Last year, I made a bet that changed how I think about why your 'chief ai officer' is probably a waste of money. Here's what happened.
Hot take: hiring a Chief AI Officer is the biggest mistake most companies are making right now. I'll explain why this role is often a symptom of a deeper problem and what you should be doing instead.
What I've Learned From 46 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with why your 'chief ai officer' is probably a waste of money.
The biggest misconception is that you need to timing is everything in this game. That's backwards. The companies that win are the ones that customer feedback is the only metric that matters.
I remember sitting with the Anthropic team early on and discussing how they thought about why your 'chief ai officer' is probably a waste of money. Their approach was counterintuitive but brilliant.
Why Most Approaches Fail
Let me be direct: about 70% of the approaches I see to why your 'chief ai officer' is probably a waste of money are fundamentally flawed. Not slightly off. Fundamentally flawed.
The root cause is usually one of three things:
- Copying what big companies do without understanding why they do it. What works for Google doesn't work for a 10-person startup.
- Over-engineering the solution when a simple approach would work better. I've seen teams spend six months building something that could have been done in two weeks.
- Ignoring the human element. Technology is the easy part. Getting people to actually use it is where the real challenge lives.
Real Talk: What Actually Matters
I'm going to cut through the noise and tell you what actually matters when it comes to why your 'chief ai officer' is probably a waste of money.
First, execution speed beats perfection. Every time. I've never seen a company fail because they moved too fast on why your 'chief ai officer' is probably a waste of money. 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 why your 'chief ai officer' is probably a waste of money strategy in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around AI change management, chief AI officer, AI leadership skills, AI transformation leadership that I've been thinking about a lot lately.
The Bottom Line
Look, why your 'chief ai officer' is probably a waste of money isn't rocket science. But it does require intentionality, consistency, and a willingness to learn from mistakes.
If you take one thing from this article, let it be this: start now, start small, and iterate. The founders who win at why your 'chief ai officer' is probably a waste of money aren't the ones with the best strategy on paper. They're the ones who execute, learn, and adapt faster than everyone else.
I've been doing this for over a decade. The patterns are clear. The companies that take why your 'chief ai officer' is probably a waste of money seriously outperform the ones that don't. Every single time.
If you're working on something interesting in this space, I'd love to hear about it. Drop me a line.
Frequently Asked Questions
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.
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.