I’ve seen it a dozen times. A founder gets excited about a new AI tool, maybe something they saw on Twitter or a shiny new app that promises to 10x their team's productivity. They buy it, mandate its use, and a few months later, it’s shelf-ware. No one is using it, and the team is back to their old workflows, only now they’re a little more cynical. The founder is left scratching their head, wondering why their big AI bet fell flat.
Sound familiar? You’re not alone. A recent study hit my desk that confirmed what I’ve been seeing for years in the trenches: a staggering 71% of companies are failing to build a real, impactful AI culture. They’re spending money, sure. But they’re not getting results.
Having managed over $7 million in remote team payroll at RemoteTeam before we were acquired by Gusto, and having invested in over 200 startups, including foundational AI companies like Anthropic and Scale AI, I’ve had a front-row seat to this drama. I’ve seen the spectacular failures and the quiet, runaway successes. The difference between the two almost never comes down to the technology. It comes down to the culture.
The Billion-Dollar Cargo Cult
Too many companies treat AI like a cargo cult. They see successful companies using AI and try to mimic the rituals without understanding the underlying principles. They buy the expensive tools, they hire the data scientists, they talk about "leveraging synergies," and they expect the magic to just happen. It doesn’t work that way.
I remember back in the early days of MovieLaLa, my second company, we were obsessed with recommendation algorithms. We thought if we could just build a smarter algorithm than Netflix, we’d win. We spent months and a significant chunk of our seed funding trying to build the perfect system. But we made a classic mistake: we never stopped to ask our users what they actually wanted. We were so focused on the technical solution that we forgot about the human problem. The project was a failure, but it taught me a lesson I’ve carried with me ever since: technology is a tool, not a destination.
This is the first and biggest mistake I see companies making. They fall in love with the solution, not the problem. They get so wrapped up in the hype of generative AI, large language models, and autonomous agents that they forget to ask the most important question: What problem are we actually trying to solve?
Your Team Doesn't Need More Tools
Think about your team. Are they asking for more software? Probably not. They’re drowning in it. The last thing they need is another login to remember and another dashboard to check. When you force a new AI tool on them from the top down, you’re not empowering them. You’re just adding another item to their to-do list.
I once advised a startup that had spent a fortune on a sophisticated AI-powered project management tool. The CEO was convinced it would revolutionize their workflow. Six months later, adoption was near zero. Why? The team was perfectly happy with their existing system of shared documents and weekly check-ins. The new tool, for all its fancy features, solved a problem they didn’t have. It was a solution in search of a problem.
This is why top-down mandates for specific tools almost always fail. Real, lasting change comes from the bottom up. It comes from empowering your team to find their own solutions to their own problems.
The One Thing Successful Companies Get Right
So, what’s the secret? I analyzed four successful remote companies I’ve invested in that are absolutely crushing it with AI. They’re not just using it; they’re integrating it into the very fabric of their operations. And they all had one thing in common.
It wasn’t the tools they used. It wasn’t the size of their budget. It wasn’t even the industry they were in.
It was a culture of psychological safety.
It’s the freedom to experiment, the freedom to be wrong, and the freedom to fail without fear of punishment. When you give your team that freedom, they will find ways to use AI that you never could have imagined. They’ll find the small, tedious parts of their jobs and automate them. They’ll discover new ways to delight your customers. They’ll build a real, organic AI culture from the ground up.
How to Build a Real AI Culture: A 3-Step Playbook
This isn’t just theory. This is a practical, actionable playbook that I’ve used to help my portfolio companies build thriving AI cultures. It’s not about buying more software. It’s about changing the way you think.
1. Start with a Problem, Not a Tool
Instead of asking "How can we use AI?", ask "What is the most tedious, repetitive, soul-crushing part of our workflow?" Get your team together and brainstorm. Make a list. I guarantee you’ll be surprised by what you find.
At RemoteTeam, we discovered that our onboarding process for new hires was a huge time sink. It involved a lot of manual data entry, repetitive questions, and a whole lot of paperwork. It was a perfect candidate for AI. We didn’t start by looking for an "AI onboarding tool." We started with the problem. We ended up building a simple chatbot that could answer new hires’ most common questions, guide them through the paperwork, and free up our HR team to focus on the human side of onboarding. It was a huge win, and it came from focusing on the problem, not the technology.
2. Create "AI Champions"
In every organization, there are people who are naturally curious and excited about new technology. Find those people. They are your "AI Champions." Give them a small budget and the freedom to experiment. Let them play with new tools. Let them try to solve the problems you identified in step one.
Don’t tell them what to do. Let them figure it out. They might fail. That’s okay. The goal is not to find the perfect solution on the first try. The goal is to learn. When they find something that works, they will become your internal evangelists. They’ll show their colleagues how to use the new tool. They’ll create a grassroots movement that is far more powerful than any top-down mandate.
3. Measure the Impact, Not the Adoption
Finally, you need to change the way you measure success. Don’t track vanity metrics like "AI adoption" or "number of users." Who cares? The only thing that matters is whether you solved the problem.
Did you reduce the time it takes to onboard a new hire? Did you increase customer satisfaction? Did you free up your team to do more creative, high-impact work? Those are the metrics that matter. Focus on them, and you’ll know whether your AI strategy is actually working.
Stop Chasing the Hype
Look, AI is not a magic wand. It’s not going to solve all your problems. But it is the most powerful tool we’ve had in a generation to augment human ingenuity. The companies that win in the next decade will be the ones that figure out how to build a culture that embraces it.
Stop chasing the hype. Stop buying tools you don’t need. Stop trying to force change from the top down. Instead, focus on your people. Give them the freedom to experiment. Empower them to solve their own problems. If you can do that, you won’t have to worry about being in the 71%. You’ll be leading the charge.
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 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.