I started a company called Satalia 17 years ago that's been building AI solutions for some of the biggest companies in the world. I sold that company three years ago, but I continue to be its CEO. I'm also the chief AI officer for the company that bought Satalia, WPP. So I coordinate AI across, now, over 100,000 people.

I've just started a research organization trying to solve machine consciousness, which is going to become a very important topic over the next decade. And I am the CEO of a research organization called Conscium.

How would you define artificial intelligence?

There are many definitions of AI and the most popular definition, I think, is the weakest one: getting computers to do things that humans can do.

Over the past three years, we've managed to get machines to recognize objects and images, and to correspond in natural language. And when we get machines to behave like humans, because humans are the most intelligent thing we know of in the universe, we assume that that's intelligence.

But if I built a brain that operated as intelligently as a mouse, it would be the most intelligent machine that we've ever built. So using human intelligence, the pinnacle, as the model is not very sensible. There's a much better definition of AI that comes from another definition of intelligence, which is “goal-directed adaptive behavior.” It's a beautiful definition.

We use AI to achieve goals: route our vehicles, optimize deliveries, or allocate our workforce to use it most effectively. Behavior means how we can move toward those goals, but the key word is “adaptive.” You want to build systems that can make decisions, learn about whether those decisions are good or bad, and adapt themselves to make better decisions next time.

If I held what we’re currently doing in industry to that definition, I might controversially argue that nobody's doing AI. That's a ridiculous statement, because new advances in algorithms, data, and computers allow us to do some incredible things.

So, I advocate not looking at AI through technologies or definitions, but through applications.

What are the key benefits of AI in the workplace?

There are some key challenges associated with the workplace. One is hiring the right people. It's forecasting job demand, what resources you have, and people’s skills, hopes, dreams, and desires. Most organizations are not aware of the skills they have in their workforces.

One of the key challenges is how to allocate the right people to the right opportunities in a way that aligns with the values of those people, their career development, and the values and needs of the organization. You don't want to use generative AI to solve that problem; you want to use optimization, which matured in academia probably 30 or 40 years ago.

You can use AI as a data-driven way to identify the right people to help with your development. You can use AI to identify the appropriate people to give feedback – rather than you choosing five of your friends.

We solve problems involving thousands or tens of thousands of people, and trillions of calculations. So using human beings to solve these problems is a waste of time. You want to be using optimization algorithms, to allocate people to the right opportunities.

You then want to be using machine learning, not necessarily generative AI, to understand whether those people have worked well on those projects, whether those projects have helped develop their skills, so that you can then better allocate them next time.

What can leaders and managers do to bring these benefits to their team and daily workflow?

Adopting Agile and Scrum methodologies is really important. It allows you to get visibility into your teams, and forces you to break your skills down into more granular segments. You can then start to get the data in a good shape and use more intelligent AIs to allocate people to opportunities.

Leaders need to educate themselves around what these technologies are and aren’t. Don't get seduced by generative AI. Don’t get seduced by machine learning. Make sure that you understand the nature of your problem and the type of technology you should be using to solve that problem.

What are the most important things for them to know and learn as AI becomes more commonplace?

Learn about the nature of the problem.

And then you need to educate yourself as a business leader in terms of what the right technologies are to solve these problems. And if you have not developed and deployed software in a scalable way, you're not going to be able to do it with AI.

Go to third parties, go to experts, go to your partners, go to startups that are focused on, dedicated to solving this problem. You don't want to be solving lots of those problems yourself.

What are the risks of AI in the workplace?

There are broadly three questions you need to ask yourself when implementing these technologies in a safe and responsible way. First, is the intent appropriate? If your intent is to identify people to let go, or to squeeze more work out of them without developing their careers , then you're probably going to cause harm elsewhere, or you're breaking the law. So, scrutinize your intent. That's an ethical question. And there are already well-established frameworks and structures to question intent.

Second, are the algorithms that you’re deploying explainable? If your algorithms are opaque, if you don't know how they're making their decisions, then you're potentially going to make harmful decisions. So, building explainable algorithms is extremely hard, but I think it's critical, particularly in the workplace.

Third, what happens if I build a system that overachieves its goal? You can allocate people to work in a much smarter way. But that might mean that clients aren't getting the continuity they want, or employees aren't getting time to train. And so you have to ask yourself, what happens if the AI overachieves its goal and what harm will that cause to the rest of my supply chain?

What’s your take on AI ethics and safety?

Ethics is the study of right and wrong. The difference between human beings and AI is that human beings have intent, and it's intent that you need to scrutinize ethically; it’s not AI. AIsdon’t make ethical decisions.

There are currently two questions you need to ask yourself on safety problems. One: are my algorithms explainable? Two: what happens if my AI goes very right? What problems can that cause? If you ask yourself those three questions, then you cover a lot of the questions and problems associated with deploying AI in a safe and responsible way.

Your company, Satalia, has a different organizational structure than most. Can you share a little about how it operates and how this connects to artificial intelligence?

Yes. We're trying to use AI to identify the best diverse group of experts to make a decision. Most organizations operate as fixed hierarchies. You end up having people making decisions who shouldn't be. AI can identify the appropriate people and empower those people to be able to make decisions.

That's how I think organizations need to operate: in a liquid way. If they operate in a liquid way, they’re more adaptable. If they’re more adaptable, going back to our definition of intelligence, they’re more intelligent.

So, Satalia is using AI to create a liquid, fluid organization, making sure that we get the right people making the right decisions at the right time.

Can any of the insights you’ve gained from working in this non-traditional way be applied to strengthen organizations with more traditional structures?

Yes. If you can start to operate with an Agile scrum-type methodology, it will force you to get control over your data. Don't wait for your data problem to be solved because it won't ever be solved. Start with the problem you need to solve, then work backwards.

Then you can start to use AIs to identify people who have skills and have them make decisions around feedback, or career development, or salary setting, or performance management.

Hiring people is still a very big challenge. You don't really know if somebody's going to work well with you until you’re working with them. I’d love AI to be able to solve that; I just don't know how.

What's Next?

For an overview of what AI does and doesn’t mean, read our article What Is AI? For specific tips for applying artificial intelligence tools when working with your team, see How to Use AI as a Manager.

Tip of the Week

Four Conflict Resolution Mistakes to Avoid

By Simon Bell, Mind Tools Writer and Editor

Differences of opinion between team members are only natural. Careful, though. It’s great having an enthusiastic and energized team, and quite another to have one whose members are raging at each other on a regular basis.

Here are four common mistakes managers make when handling conflict. Steer clear of them if you can!

1. “It’s not my problem.” Yes, it is. Managers have a responsibility to actively manage conflict in their teams. Without control, the problem will escalate.
2. “Conflict? What conflict?” Many managers don’t spot the early signs of conflict in their team members’ body language. If you do, address the problem quickly.
3. “It’ll blow over.” Conflict usually arises from small disagreements that you can often resolve early on. If you don’t, the conflict may blow up into something way more serious than it needed to be.

"Yeah, I’m on your side.” Even if you agree with one individual, stay objective. Address the issues causing the conflict to reach a resolution that works well for both sides.

Pain Points Podcast

On the podcast this week we explore emotional intelligence. It's a phrase that's thrown around a lot, but what does it actually mean? How do you get it? And does everyone at work need it – even the people in charge? Jonathan Hancock meets up with author, leadership coach and mentor Sarah Harvey, for Pain Points: "Do Leaders Need Emotional Intelligence?"

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News Roundup

This Week's Global Workplace Insights

The Three Culture Questions to Ask in an Interview

Corporate culture expert Marion Campan recommends asking three key questions during job interviews to assess a company's culture. On CNBC.com Campan, founder of HR consultancy Intandid, highlighted the importance of interviews in helping candidates to evaluate potential employers.

1. First, ask “What kind of people get promoted here?” The answer will tell you plenty. If those getting recognized are genuine movers and shakers rather than time-servers, that's a good sign.
2. Second, ask about the company's core values. Positive answers will talk about those values, and back them with recent examples.
3. Finally, inquire about the feedback process – regular, constructive feedback is a good sign, while annual-only reviews may be a red flag.

Nolan Church, former Google recruiter and CEO of FairComp, suggests other specific questions, such as asking about top performers' common traits and what employees love about the culture. Both experts agree that these inquiries can provide deeper insights into what it’s like to work at a company.

For more interview tips, see our article Interview Skills.

The Rise of the Gig

Despite concerns about an economic slowdown, the gig economy continues to thrive, with over a third of the U.S. workforce now engaged in flexible work, a figure expected to reach half by 2025.

Gig work’s flexibility and ease of access have made it highly appealing to job seekers, attracting attention from HR leaders who must compete with these opportunities, as reported on Worklife News.

According to Victoria Bethlehem, chief people officer at talent marketplace website Jitjatjo, gig work’s adaptability is especially attractive in uncertain economic times. Gig roles span industries like healthcare, hospitality and retail, offering diverse opportunities.

A survey by Jitjatjo found that most Americans under 45 believe flexible workers will drive the U.S. economy in the future. Additionally, younger workers, especially Gen Z and millennials, prioritize early wage access, further boosting gig work’s appeal. Companies are increasingly using AI to provide gig-like flexibility, recognizing that work-life balance and autonomy are key to retaining talent.

See you next week for more member-exclusive content and insight from the Mind Tools team!