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 here. 

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 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.

China has finally caught up with Mythos on cybersecurity. Zhipu AI, known as Z.ai, has released its open-weight GLM-5.2, and experts are concerned that it could match up to Claude’s Mythos, which is considered the gold standard in cybersecurity.

While it reportedly lags behind in general areas, China appears to have closed the gap between itself and the US in the realm of defense, with Z.ai demonstrating a similar level of proficiency in detecting security vulnerabilities.

The news will cause panic to echo through the halls of power. The US government has gone to great lengths to restrict China’s access to Mythos and related models, with such tools regarded as serious threats to national security.

China Rivals Mythos on Cybersecurity With New AI Model

China’s Z.ai has released its latest AI model, GLM-5.2, which can detect security vulnerabilities as effectively as Mythos, researchers claim. While it can’t compete with the likes of Claude and ChatGPT in terms of general performance, it has proven highly capable in “cybersecurity scenarios.”

Revealed in April to significant alarm, Mythos is a tool for detecting vulnerabilities in cybersecurity infrastructure. US lawmakers have warned that it could instead be used to power a catastrophic wave of cyberattacks.

In the interim, the federal government has been engaged in a protracted saga with Anthropic surrounding public access to the platform. Recently, it granted the company permission to release its latest model, Mythos 5, to a group of about 100 businesses and federal agencies.

Cheaper & Publicly Available

Z.ai GLM-5.2 is an “open-weight” model, which means that it can be downloaded and operated by anyone with the relevant hardware. It can also be modified, with bad actors theoretically able to remove safety guardrails and use it for illicit purposes.

“An attacker can run it locally without safety guardrails, fine-tune it against their specific targets, and operate with zero visibility to any provider or defender.” – Travis Lanham, CTO and founder of Armadin

Compounding these anxieties, GLM-5.2 is also significantly cheaper than comparable US models, including Claude Opus 4.8 and ChatGPT-5.5. There are reports that it could be an “illegal distillation” of those two models, with Anthropic earlier this year expressing concern that Chinese companies were launching attacks to steal its model weights.

Businesses Must Act Now to Avert Security Disaster

There are fears that the repercussions could be catastrophic. Business cybersecurity is already in a dire position. As attackers harness AI to commit increasingly sophisticated data breaches, firms suffer the impacts of a yawning skills gap. If it falls into the wrong hands, GLM-5.2 could make a bad situation infinitely worse.

Businesses need to overhaul their cybersecurity practices. As a starting point, they need to invest heavily into the best talent. With higher education facilities across the US doing their bit to close the skills gap, this should hopefully become easier in the near-future.

At the same time, firms should focus on training their existing workforce on how to spot cyberattacks. This is a problem that starts at the top, with a scarcely believable 98% of bosses unable to identify all the signs of a phishing attack.

And finally, it’s critical that companies adopt the latest technology. There is cause for optimism in this respect, with 83% of businesses already using AI to combat data breaches. As AI models continue to develop apace, so, too, do answers to the questions posed when powerful technology falls into the wrong hands.

AI regulation is apparently a bipartisan issue, with a new study showing that both Democratic and Republican voters are heavily in favor of more robust standards for the technology.

The report pointed to a wide range of measures that AI companies should address, like a guaranteed “off” switch, regulatory guardrails, and pre-release safety tests.

In 2026, businesses need to consider the fact that everyday users are still quite skeptical about AI and want to see it reigned in before it’s too late.

AI Regulations Are a Two-Party Issue

According to a report titled The AI Safety Majority from the Artificial Intelligence Policy Institute (AIPI), Democratic and Republican voters in the US believe that AI regulation is important.

More specifically, 82% of Democrats and 77% of Republicans believe that the industry needs regulatory guardrails to remain safe.

This report surveyed 1,007 U.S. likely voters across the country to collect data in regard to how Americans feel about AI.

What Kind of AI Regulation Do Americans Want?

Democratic and Republican voters weren’t just aligned when it came to applying required guardrails for AI regulation. Across the survey, the party voters were mostly on the same page when it came to various flagship items of AI regulation, including:

• Guaranteed off switch: 88% D vs 83% R
• Congress address loss of control: 87% D vs 82% R
• Don’t build until controllable: 84% D vs 83% R
• Mandatory pre-release safety tests: 72% D vs 72% R

Simply put, there are very few issues on which these types of voters agree, but when it comes to regulating AI, the partisan gap is a lot smaller.

AI Concern Remains High

In 2026, AI is not the silver bullet many businesses hoped it would be. AI errors from simple typos to full-on database deletions have eroded public trust in the technology so much that most people are more concerned than excited.

The data from AIPI found that people are far more concerned about the negative impacts of AI (56%) than they are excited about the changes from its growth (18%).

All that to say, businesses need to be cautiously hesitant when it comes to diving all-in on AI technology. Without a human-led strategy, you could end up with a lot more problems than solutions.

New research from Pegasystems finds the businesses seeing the most success from agentic AI implementation are focused on reimagining existing processes. This suggests businesses should aim to enhance existing functions based on their needs.

Peter van der Putten, director of the AI Lab at Pegasystems, spoke to Tech.co about the most meaningful measure of agentic success being “adoption at scale.” Similarly, he adds, “Organizations must connect AI initiatives to strategic priorities and core business processes and tie them directly to measurable outcomes and metrics.”

The study urges businesses to examine their existing processes, sourcing the ones that can be automated, and use collaborative and innovative approaches to maximize deployment based on clear governance and business goals.

Use Agentic AI to Reimagine Existing Processes

New research from Pegasystems Inc. and research firm Savanta, finds organizations seeing the most success when delivering agentic AI are doing so by rethinking the existing processes they already have in place.

Overall, 96% of respondents said they had achieved success by rethinking existing processes. 53% said they had done this to a “significant” extent, by reimagining everything their company does.

For this report, Pega surveyed 500+ business and IT decision makers worldwide who had successfully implemented agentic AI projects.

Support a Culture of Collaboration and Innovation

The businesses seeing the most success with agentic AI are fostering a culture of collaboration and invention. 80% of respondents report business and IT operations were willing to introduce new technology, innovation, and ideas to explore new possibilities. Most of this stems from a desire to take existing processes and make them more predictable and consistent.

This doesn’t necessarily mean simply replacing entire workflows with agentic capabilities, however. Peter van der Putten, director of the AI Lab at Pegasystems, explained in an interview with Tech.co that human and AI collaboration remains a critical element. 

“Agentic AI should not be pursued in isolation,” van der Putten says. “It must be combined with other forms of artificial and human intelligence and orchestrated within how work is executed across the organization. This includes both straight-through workflows and human-in-the-loop decision-making.”

Similarly, van der Putten expresses the importance of governance and explainability. “Agent behavior must be auditable, measurable, monitored, an controlled to ensure consistent and predictable outcomes.” This not only creates more consistent outcomes, but protects businesses from common AI mistakes like poor data quality.

Prioritize Corporate-Level Strategy

A staggering 95% of businesses who successfully deployed AI agents had a specific, corporate-level strategy and plan for execution. This strategy should be tied directly to success metrics, which are regularly reviewed and evaluated based on progress.

In a press release, chief technology officer at Pegasystems Don Schuerman said, “We’re fast reaching a tipping point with agentic AI where adoption is high within organizations, but maturity is not.”

Curious about what Schuerman believes “mature” AI adoption looks like, I asked van der Putten, who started by defining what it doesn’t look like. He dismissed “large data science teams experimenting in isolation,” and simply providing employee access to tools like Claude or Gemini.

Instead, it “reflects a shift from experimentation to execution, from activity to outcomes, and from isolated agents to agentic AI embedded in orchestrated systems of work.” To achieve this, van der Putten adds, leaders must align business and IT around shared outcomes, and design for “predictability, governance, reduced complexity, and scalability from the outset.”

How Businesses Should Focus Agentic Investments

In terms of what businesses should focus primarily on when deploying agentic AI agents, van der Putten said: “Too often, core and primary business functions, especially those running on legacy systems, are left untouched. This is understandable, as these environments consume the majority of IT resources and governance attention. However, it is also a critical mistake.

“Agentic AI should be used to reimagine these core systems and processes as part of a modern AI-enabled enterprise architecture. The starting point must always be the processes and outcomes that matter most to the business, rather than isolated use cases at the periphery.”

The message for businesses is to be strategic, but also, think holistically. Gaining a strong understanding of how individual processes connect to wider success, sets you up for an agentic solution that supports all business functions.

You can now officially talk to Claude in Slack, with Anthropic announcing the new Claude Tags feature for messaging platforms.

By giving Claude access to their Slack platform, users will be able to tag the AI to ask questions, request specific tasks to be performed, and receive updates on company priorities.

Claude Tags is currently only available for Enterprise and Team users, and it’s only available in beta, but the company obviously has plans for a wider rollout in the future.

Anthropic Unveils Claude Tags

Announced in a company blog post, Claude Tags are a new way to access the increasingly popular AI model on messaging platforms like Slack.

Users will be able to tag @Claude in Slack conversations to get information and perform tasks without having to leave the messaging platform.

Claude Tags can currently be used in Slack by Team and Enterprise users in beta, although the company has plans to roll out the feature to broader Claude users and other messaging platforms.

What Can Claude Tags Do?

Claude Tags can perform a wide range of tasks for your staff, without your employees having to leave the messaging platform at all. It can:

• Work collaboratively – Claude Tags exist in Slack channels for everyone to see, so your team can collaborate on what is said and how to move forward.
• Provide updates – Claude Tags learn over time in specific Slack channels, so it can provide relevant updates.
• Perform tasks – You can instruct Claude Tags to perform specific tasks right in Slack and follow its progress in threads.

Claude Tags will replace the existing Claude for Slack app in the messaging platform.

Is Claude Best for Business?

In the early AI years, ChatGPT was the go-to solution for the majority of businesses, because it was the most advanced and accurate among the various chatbots.

However, over the last few months, Claude has established itself as the clear favorite, with more and more businesses getting on board. This is largely because of Claude Code and Claude Cowork, which makes automating businesses tasks infinitely easier.

With the launch of the decidedly convenient Claude Tags, Anthropic could be positioning itself as the de facto business AI for the foreseeable future.

The AI boom has had a negligible impact on the US workforce and wages, according to a new study from the European Central Bank (ECB). Despite firms’ heavy investment in the technology, fears that AI will lead to mass unemployment are so far largely unfounded.

According to the research, the US economy began to adjust to the emergence of AI several years ago, with jobs from the most vulnerable sectors being reallocated to other segments. This has gradually reshaped the labor market, but the study notes “no major income effects” from this shift.

Researchers do not rule out more pronounced changes in the future, however. As CEOs across the country gear up to make layoffs in favor of automation, businesses should be mindful that a winning AI strategy is built on maintaining a “human-in-the-loop.”

AI Boom Yet to Significantly Impact US Workforce and Wages

The ECB has found that the AI boom of the last few years has not yet substantially altered the US workforce, despite fears to the contrary. There has also been no noticeable impact on wages, the report notes.

Some workers may be displaced, with junior staff in “highly exposed sectors” thought to be most at risk. However, the report observes, the overall aggregate impact on the workforce and wages has so far been minimal.

The US economy begun its adjustment to the AI explosion several years ago. In the interim, jobs from the most vulnerable sectors have been reallocated to other segments, which has slowly reshaped the labor force.

Workforce and Wages Largely Unchanged Since 2019

According to the ECB: “All else being equal, between 2019 and 2025, jobs with a high substitution risk grew by around 15 percentage points less than jobs with a low substitution risk.”

Across this period, jobs with a “high substitution risk,” such as economists or graphic designers, declined by an average of more than 4%, while low-risk jobs, including electricians and teachers, increased by 13%. On a macro level, low-risk jobs grew from 23% to 25%, while high-risk jobs dropped from 35% to 33%.

ECB has observed no major impact on US wage, stating: “AI substitution risk has had no significant impact on wage growth since 2019.” It did, however, sound a note of caution: “Over time, as the labor market continues to adjust and AI tools become more generative, income effects may be more pronounced.”

Successful AI Strategy Hinges on Human Involvement

With the majority of US businesses now leveraging AI, and many more set to embed it into their ways of working in future, firms face renewed pressure to develop a rigid deployment framework. When a company rushes to embed AI without pausing to consider the ramifications, it can lead to “AI debt,” which can have damaging reputational and financial impacts.

In order to mitigate this, it’s crucial that businesses reflect on their AI strategies before they pull the trigger. While the rewards can be massive, the inverse is also true — failure to properly map out your integration plan will only hurt your prospects.

Human involvement is a key part of this. The temptation is to outsource wholesale processes to technology, but keeping a “human-in-the-loop” will ensure that you avoid obvious mistakes, leave the door open for data breaches, and ultimately waste vast amounts of time and money.

Google’s AI lab, DeepMind, has just introduced a new security framework that classifies autonomous, untrusted artificial intelligence agents as internal security concerns, calling them “potential insider threats.”

The roadmap is designed to contain and monitor AI systems that try to bypass human oversight.

At the same time, OpenAI is rolling out a new raft of security features for its own AI tools. In 2026, it seems, top AI companies are taking security risks more seriously than ever.

How Does Google’s New Roadmap Work?

Google Deepmind announced their “AI Control Roadmap” in a blog post that revealed a rough overview of the framework.

It covers “system-level mitigations that limit the harm a misaligned AI system could cause” across four different areas. First is threat modeling, which lists tactics to use against a “hypothetical AI adversary,” assuming a worst-case scenario.

The other areas covered in the roadmap include two control invariants (specifically, reliable detection of misaligned intent and effective responses to attack attempts), capability-based mitigation ladders (defensive measures that can evolve alongside AI model capabilities), and a portfolio of practical defenses, which is a list of specific, actionable interventions or safeguards.

If you want even more information on all of the above, check out Deepmind’s full 36-page research paper.

Deepmind’s Mitigation Plan

The same announcement also discussed Deepmind’s plan to “deploy AI control mitigations” through a two-pronged approach.

• Identifying the problem (Detection): Uses trusted AI systems to constantly review the less-trusted working agent’s reasoning, actions, and plans in order to keep them on track.
• Managing the problem (Prevention and Response): This gives supervisors their next steps, should they spot an agent taking harmful actions.

While all of these responses might appear to be validating fears of a robot uprising straight out of Terminator or The Matrix, it’s actually a more mundane response.

This new roadmap is essentially taking a zero-trust approach to computer security: We can only be sure that we’re preventing unauthorized system actions by never actually trusting AI agents to be fully autonomous, regardless of how likely they are to go off book with harmful actions.

OpenAI Boost Security Protocols As Well

It’s also worth mentioning that OpenAI has itself announced several security-oriented changes this week.

The company is releasing an updated iteration of the security-focused model GPT-5.5-Cyber and has just released the Codex Security scanner as an app plugin, giving users a simple way to vet code in order to identify, validate, and patch any vulnerabilities.

OpenAI’s ChatGPT and Google’s Gemini are two of the most well-known AI tools operating today.

Seeing both companies working towards increasing security measure surrounding AI agents and tools is an indicator that the cybersecurity ecosystem is well aware of the many challenges that it currently faces as LLMs continue expanding their influence to, well, just about everywhere.

83% of organizations are using, or planning to adopt, AI to bolster their cybersecurity, a new study has revealed.

According to the research, the top use cases for AI include automating scanning and testing (50%), predictive risk analysis (48%), and threat detection (38%). Despite the emergence of AI, a further 68% of respondents say that the job has become harder in the last two years.

The study points to the yawning cybersecurity skills gap, which is devastating the business sector. Ultimately, to combat the rise of AI-driven cyberthreats, organizations need to adopt a three-pronged approach — deploying the latest AI security systems, upskilling their existing employees, and investing in top talent.

83% of Organizations Leveraging AI for Cybersecurity

According to new research from ISSA and Omdia, the majority of organizations are either already using AI or planning to in order to combat the rise of AI-driven cyberthreats. The “Life and Times of Cybersecurity Professionals” finds that no fewer than 83% of organizations have AI at the center of their cybersecurity plans.

Top use cases for AI include automating scanning and testing (50%), predictive risk analysis (48%), and threat detection (38%). Despite this sharp uptick in adoption, however, a further 68% of respondents confirm that their jobs have become harder in the last two years.

This impact is being felt across the business, with almost half of respondents confirming that they’ve thought about leaving their role in the last 18 months, with 57% of those considering leaving cybersecurity entirely.

AI Spend Not Aligned to Strategy

The results suggest that part of the problem stems from inefficient AI strategies. Reportedly, 25% of organizations have increased their AI spending without a defined strategy connecting it to their employees or security program.

The existing workforce is feeling the brunt of this disconnect between spend and strategy. According to the study, 71% of participants say that technology decisions are made without the input of security teams.

“Eight years of data point to the same conclusion. The profession is struggling not because talent is scarce, but because organizations are not investing enough in the people they already have. That is the leadership opportunity in front of us right now.” – ISSA President, Jimmy Sanders

Businesses Reach Cybersecurity Inflection Point

This spiral is leaving businesses in a tough spot. As employees become more disenchanted, the existing skills gap threatens to become more pronounced. And with 88% of cybersecurity professionals already experiencing the “significant” impacts of the skills gap, that could spell disaster for the business sector.

Ultimately, a coherent and effective cybersecurity strategy rests on a three-pronged approach. Organizations must continue to invest in the latest defense technology in order to keep pace with hackers, who are increasingly adopting new AI-driven approaches.

However, this strategy will only succeed if paired with an aggressive investment in talent. Institutions need to closely monitor the talent pool and move quickly to hire the latest specialists. With several higher education facilities adopting a hands-on approach to cybersecurity learning, this pool should hopefully deepen in the future.

Finally, businesses need to upskill their existing employees in cybersecurity best practices. This is a problem that starts at the top, with a shocking 98% of senior leaders unable to correctly identify all the signs of a phishing attack.

The FBI has issued an urgent warning about a fast-acting phishing scam operated by the hacking platform Kali365.

The scam targets Microsoft 365 users — anyone using Teams, Outlook, or OneDrive could be in danger.

The goal of the phishing scam is to trick potential victims into handing over their OAuth device codes, which the hackers can then use to bypass multifactor authentication and access Microsoft accounts. To stay safe, you’ll have to keep your OAuth tokens to yourself.

What Does the Scam Look Like?

If you’re targeted by Kali365, you’ll receive a phishing email that appears to be from an authentic document-sharing platform. It will have a device code and instructions on how to verify yourself.

The FBI’s warning, available online here, walks viewers through the four steps of the scam:

• Lure: An email “impersonating trusted cloud productivity and document-sharing services,” containing a code, which asks users to go to “a legitimate Microsoft verification page and enter the code.”
• Authorization: Entering this device code will actually give the scammer’s device access to the victim’s account.
• Token Theft: The scammer then “captures OAuth access and refresh tokens, granting them access to the targeted individuals/entities’ Microsoft 365 account.”
• Persistence: Armed with this access, the scammer can now gain access to even more Microsoft 365 services, like Outlook, Teams, and OneDrive, without needing to get any additional passwords or information.

What’s Kali365?

The threat doesn’t come from any single, unified hacking group. Instead, these phishing attempts might come from any scammer who own the Kali365 platform, a subscription-based service aimed at helping scammers become more effective.

News of this “scamming-as-a-service” software tool first emerged to the general public in April 2026, but has been circulating through closed groups on Telegram for a lot longer. According to a Bitdefender report, it costs about “$250 per month or $2,000 a year.”

How Can You Stay Safe?

The biggest thing you can do to avoid this particular scam is stay vigilant against any phishing emails. However, that’s easier said than done.

The FBI’s warning comes with a few technical tips for staying safe.

You can try to “create a conditional access policy to block device code flow for all users,” and you can figure out how to block authentication transfer policies, so that any users with unauthorized access can’t transfer their authentication between computers and mobile devices.

Finally, if you’ve already been hit, you can report the incident and help experts work to stop the evolving threat: Go file an online complaint with the Internet Crime Complaint Center (IC3) here if you’ve been impacted by the Kali365 phishing kit.

The companies most exposed to AI achieved labor productivity gains of 163% in a new study, significantly leapfrogging other businesses.

Within the labor market, AI is creating two different kinds of roles. “Professionalized” roles, where AI acts more as a force multiplier, are seeing a greater growth in hiring and wages compared to “democratized” roles, where AI makes a role easier to perform.

Companies are changing the requirements of roles as AI continues to sweep the workplace. This is most evident in entry-level roles, where human skills such as judgement and creativity are becoming more desirable.

The Companies Most Able to Use AI Are Pulling Ahead

Companies most exposed to AI, dubbed “super-star companies,” have seen labor productivity growth of 163% relative to 2018, in the 2026 PwC Global AI Jobs Barometer. These companies are in the top 20% of the most AI-exposed companies overall.

Companies operating within the most AI-exposed sectors recorded a 34% growth in productivity in 2025 compared to 2018, in contrast to the 24% recorded for the companies least able to use AI.

Likewise, headcount growth at the most AI-exposed companies is higher than the least exposed companies. Companies with more exposure saw 52% growth, compared to the 36% seen by those with less exposure.

AI is Creating Two Types of Roles

PwC reports that AI is creating a “two-track” labor market, consisting of “professionalized” and “democratized” roles.

For “professionalized” roles, AI acts as a force multiplier, allowing the expert to accomplish more than they ordinarily would. These roles include radiologists and recruiters. On the other hand, in “democratized” roles, AI evens the playing field, making a role easier for non-experts to perform. These roles include IT service managers or medical secretaries.

Overall, the study finds “professionalized” roles are seeing greater wage and headcount growth, with twice the amount of available jobs and 42% faster salary growth compared to “democratized” roles.

AI skills such as prompt engineering are also becoming increasingly more desirable. Jobs that require specific AI skills are growing roughly eight times as fast as the overall jobs market, and the average wage premium for AI skills has risen to 62%, up from 57% the previous year.

Increase in Human Skills Required for Roles

Although leaders are no longer warning about an AI jobs apocalypse, the technology is changing and reshaping the skills needed to thrive in the workplace. PwC found human skills, such as judgement, creativity, and leadership are becoming more desirable.

This is particularly evident within entry-level hiring. Based on 2.4 million entry-level jobs in the US, those exposed mostly to AI are seven times more likely to require traditionally senior-level human skills such as leadership or face-to-face interactions. Job openings for these roles have grown 35% since 2019, while other entry level roles have shrunk by 10%.

“The companies seeing the greatest returns on AI are using it to amplify human expertise, accelerate innovation and create entirely new sources of value. As a result, they are pulling further ahead on productivity and growth than companies that focus primarily on automation.” – Joe Atkinson, Global Chief AI Officer at PwC

These findings suggest human skills and retaining that “human touch” remain critical in the age of AI, and that graduates entering the workforce for the first time will be tested on different grounds than they have been previously.