman, President of Thryv

The main takeaway here is that business leaders should spend time familiarizing both themselves and their departments with AI, before adopting it on a mass scale. This will help prevent against security errors and ensure the technology is making a difference.

Over three quarters of respondents reported individual value findings from AI, compared to just over half of those who reported company-level value, in a new study.

Likewise, the study found that many of the respondents believing themselves to be critical components of company innovation were also creating resistance on AI initiatives.

Viacheslav Brui, Head of AI Transformation at Sombra, spoke with Tech.co about the survey’s findings, and gave his advice for businesses implementing and developing their AI strategy.

Companies are Seeing More Personal Value from AI Than Company-Level

Personal value from AI was more visible than company-level value in a new survey from Sombra. 87% of respondents claimed they had gained transformational, significant, or moderate value from AI in the last 12 months. Comparatively, only 55% of respondents said their company had benefited from AI implementation.

Viacheslav Brui, Head of AI Transformation at Sombra, told Tech.co in an exclusive interview that there are “multiple factors” that can influence whether a company is seeing benefits from AI.

24% of respondents admitted they hadn’t looked into whether their company has benefited from AI implementation, and 15% said leadership had never communicated any gains. As a result, the study suggests local benefits are more visibly seen, whereas company-wide benefits are not always clearly communicated.

The Danger of AI “Champions” and Individual Resistance

The study states, quite plainly, that “innovation has an ego problem.” This is evident in the findings: 79% of respondents saw themselves as a major force behind innovation at their company, and 64% believed innovation would weaken in their absence.

It’s quite common, Brui explains, for companies to select a few AI “champions”, or those that have adopted AI at a very high level. The problem is that this expertise is often not shared with the rest of the organization. “We have one champion, who is on the cutting edge: he knows everything about how to improve performance. But the department in the next room have no idea how to apply that,” Brui says.

The danger of this is that while some employees are seeing individual benefits, the organization as a whole is lagging behind. The best solution is to ensure knowledge is shared across departments.

At Sombra, Brui says, they pick enthusiastic people from each department, give them the tools and the training, and then ask them to share this knowledge with their colleagues. This is better than say, leadership giving general use cases across the business, because it means individuals can adopt AI while remaining “close to their workflows,” meaning overall benefits are far more likely, says Brui.

However, while respondents rated themselves highly on an individual level when it came to innovation, many of the same respondents also admitted to slowing innovation down. 22% had done so because of unreliable data quality, and another 22% said they didn’t see enough value in the project.

Sombra suggests this means innovation depends as much on “individual conviction, control, and willingness to let other people’s initiatives succeed” as it does on organizational support.

How Businesses Can Develop Their AI Strategy

In our interview, Brui broke down what he believed businesses should prioritize when implementing and developing their own AI strategy. He believes leadership should provide support to middle management, and keep them informed on business goals, ownership, and budget.

“Understand what are the company goals and which of those company goals can be achieved with AI, and actually give authority to middle management to decide what initiatives can support these goals.” Viacheslav Brui, Head of AI Transformation at Sombra

Likewise, it’s important for businesses to understand why they are adopting AI. This could be for better ROI or improved customer satisfaction, but “adoption for adoption won’t work,” Brui says.

Another big concern for respondents was data privacy and security, with 58% reporting they’d resisted AI initiatives because of this reason. On this note, Brui says, “I would put in place the policy and the rules of how AI can be used, and set up governance around AI to make sure we prevent data leakage.”

Businesses should also opt for a clear AI policy that details what employees “shouldn’t do with AI so as not to harm the business,” Brui adds.

Overall, businesses should start small. Give employees access to AI tools, and let them understand the basics, like reading documents. Then, maybe introduce AI agents. The main takeaway from Brui? “Don’t build a rocket ship if you cannot build a paper plane.”

This article is part of an interview with Joe Roushar, CEO and founder at Empathi AI, conducted for Tech.co’s newsletter, The AI Strat. For more interviews with AI experts on the latest trending topics, subscribe to the newsletter here. 

AI will eventually lead to the flattening of corporate leadership structures, according to Empathi AI CEO and founder Joe Roushar in an exclusive interview with Tech.co.

Experts weighing in on the subject believe the source of workplace power will change, as AI changes the kinds of capabilities workers have access to. This creates new opportunities to teams on the ground floor and entry-level workers who are new to the workplace.

Despite these changes, Roushar believes in the importance of managers during times of AI investment, and urges businesses to continue to train and monitor management as the technology becomes more and more integrated.

Corporate Structures Will Flatten Because of AI, Expert Says

Joe Roushar, CEO and founder at Empathi AI, believes AI will help “break down the silos” that make hierarchial structures within businesses necessary, leading to a flatter corporate pyramid.

“When you break down the silos, you also break down the stone pipe. Having a flatter structure between the people on the floor and the people in the office will be an inevitable result of more artificial intelligence,” Roushar said in an interview with Tech.co.

With AI, it could be the case that employees below the management level gain access to capabilities that would otherwise have been obtained through years of experience.

How Companies Will Organize Themselves After AI

Anish Batlaw, writing for General Atlantic, describes how he believes workplace hierarchy will more closely resemble a “shape-shifting organism” as AI becomes more widely integrated.

Batlaw explains how tasks will be completed within this new structure: when a task needs to be done, teams come together, organize and use a team of AI agents to achieve the outcome, and collapse when the task is done. “The teams coordinate laterally rather than reporting vertically. They set outcomes, define constraints, and make the judgment calls that require human context.”

Many experts have weighed in on the potential of AI, but it can be intimidating to imagine entire corporate structures changing. Is it even possible to imagine a workplace without managers, and how will ambitious employees develop and rise in their companies without opportunities for promotion?

In an article for Forbes, Bernard Marr suggests AI could provide an opportunity for junior and mid-level employees to come into the workplace with superior skills than those in senior positions. AI will, according to Marr, allow these workers to “produce work that once required researchers, analysts, designers, administrators, and technical specialists.”

This new set up suggests any employee, at any level, will be able to make a large impact within companies. However, it may mean AI will have to be more carefully regulated, if businesses reach a point where senior leaders aren’t interacting with every project AI touches.

Management Remains a Key Influencer

We’re not at the point where managers are obsolete, however, and Joe Roushar explained to Tech.co how he believes management is a vital component of how AI develops and performs within a business.

“They say that the most common reason for people leaving a company is because they have a poor relationship with their supervisor, and I believe that’s true,” Roushar said, suggesting strong management is key to retaining top talent.

“Good companies improve the quality of their middle management. Having AI doesn’t impair that capability, it just makes you have to be more planful and intentional in training your management, in monitoring your management, and in making sure your management continues to incentivize each of your employees who are using AI,” Roushar continued.

Similarly, Roushar advises managers and leaders to continue to empower their employees during times of AI investment, and give them the opportunity to reinvent themselves on their terms. “As AI takes over more brain tasks, and might require fewer people to do those tasks, people will reinvent themselves, and that’s a good thing.”

At the center of Roushar’s philosophy on AI is giving employees the option to be the hero of their own story, and decide what it is AI is going to do for them, not just their company.

Just when you think you’ve learned everything there is to know about AI, a new tool pops up, and it’s back to basics for everyone.

Whatever your role, remaining agile and attentive during this time of rapid AI development is the key to success, and online courses are a great (and free) way to assure you and your business remains competitive.

Businesses are already reporting heavy AI wins. A recent Gallup poll found 65% of US workers say AI has had a positive impact on their productivity. However, another study has found AI performs ‘potentially harmful actions’ 80% of the time, meaning businesses should still exercise caution and remain informed when using the technology.

Building AI Agents with Agno – Edureka

Summary:

• Learn how agentic AI systems work and build your own working agents using Agno’s API
• 4 modules, taking approximately 6 hours to complete
• Beginner-level
• Shareable certificate available on completion

Everybody’s talking about AI agents. Gartner predicts businesses will have over 150,000 agents by 2028, signaling a real demand for elaborate and autonomous systems that live within everyday workflows. So there’s definitely no harm in taking a course that allows you to build your own, especially if you’re yet to do so.

This course from Edureka says you’ll not only be able to build your own working agents, but you’ll learn how to write effective prompts, different tool definitions, and how to structure outputs that make agents more accurate, secure, and automate reliably. Guidance on agentic workflows, model deployment, prompt engineering, AI orchestration, and AI workflows are also included.

The course is recommended for software developers and others with basic experience writing code in Python. Familiarity with APIs, command-line usage, and LLM concepts is also helpful, but most of all the course asks for a willingness to practice through hands-on coding tasks, making it overall great for beginners.

Learn more about this course at Coursera

AI Fluency: Framework & Foundations – Anthropic

Summary:

• Learn how to collaborate effectively with AI
• 14 lectures, 1.1 hours of video, 1 quiz
• Beginner-friendly
• Shareable certificate available upon completion

Anthropic is the well-known makers of Claude, arguably some of the most powerful AI models at the moment. Anthropic offers many different free AI courses, and this one invites users to learn to collaborate with AI “effectively, efficiently, ethically, and safely.”

In this course, you’ll learn The AI Fluency Framework created by Anthropic and professors Rick Dakan from Ringling College of Art and Design and Joseph Feller from University College Cork. This consists of four interconnected competencies: Delegation, Description, Discernment, and Diligence.

Whether you’re deploying AI to your team for the first time, or creating a strong and safe AI culture, this framework promises to help guide human-AI collaboration.

Learn more about this course at Anthropic

AI Prompting for Everyone – DeepLearning.AI

Summary:

• Learn how to effectively prompt AI tools
• 21 video lessons, spanning 7.4 hours overall
• Beginner-level
• Graded assignments and a certificate available with Pro subscription

Companies are spending more and more on AI, and as many AI companies switch to usage-based pricing models, learning how to effectively prompt could make the difference in keeping costs down and sparing your bottom line.

This course, taught by AI pioneer Andrew Ng, provides an up-to-date guide on prompting AI tools for tasks such as finding information, brainstorming and writing, and no-code website building. Aimed at all users, this course provides the fundamentals for any business owner or leader that wants to better their company’s interactions with AI systems.

DeepLearning.ai says the course is a great next step if you’ve already completed its Generative AI for Everyone or ChatGPT Prompt Engineering for Developers courses, but these aren’t essential to starting.

Learn more about this course at DeepLearning.AI

Ethical Considerations for Using Generative AI – IBM SkillsBuild

Summary:

• Learn the fundamental ethical considerations of using AI
• 60-90 minutes total course time, available in 7 languages
• Beginner-level
• Users must be registered to take part

IBM is a champion of AI courses, and has plenty for registered members to complete for free.

On this course, you’ll “explore the fascinating and complex world of ethics as they relate to generative AI.” Likewise, you’ll discover the specific risks related to data inputs and consider the ethical implications of AI-generated output. Included is also guidance from the IBM AI risk atlas.

Business leaders should be fully aware of the ethical implications of any AI investments. By learning these fundamentals, businesses can protect themselves from legal and reputational risk, and ensure they remain compliant with regulations while using the tools.

Learn more about this course at IBM

Why It’s Important to Keep Learning AI

Leaders might no longer be predicting a jobs apocalypse in response to AI, but the technology is still running rampant in workplaces. The companies exposed to AI are seeing as much as a 163% growth in productivity in some studies, and AI spending continues to rise.

By focusing on what they have learned previously with AI and failing to keep up with new developments, business leaders risk being left behind. It’s hard to predict where the technology will be even in the next year, so taking advantage of free courses like the ones above means leaders can correctly guide their teams through the next AI wave.

Even if you’re not using these tools yourself, having an understanding of how they work will help inject a positive, AI-friendly work culture into your company.