Everyone’s talking about the AI hype of today. I’m already thinking about 2027. Here are the three big leadership shifts that are going to blindside most people.
I get it. It’s easy to get caught up in the latest model release, the newest shiny object. But I’ve seen this movie before. I’ve been through a couple of exits, with RemoteTeam and MovieLaLa, and I’ve invested in over 200 companies, including some of the biggest names in AI like Anthropic, OpenAI, and Scale AI. And I can tell you that the technology is only half the story. The other half is leadership—the part that really determines success or failure.
I’ve been talking to a lot of founders and investors, and I’m seeing some big shifts in AI leadership. Here are the three trends you need to be watching.
1. The Chief AI Officer is No Longer Optional
For a while there, the Chief AI Officer (CAIO) was a bit of a novelty. A nice-to-have for the big tech companies, but not something most businesses took seriously. That’s about to change. By 2027, if you don’t have a CAIO, you’re already behind.
I remember talking to a founder a few years ago who was building an incredible AI-powered product. The tech was brilliant. But the company was a mess. The engineers were off in their own world, the product team didn’t understand the technology, and the CEO was just trying to keep the peace. The company eventually imploded. It wasn’t a technology problem; it was a leadership problem.
A great CAIO isn’t just a tech guru. They’re a translator. They can speak the language of the engineers and the language of the business. They can see the big picture and they know how to get things done. They’re the ones who will be responsible for setting the AI strategy, building the AI team, and making sure that AI is creating real value for the business.
So what makes a great CAIO? It’s not just about having a PhD in machine learning. It’s about having a deep understanding of the business, a passion for building great products, and the ability to lead and inspire a team. I've seen successful CAIOs come from a variety of backgrounds: some are former product managers, others are ex-consultants, and some are even former startup founders themselves. The common thread is that they are all masters of communication and collaboration. They know how to get buy-in from all stakeholders, from the board of directors to the junior engineers.
One of the most impressive CAIOs I know came from a non-technical background. She was a former marketing executive who had a knack for understanding customer needs. She taught herself the basics of AI and then surrounded herself with a team of brilliant engineers. She was able to bridge the gap between the technology and the market, and the company she worked for is now one of the leaders in its industry. That's the kind of creative, out-of-the-box thinking that will be required to succeed in the age of AI.
One of the most important jobs of the CAIO is to build a strong AI team. This is not just about hiring a bunch of PhDs. It's about creating a culture of innovation and experimentation, where people are not afraid to fail. It's about providing the team with the resources and support they need to be successful. And it's about setting a clear vision for what the team is trying to achieve.
2. AI is a Change Management Problem
You can have the best AI in the world, but if you can’t get your team to use it, it’s worthless. This is the reality that so many companies are struggling with right now. They’re investing millions in AI, but they’re not seeing the results they expected. Why? Because they’re treating AI as a technology problem, not a change management problem.
I saw this firsthand with one of my portfolio companies. They had developed a truly innovative AI tool that could automate a huge chunk of their customer support. They were so excited. They rolled it out to the team, and… nothing. The support agents just kept doing things the old way. They were comfortable with the old way. They didn’t trust the new tool.
The company had to go back to the drawing board. They brought in a change management consultant. They did a ton of training. They created a new incentive program. It was a long and painful process, but it worked. The team finally started using the new tool, and the results were incredible. Customer satisfaction went up, costs went down, and the support agents were able to focus on more strategic work.
This is the reality of AI transformation. It’s not about flipping a switch. It’s about changing the way people work. And that’s a lot harder than just writing a check for a new piece of software. It requires a thoughtful and deliberate approach to change management. You need to communicate the vision, you need to provide training and support, and you need to create a culture where people are willing to experiment and learn. It's about making people feel safe and empowered, not threatened and replaced.
Another key aspect of this is to involve your team in the process from the very beginning. Don't just spring a new AI tool on them and expect them to be happy about it. Get their feedback, understand their concerns, and make them feel like they are part of the solution. When people feel like they have a stake in the outcome, they are much more likely to embrace change. I've seen this work time and time again. The companies that are most successful with AI are the ones that treat their employees like partners, not cogs in a machine.
3. Get Ready to Manage Hybrid Human-AI Teams
The future of work isn’t about AI replacing humans. It’s about humans and AI working together. And that’s going to require a whole new set of leadership skills.
Think about it. How do you manage a team that’s made up of both humans and AI? How do you motivate them? How do you measure their performance? These are the questions that leaders need to be thinking about right now.
I’m already starting to see this in my own work. I use AI to help me with everything from scheduling meetings to analyzing investment opportunities. It’s like having a team of super-smart assistants who are available 24/7. But I’m still the one who has to make the final decisions. I’m the one who has to set the strategy. I’m the one who has to be the leader.
The leaders who will succeed in the age of AI are the ones who can embrace this new reality. They’re the ones who can build teams that are more than the sum of their parts. They’re the ones who can create a culture of collaboration and trust between humans and AI.
This means that leaders need to be able to identify the strengths and weaknesses of both humans and AI, and then design workflows that play to those strengths. For example, AI is great at processing vast amounts of data and identifying patterns, but it's not so great at creative problem-solving or building relationships. That's where humans come in. The best leaders will be able to create a seamless integration between the two, so that the whole is greater than the sum of its parts.
I've been experimenting with this in one of my own companies. We have a team of data scientists who work alongside an AI platform that we developed in-house. The AI does the heavy lifting of crunching the numbers and identifying potential investment targets. But it's the data scientists who make the final call. They use their intuition and experience to vet the AI's recommendations and then present their findings to me. It's a beautiful symbiosis of human and machine intelligence, and it's already paying off in a big way.
The Real Bottom Line
Look, the AI hype isn’t going away. If anything, it’s only going to get more intense. But the companies that will win in the long run are the ones that can look beyond the hype and focus on what really matters: leadership.
It’s not about having the fanciest algorithm or the biggest dataset. It’s about having the right people in the right roles, with the right skills and the right mindset. It’s about building a culture that embraces change and is constantly learning and adapting.
So, as you’re thinking about your AI strategy, don’t just think about the technology. Think about the people. Think about the leadership. That’s what will ultimately determine your success or failure in the age of AI. The future is not about man versus machine. It's about man with machine. And the leaders who understand that are the ones who will build the next generation of great companies. The ones who don't will be left behind. It's as simple as that.
Frequently Asked Questions
Are these recommendations still relevant in 2026?
Absolutely. While specific tools and tactics change, the underlying principles remain consistent. I update my thinking regularly based on what I'm seeing in the market and across my portfolio companies.
Can I implement all of these at once?
I'd strongly recommend against it. Pick the 2-3 items that resonate most with your current situation and focus there. Trying to do everything simultaneously is a recipe for doing nothing well.
Which item on this list has the highest impact?
It depends on your stage and context, but in my experience, the items near the top of the list tend to have the broadest applicability. That said, sometimes the less obvious items create the biggest breakthroughs for specific situations.
How do I know which items apply to my situation?
Start by honestly assessing where your biggest bottleneck is right now. The items that address that specific constraint will give you the highest return on your time and energy.