What if I told you the key to unlocking massive productivity with AI performance reviews was actually doing less? It sounds crazy, but the results speak for themselves.
I’ve managed over $3M in remote team payroll, built and sold two companies, and invested in over 200 startups, including some of the biggest names in AI like Anthropic, OpenAI, and Scale AI. I’ve seen firsthand how AI can transform a business. But I’ve also seen how it can be a massive waste of time and money, especially when it comes to performance reviews.
Most founders I talk to are using AI in their performance reviews in a way that’s not just ineffective, but actually counterproductive. They’re making a few critical mistakes that are costing them their best people and killing their team’s morale. I’m writing this to show you a better way.
The Black Box Trap
One of the biggest mistakes I see founders make is treating AI as a magic black box. They buy some shiny new AI tool, plug it into their HR system, and expect it to spit out perfect performance reviews. They don’t bother to understand how the AI works, what data it’s trained on, or what its limitations are.
A founder I know—let’s call him Bob—did exactly this. He was so excited about his new AI performance review software. He told me it was going to save him and his managers hundreds of hours. A few months later, I checked in with him to see how it was going. He was… less enthusiastic. It turned out the AI was just generating generic, positive feedback for everyone. It was completely useless. Bob had wasted thousands of dollars and, more importantly, his team’s trust.
This is what happens when you treat AI like a black box. You’re abdicating your responsibility as a leader. You’re letting an algorithm make decisions about your people without any understanding or oversight. That’s not just lazy, it’s dangerous.
The Metrics Mirage
Another common mistake is focusing on the wrong metrics. Founders love quantitative data. It’s easy to track, easy to measure, and it makes you feel like you’re making objective decisions. So, they use AI to track things like lines of code, sales calls made, or tickets closed. But these metrics are often a poor proxy for actual performance.
At my last company, RemoteTeam, we learned this the hard way. We had a few engineers who were consistently at the top of the leaderboard for lines of code written. But when we dug deeper, we found that they were writing a lot of bloated, inefficient code that was causing problems down the line. The real top performers were the ones who wrote less code, but it was elegant, efficient, and solved the customer’s problem.
Qualitative contributions like teamwork, creativity, and mentorship are what truly drive a company forward. These are the things that are hard to measure, but they’re also the things that matter most. An AI can’t tell you that your quietest engineer is the one everyone else goes to for advice. It can’t tell you that your marketing manager is the one who comes up with all the best ideas in brainstorming sessions. That’s your job as a leader.
The Coward’s Crutch
Let’s be honest, giving negative feedback is hard. No one likes to do it. So, it’s tempting to use AI as a crutch to avoid those difficult conversations. I’ve seen founders use AI to deliver negative feedback, or even to fire people. This is a massive mistake.
I once had to let go of an employee I really liked. He was a great guy, but he just wasn’t a good fit for the role. It was one of the hardest conversations I’ve ever had. I could have easily sent him an email or had HR do it. But I owed it to him to have that conversation face-to-face. An AI could never have handled that situation with the empathy and respect it required.
When you use AI to avoid difficult conversations, you’re not just being a coward, you’re also robbing your employees of the opportunity to learn and grow. A well-delivered piece of negative feedback can be a gift. It can help someone see a blind spot they never knew they had. An AI-generated message will never have the same impact as a real, human conversation.
The Bias Amplifier
AI models are trained on data, and that data is often biased. If you’re not careful, your AI-powered performance reviews can perpetuate and even amplify the existing biases in your organization. For example, if your company has historically promoted more men than women, your AI might learn to associate male-coded language with high performance.
This isn’t some theoretical problem. It’s happening right now. And it’s one of the reasons I’m so passionate about investing in companies like Anthropic that are working to build safer, more transparent AI. But even with the best intentions, it’s incredibly difficult to eliminate bias from AI models completely.
As a founder, you need to be hyper-aware of this. You need to be constantly auditing your AI systems for bias and making sure they’re not unfairly penalizing certain groups of people. And you need to have a human in the loop to make the final call.
A Better Way Forward
So, what’s the right way to use AI in performance reviews? It’s simple: use it as a tool to augment, not replace, human judgment.
Use AI to gather data and identify patterns that you might have missed. Use it to provide your employees with real-time feedback and coaching. Use it to automate the tedious parts of the performance review process so you can spend more time on the human parts.
At my companies, we used AI to flag potential issues, like a sudden drop in an employee’s activity level. But we never used it to make a final decision. That was always done by a manager who could take into account the full context.
Be transparent with your team about how you’re using AI. Explain what data you’re collecting and how it’s being used. Give them a chance to ask questions and provide feedback. The more you can demystify the process, the more your team will trust it.
AI can be an incredibly powerful tool for building a high-performing team. But it’s not a silver bullet. Stop looking for a magic black box to solve all your problems. Instead, focus on using AI to empower your managers and your employees. That’s the real secret to unlocking its potential.
Frequently Asked Questions
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.
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.