Let’s take a look at three big ones out there right now, and what’s actually going on underneath each.
Myth: AI is about to replace all workers
OpenAI’s Sam Altman spent much of 2025 warning that AI would “probably replace most of the jobs people do today,” with entire job categories going “totally, totally gone.”
That’s pretty grim news, but is it true?
Well, telling the world your product is about to reinvent the entire workforce is an extremely effective way to drive urgency and attract investment. What better way to increase your company’s valuation than to pitch your product as inevitable, and already replacing people. A CEO chasing a lucrative exit is incentivized to make it sound like the future is unavoidable and they’re the ones building it.
It appears to have worked. In May 2026, with OpenAI reportedly preparing a roughly trillion-dollar IPO, Altman reversed course publicly: “I thought there would have been more impact on entry-level white-collar jobs being eliminated by now than has actually happened. I’m delighted to be wrong.”1 The scary prediction and the walk-back came from the same person, about the same technology, at two very different moments for his company’s fundraising.
Company after company brands itself an “AI company” the moment the term starts trending, whether or not anything about the product actually changed. A Financial Times analysis found dozens of companies — in sectors as far from tech as gold mining and footwear — rebranded themselves around AI since 2023, and the rebrand alone added a combined $8.7 billion to their valuations, at least initially.2 The SEC has already fined firms directly over this. Two investment advisors were charged $400,000 combined for falsely claiming their AI capabilities did things they simply didn’t do.3
None of that means AI isn’t real or useful. It means a company talking up how revolutionary its AI is might be doing that for their own financial gain.
Myth: Large companies are cutting staff because of AI
In 2025 alone, several companies attributed over 54,000 planned layoffs to AI.4 How much of that is true?
Blaming AI for a layoff is a much easier story to tell than the real one. “We cut underperforming or overpaid staff” invites uncomfortable questions about hiring decisions and management. “AI made these roles obsolete” has become an easy scapegoat that sounds like a result of innovation. It’s a clean, unemotional and acceptable headline instead of a messy one.
Klarna’s CEO spent months publicly boasting that AI had replaced the work of 700 customer service agents. He later walked that back directly: “We have made 0 layoffs due to AI.” The cuts, he clarified, came from natural attrition after the company simply stopped hiring.5 UPS told CNBC something similar about its own corporate layoffs — AI was “partially related,” but not the primary driver behind cutting 14,000 roles; the real driver was falling parcel volumes and closing buildings.6
A Gartner VP put the pattern plainly: “Many CEOs turn to layoffs to demonstrate quick AI returns; however, this disposition is misplaced.”7
Myth: AI is a magic wand that can do anything
Marketing campaigns have painted AI as a tool that can do pretty much anything, with little to no effort from a human being. The idea of a tool handling your workload for you moves a sale forward a lot faster than “this tool works, but here are all the caveats to that.” Marketing only has to be “true enough.” A common theme I hear from companies I speak with is “Oh, I can just get someone on staff to use Claude Code to develop custom apps for us.”
As a frequent user of AI, I can tell you from personal experience that not one of these tools has been as easy to use as advertised. Yes, AI does help level the playing field and remove technical knowledge entrance barriers, but you still have to have the time, patience, and develop some technical understanding to use them as effectively as they are being promoted.
In fact, research analyzing over 2,400 enterprise AI initiatives found that more than 80% failed to deliver their intended business value. That’s roughly twice the failure rate of ordinary IT projects, by the way.8
A separate MIT study found that 95% of companies investing in generative AI saw no measurable return on their spending at all.9
AI is a genuinely powerful tool, but it is not a tool that works automatically, on any problem, with no setup. The businesses landing in that surviving 20% are the ones that treated it like any other serious technology investment: clear objectives, real preparation, and realistic expectations about what it can actually do.
None of this is new. People have been cashing in on market hype and the public’s unfamiliarity with new technology long before AI came along — the dot-com boom ran on the same playbook. That doesn’t mean the product is worthless. It means it’s worth reading the fine print before you buy in.
