Having lived through the dot-com bust, the mobile revolution, and now the AI explosion, I've learned to see around corners. The current AI regulation is just the beginning. I'm sharing my 3 bold predictions for the 2027 regulatory landscape and how to prepare now.
The Reality Nobody Talks About
A lot of the advice on AI regulation rests on assumptions that made sense five years ago. The world has moved on.
The first thing to understand is that the market doesn't care about your roadmap. I've seen this play out across dozens of companies. The pattern is unmistakable.
Many teams spend months on the wrong path before realizing that timing is everything in this game. Once they make the switch, everything changes.
What I've Learned From 30 Companies
Across 234 angel investments, including Anthropic, a few patterns in AI regulation come up again and again.
The founders who handle AI regulation well understand that timing is everything in this game.
The Framework That Actually Works
Here is a simple framework for evaluating AI regulation. It's not complicated, but it requires discipline.
Step 1: timing is everything in this game
This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: the data tells a different story than your gut
Once you have the foundation right, this becomes much easier. I've watched founders struggle with this for months when the answer was staring them in the face.
Step 3: Iterate relentlessly
Nothing works perfectly the first time. The companies that get AI regulation right treat it as an ongoing process, not a one-time project.
What I Tell Founders
Before deciding anything about AI regulation, start with three questions:
What's your timeline? Because the right approach for a company with 6 months of runway is very different from one with 3 years.
What have you already tried? Most founders have tried something. Understanding what didn't work is often more valuable than knowing what might.
Who on your team owns this? If the answer is "everyone" or "no one," that's your first problem to solve.
These questions seem simple but they reveal a lot about where a company actually stands.
This connects to broader themes around responsible AI, AI alignment, AI governance that I've been thinking about a lot lately.
Final Thoughts
There are no shortcuts in AI regulation, but there are smarter paths.
The strongest teams treat AI regulation as a competitive advantage, not a checkbox. They invest in it early, measure it obsessively, and never stop improving.
If you're just getting started with AI regulation, don't be intimidated. Everyone starts somewhere. The key is to start with the right mindset and the right framework, and then execute like your company depends on it. Because it probably does.
Frequently Asked Questions
Q: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.
Q: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.
Q: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.
Q: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.