I’m going to say something that might get me in trouble with some of my friends in Silicon Valley. Most of what we call “AI leadership” today is a joke. It’s a mix of buzzword bingo, chasing hype cycles, and frankly, a lot of pretending. People are slapping “AI” on their LinkedIn profiles and company mission statements without a real clue of what’s coming.
I’ve been lucky enough to have a front-row seat to this revolution. I’ve built and sold two companies, one of which, RemoteTeam, was acquired by Gusto. I’ve invested in over 200 startups, including some of the foundational companies of this new AI era like Anthropic, OpenAI, Scale AI, and Hugging Face. I’ve talked to hundreds of founders, investors, and executives. And I can tell you this: the leaders who will win in the next five years are not the ones who can recite the latest transformer architecture. They are the ones who understand that AI is not just a technology, but a fundamental shift in how we work, create, and lead.
So, what’s actually going to matter? I’ve boiled it down to three trends that I’m betting on. These are the shifts I’m looking for in the founders I back and the advice I give to the CEOs I mentor. If you want to be a leader in the age of AI, this is what you need to know.
1. The Death of the “AI Expert” Leader
For the last few years, there’s been a huge premium on leaders who have a deep technical background in AI. The thinking was that to lead an AI company, you needed to be an AI expert. You needed a PhD in machine learning or a background in a FAANG research lab. And to be fair, in the early days, that was probably true. When the technology was still nascent and the biggest challenge was just getting the models to work, you needed that deep technical expertise.
But that era is over. The foundational models are now so powerful and so accessible that you don’t need to be a world-class researcher to build a world-class AI product. In fact, I’d argue that being too deep in the technical weeds can actually be a disadvantage. You can get lost in the complexities of the technology and lose sight of the most important thing: the customer.
I remember meeting a founder a few years ago who was building an AI-powered tool for lawyers. He had a PhD in natural language processing and could talk for hours about the intricacies of his model. But when I asked him who his customer was and what problem he was solving for them, he couldn’t give me a clear answer. He was so in love with the technology that he had forgotten about the user. I passed on the investment.
A few months later, I met another founder who was tackling the same problem. She had no formal AI background. She was a lawyer who had experienced the pain of legal research firsthand. She had taught herself enough about AI to know what was possible, and she had partnered with a strong technical co-founder. But her focus was always on the customer. She was obsessed with building a product that would make lawyers’ lives easier. I invested in her company, and it’s now one of the fastest-growing startups in my portfolio.
The new AI leader is not an AI expert. They are a learning expert. They are insatiably curious, they ask great questions, and they are not afraid to say “I don’t know.” They know that in a field that is moving as fast as AI, the most important skill is the ability to learn and adapt. They focus on building a team of A-players and then empowering them to do their best work. They are translators, connectors, and visionaries. They can bridge the gap between the technical and the practical, between the lab and the market.
So, if you’re a leader who is feeling intimidated by AI, don’t be. You don’t need to go back to school and get a PhD. You just need to stay curious, keep learning, and focus on what really matters: solving real problems for real people.
2. The Rise of the “Human-in-the-Loop” Manager
There’s a common misconception that AI is going to automate everything and that managers will become obsolete. The reality is much more nuanced. AI is not replacing managers; it’s changing the nature of management. The old model of top-down, command-and-control leadership is dead. The new model is all about collaboration, coaching, and co-creation with AI.
I call this the “human-in-the-loop” management style. It’s about understanding that AI is not a magic box that you can just plug in and forget about. It’s a powerful tool that needs to be guided, trained, and managed. And the best managers will be the ones who can do this effectively.
At RemoteTeam, we built a platform to help companies manage their remote teams. We used AI to automate a lot of the administrative tasks that managers hate, like tracking time off, running payroll, and managing compliance. But we quickly realized that you can’t automate the human element of management. You can’t automate empathy, trust, or psychological safety.
So, we designed our product to be a co-pilot for managers, not a replacement. Our AI would surface insights and recommendations, but it was always up to the manager to make the final decision. For example, our tool might flag that an employee was at risk of burnout based on their work patterns. But it wouldn’t automatically intervene. It would present the information to the manager and suggest a few conversation starters. It was then up to the manager to have a real, human conversation with the employee.
This is the future of management. It’s not about managing people or projects; it’s about managing the interface between people and AI. It’s about designing systems and processes that bring out the best in both. It’s about knowing when to trust the AI and when to trust your gut. It’s about being a coach and a mentor, not a micromanager.
This requires a whole new set of skills. Managers need to be data-literate, but they also need to be emotionally intelligent. They need to be able to think systematically, but they also need to be able to think creatively. They need to be comfortable with ambiguity and uncertainty. And most importantly, they need to be deeply human.
3. From “Growth at all Costs” to “Responsible Scaling”
For the past decade, the mantra in Silicon Valley has been “growth at all costs.” The goal was to get as big as possible, as fast as possible, and worry about the consequences later. That mindset led to some incredible innovations, but it also led to some serious problems: misinformation, polarization, and a general erosion of trust in technology.
With AI, the stakes are even higher. We are building systems that have the potential to reshape society in profound ways. And we have a responsibility to do it right. The “move fast and break things” approach is not going to work anymore. The leaders who will succeed in the next era of AI will be the ones who can balance innovation with responsibility, speed with safety, and growth with ethics.
This is not just about avoiding bad PR or regulatory fines. It’s about building a sustainable and equitable future. It’s about ensuring that the benefits of AI are shared by everyone, not just a privileged few. And it’s about being proactive, not reactive, when it comes to the potential risks of AI.
I’m an investor in Anthropic, one of the leading AI safety research companies. They are pioneering a technique called “Constitutional AI,” which is a way of training AI models to align with a set of ethical principles. It’s a fascinating approach, and I think it’s a sign of what’s to come. The best AI companies will have a strong ethical compass built into their DNA.
This doesn’t mean that we should stop innovating or taking risks. But it does mean that we need to be more thoughtful and intentional about the way we build and deploy AI. We need to ask ourselves not just “can we build it?” but “should we build it?” And we need to have a clear answer for who is responsible when things go wrong.
This is a huge challenge, but it’s also a huge opportunity. The leaders who can figure out how to scale responsibly will not only build great companies, but they will also earn the trust of their customers, their employees, and society as a whole. And in the long run, that’s the only way to win.
The Road Ahead
I’m more excited about the future of AI than I’ve ever been. We are on the cusp of a new era of innovation and progress. But it’s not going to be easy. The path ahead is full of uncertainty and complexity. And the leaders who will guide us through it will need a new set of skills, a new mindset, and a new moral compass.
They will be learners, not experts. They will be coaches, not commanders. And they will be responsible stewards, not reckless cowboys. They will be the ones who can build not just great products, but great companies. And they will be the ones who will shape the future of AI for the better.
Are you ready to be one of them?
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.
What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
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.
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.