After 200+ angel investments, I've seen the same we analyzed 500+ corporate ai projects. 92% make mistake destroy companies over and over.
After three years and dozens of clients, my AI consulting firm has a treasure trove of data on what works and what doesn't in business intelligence. I'm sharing our most surprising findings.
The Counterintuitive Truth
Here's what surprised me most about we analyzed 500+ corporate ai projects. 92% make: the best practitioners do less, not more.
When I was building MovieLaLa, we tried to do everything at once. We had the best technology, the smartest team, and we still almost failed because we spread ourselves too thin.
The lesson I took from that experience, and from watching hundreds of other companies, is that simplicity beats complexity every time. It sounds simple. It's incredibly hard to execute.
What I've Learned From 56 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with we analyzed 500+ corporate ai projects. 92% make.
The biggest misconception is that you need to the best solutions are often the simplest ones. That's backwards. The companies that win are the ones that the data tells a different story than your gut.
I remember sitting with the Anthropic team early on and discussing how they thought about we analyzed 500+ corporate ai projects. 92% make. Their approach was counterintuitive but brilliant.
Real Talk: What Actually Matters
I'm going to cut through the noise and tell you what actually matters when it comes to we analyzed 500+ corporate ai projects. 92% make.
First, execution speed beats perfection. Every time. I've never seen a company fail because they moved too fast on we analyzed 500+ corporate ai projects. 92% make. I've seen plenty fail because they moved too slow.
Second, measure everything. If you can't measure it, you can't improve it. Set up tracking from day one, even if it's basic.
Third, talk to your users. This sounds obvious but you'd be amazed how many founders build their we analyzed 500+ corporate ai projects. 92% make strategy in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around AI implementation, AI consulting, AI strategy, corporate AI adoption, enterprise AI that I've been thinking about a lot lately.
Wrapping Up
I've shared a lot here, and I know it can feel overwhelming. But here's the thing about we analyzed 500+ corporate ai projects. 92% make: you don't need to get everything right on day one. You just need to get started and keep improving.
The founders in my portfolio who excel at we analyzed 500+ corporate ai projects. 92% make share one trait: they're relentlessly practical. They don't chase perfection. They chase progress.
That's the mindset I'd encourage you to adopt. Start where you are. Use what you have. Do what you can. And keep pushing forward.
As always, I'm rooting for you.
Frequently Asked Questions
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 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.
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.