AI & Tech
43 Hard Truths About AI No One Wants to Admit
Everyone’s posting wins. Nobody’s posting what’s actually happening. In the last six months, we’ve been deep in it, building, selling, deploying, cleaning up the mess that follows, and celebrating the wins.
AI isn’t broken. The way companies approach it is. Below are 40 truths from the trenches, the lessons, frustrations, and realities that separate hype from progress.
By Gabe Larsen
November 4, 2025
The Illusion of Progress
- Nobody has this figured out. Not even the loud ones. Anyone claiming mastery is either lying or selling you something.
- Everyone’s been burned once. Your first AI project isn’t a win, it’s a lesson you pay for.
- Buyers don’t understand AI pricing. Vendors barely do either. Everyone’s still guessing what “intelligence” is worth.
- Most projects fail because teams try to do too much, too fast. If you skip crawl and walk, AI will expose every weakness in your run.
- “Where do we start?” is still the most common question. Strategy isn’t the issue. Knowing what the hell you’re doing is.
- Boards and CEOs are demanding AI without knowing what they’re asking for. They don’t want a plan. They want a headline. Though some are finally waking up.
- Most “AI projects” are automation with lipstick. There’s no intelligence, just SaaS with better marketing.
- Productivity’s a nice start. The real wins are cost and growth. Efficiency is nice but results are better.
- Real AI wins are showing up in customer service, sales dev, recruiting, and engineering. Functions with repeatable inputs and measurable outputs.
- Everyone thinks they can build AI themselves, until they try. Then the honeymoon ends: bad data, brittle APIs, and models that age like milk.
The Vendor Mirage
- Every vendor says they’re not ChatGPT with a wrapper. They’re absolutely another ChatGPT wrapper.
- Building a basic agent is easy. Building a complex agent is hard. The first impresses your friends, the next one humbles you.
- Security reviews are brutal, and they should be. AI pokes holes in everything you thought was locked down.
- Crawl, walk, run always beats sprint and burn. Velocity without direction is just noise.
- New AI roles are emerging to manage, prompt, and optimize AI teammates. We’re all quietly hiring translators between humans and machines.
- People aren’t saying “AI tools” anymore. They’re saying “AI teammates.” Software is evolving into labor. That shift changes everything.
- If a vendor says they’re “working with” a big logo… Assume one person there downloaded a trial until proven otherwise.
- There’s a massive gap between AI-first companies and AI-add-on companies. One redefines work. The other adds a button.
- A 90-day pilot isn’t a customer. It’s a test. Until someone signs a contract, it’s still a science project.
- Only believe 10% of what you read on LinkedIn. Everything else has been filtered, fluffed, or flat-out invented.
The Human Problem
- N8N and Make are fun until enterprise reality hits. What works for a solopreneur collapses under complexity and compliance.
- AI multiplies whatever environment you drop it into. Brilliance scales. Chaos explodes.
- Leaders lead through it. Tourists wait for vendors to fix it. You can’t outsource ownership.
- People are scared, and they should be. No one wants to admit how much of this still feels like guessing.
- Half your team’s terrified. The other half’s obsessed. Culture’s split, and no one’s aligned.
- Everyone’s pretending their AI results are better than they are. Half the “wins” are vaporware; the rest are interns with spreadsheets.
- Teams are fighting back harder than you think. This isn’t just a tech problem, it’s a change management one.
- AI doesn’t break companies. It just shows what’s already broken. Bad data, lazy processes, and fake productivity don’t hide anymore.
- People expect perfection from AI but tolerate chaos from themselves. That’s why most projects never leave testing.
- Most “AI strategies” are PowerPoint decks. Real ones live in roadmaps, not slides.
The Reality Check
- “We’re experimenting” is usually code for “we’re lost.” Experimentation is good. Directionless dabbling isn’t.
- The Shadow AI Problem. While leadership debates strategy, half the company’s using ChatGPT behind IT’s back.
- Integration is where a lot of AI projects die. It’s not the model that fails, it’s the plumbing.
- One hallucinated email on customer data can set a program back six months. Trust takes months to build, seconds to lose.
- Most execs still treat AI like a press release, not a rebuild. AI isn’t a side project, it’s a system shift.
- Every company is one headline away from banning AI again. Fear still outruns innovation.
- Politics kill more AI projects than accuracy ever will. The org chart moves slower than the model.
- The best AI teams are small, technical, and slightly rebellious. They don’t ask for permission, they build proof.
- The people who get it aren’t talking. They’re too busy deploying agents that actually work.
The Lessons Everyone Learns Too Late
- The Measurement Mirage. No one agrees on what success looks like. They measure “adoption” in logins, not outcomes.
- The Procurement Black Hole. Legal and compliance don’t know what to do with AI. So they stall. By the time contracts are signed, the competition’s moved on.
- Nobody’s training their people fast enough. Everyone’s using AI. But most companies are not providing any support.
- The Maintenance Trap. Launching AI is easy. Keeping it alive is where the bodies pile up.
AI’s messy. It’s hard. It’s humbling. But it’s also progress and every failure teaches faster than waiting on the sidelines.
You don’t have to get it perfect. You just have to get started. And if you’re smart, you’ll learn from the ones who already took the hits.