95% of Companies Are Failing at Implementing Generative AI — and I Understand Why
Decades of digital transformation should have taught us. But the same mistake repeats: companies spend millions on AI without nailing the basics — processes, culture, and data.
Fradev / October 16, 2025
Abstract representation of companies trying to implement AI without a solid foundation
95% of Companies Are Failing at Implementing Generative AI
I read yesterday: 95% of companies are failing at implementing generative AI.
Ninety-five percent.
Something is very wrong.
I’ve worked in technology since 2020 — the last three years focused on applied artificial intelligence projects.
And if there’s one thing I’ve learned, it’s simple:
👉 The problem is never the technology.
The Replay of Digital Transformation 🎞️
What’s happening now is the same movie as digital transformation.
Companies are spending hundreds of millions with the same consulting firms, selling the same pitch, just swapping in the new buzzword.
The result?
Systems that don’t integrate, non-existent datalakes, disconnected APIs, broken processes, and a lot of slick PowerPoint.
The difference is, now the slide says “AI”.
And worse: the same directors and VPs keep hiring the same companies, for the same reasons — status, comfort zone, and maybe... that shared boat in Angra.
The Root Error: Automating Chaos ⚙️
What really bothers me is seeing companies trying to automate with AI processes that don’t even work manually.
“Automating what doesn’t work is scaling disaster.”
Before thinking about agents, copilots, or proprietary LLMs, there should be at least a minimum level of operational maturity.
Without it, AI just multiplies the noise.
Steak and Potatoes > Stage Futurism 🍛
Do you know what actually drives results?
Well-structured processes, reliable data, and disciplined execution.
The companies that get this will scale with AI.
Those that keep buying PowerPoint will become failure case studies in the next Gartner reports.
Conclusion
The truth is harsh, but necessary:
AI does not fix bad management.
It amplifies.
It amplifies the efficiency of those who know what they’re doing.
And it amplifies the chaos of those who still haven’t mastered the basics.
The good news?
There’s still time to get it right.
But the first step is to stop buying pitches — and start executing.
“Automating what doesn’t work is scaling disaster.”
That’s the phrase every company should stick on the wall before starting any AI project.
