I’ve probably sat in a hundred board meetings in the last year where the words “AI strategy” were uttered. And in ninety of them, the conversation was complete nonsense.
Everyone is scrambling to appoint a “Chief AI Officer” or launch some massive “AI transformation” initiative. It feels like the early days of the internet all over again, where companies were spending millions on websites with no real plan. Lots of motion, not a lot of progress.
After two exits and investing in over 200 companies, including some of the foundational players in the AI space like Anthropic and OpenAI, I’ve developed a pretty good filter for the hype. I see a few fundamental shifts coming in how we lead our companies in the age of AI. Most people aren’t ready for them.
Here are my top three predictions for what AI leadership will actually look like in 2027, once the dust settles.
1. The “Chief AI Officer” role will be a punchline.
This might be a hot take, but I’m seeing it already. Companies are rushing to hire a Chief AI Officer, thinking one executive can sprinkle some AI magic on the business and call it a day. It’s a vanity hire. It’s a sign that the CEO doesn’t understand how AI actually creates value.
I was talking to the founder of a Series B company in my portfolio a few months back. His investors were pressuring him to hire a big-name CAIO. I told him to hold off. Instead, I pushed him to identify the top three problems in his business that AI could realistically solve in the next 12 months. Not vague goals like “improve efficiency,” but specific, measurable problems.
He came back with: “Our customer support team is underwater, and it’s killing our retention. We have a ton of unstructured data from user feedback that we do nothing with. And our sales team spends half their time on manual data entry.”
Great. Now, who in your organization is best equipped to solve those problems? It wasn’t a single executive. It was a product manager on the customer success team, a data scientist who had been begging for a project like this, and a sales ops leader who knew the CRM inside and out.
We empowered them. We gave them a budget, a small team of engineers, and the mandate to ship a solution in 90 days. The results were incredible. They built a simple AI-powered chatbot that handled 40% of support tickets. They used an off-the-shelf model to analyze user feedback and surface the top 5 feature requests every week. They automated most of the sales data entry.
Did they need a Chief AI Officer to do that? Absolutely not. True AI leadership isn’t about a title. It’s about deeply understanding the business and empowering the people closest to the problems to use these new tools. By 2027, the companies that get this right will have AI capabilities distributed throughout their organization, not siloed in one department.
2. Your AI transformation will fail without real change management.
When Gusto acquired my last company, RemoteTeam, we had a product that was working well. But integrating it into a much larger organization was a massive challenge. It wasn’t a technical problem. It was a people problem.
Engineers were used to their old workflows. The sales team had their own way of doing things. We had to spend months doing the hard work of change management: listening to concerns, running training sessions, and showing people how the new tools would make their lives better. It was a slog.
Now, multiply that by a thousand, and you have the challenge of AI adoption. You can’t just drop a new AI tool on your team and expect them to use it. People are scared. They’re worried about their jobs. They’re skeptical of new technology.
I see so many companies making this mistake. They buy a fancy new AI platform, send out a memo, and then wonder why nobody is using it six months later. It’s because they ignored the human element.
Real AI transformation is a change management problem first, and a technology problem second. It requires a massive investment in training and communication. It requires empathy and a deep understanding of your team’s fears and motivations.
By 2027, the successful AI leaders will be the ones who are masters of change management. They’ll be the ones who can bring their people along on the journey, not just impose new technology from on high. They will have a clear answer to “what’s in it for me?” for every single person in the company.
3. The most valuable AI leaders will be product-focused engineers.
If you look at the companies that are truly pushing the boundaries of AI – OpenAI, Anthropic, Scale AI, Hugging Face – they are all led by technical founders. They are engineers and product people at their core.
This is not a coincidence. In the age of AI, the product is the technology, and the technology is the product. You can’t separate them. The leaders who will build the next generation of great companies will be the ones who can think in terms of systems, models, and data.
I’m not saying you need to be a PhD in machine learning to be a successful leader. But you do need to have a deep intuition for how these systems work. You need to be able to have a credible conversation with your engineering team. You need to be able to spot a technical limitation from a mile away.
I’m seeing a huge gap in the market for this kind of talent. There are plenty of great managers and plenty of brilliant engineers. But there are very few people who can do both. The ones who can are going to be incredibly valuable in the coming years.
My advice to anyone who wants to be a leader in the AI era is simple: get your hands dirty. Build something. Learn to code. Spend time with your engineering team. Don’t just read about AI in a magazine. Go to the source.
The Road Ahead
So, what does this all mean for you? It means that the old playbook for leadership is being thrown out the window. The skills that made you successful in the past might not be the ones that make you successful in the future.
Forget the fancy titles and the grand pronouncements. The future of AI leadership is about being deeply embedded in the business, empowering your people, and having a real, hands-on understanding of the technology.
It’s not going to be easy. But for those who are willing to adapt, the opportunity is immense. The next decade will be defined by the leaders who can navigate this new landscape. I, for one, am excited to see what they build.
Frequently Asked Questions
Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.
How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.
What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.