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.