AI, Software, Coding, Internet Security Thread
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There is a shift in the job market. There is an oversupply of CS graduates and postgraduates, and the demand is dwindling. A factor contributing to this is large corporations acquiring or having a stake in newer emerging companies, integrating them within their own ecosystem, and slashing the redundant workforce.
A recent report came out and stated that CS and Engineers are seeing more unemployment and are the top two.
Indos
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The companies laying off staff for AI today will regret it in five years
By Alexandra Ebert
Alexandra Ebert is Chief AI & Data Democratization Officer at Mostly AI.
July 16, 2025 at 3:04 PM EDT
Alexandra Ebert believes AI can support creative people, but it can’t replace them.
You’ve probably seen the headlines. “AI job cuts.” “Automation replacing humans.” Some CEOs are even proud of it.
OpenAI CEO Sam Altman says the next billion-dollar company could consist of one person thanks to AI advances. Anthropic CEO Dario Amodei thinks AI could eliminate nearly half of all entry-level white-collar jobs in five years.
Already this year, more than 64,000 people have been laid off across the tech sector, with Microsoft and Intel leading the charge and AI being a major factor.
People innovate, AI imitates
Not only is this short-sighted, it’s fundamentally bad business. The companies cutting people today in the name of AI will be the ones playing catch-up tomorrow.There is no doubt that AI is excellent at doing more with less. It speeds up processes, cuts down repetitive work, and buys back time. But AI on its own cannot create the next generation of products and services.
The businesses that win in the long term are the ones that innovate. That create new products. That reimagine how things should work, and find radical breakthroughs that impress their customers in new ways.
The data backs it up. McKinsey found that companies with innovation baked into the culture are 3.5 times more likely to outperform their competitors.
And history supports it as well—just ask Blockbuster. Back in the early 2000s, it had strong profits and a large customer base. But what it lacked was the foresight to use its leading position to build the next wave of value. Netflix built it instead.
And that kind of creative thinking still only comes from people. Ultimately, it comes down to this: AI doesn’t invent. It recycles. It’s trained on other people’s ideas, imitates patterns, and doesn’t jump the curve.
That’s not a flaw—that’s how AI is designed. As academic Mark Runco puts it: “AI can only produce artificial creativity.” It can support creative people, but it can’t replace them.
If your strategy is to lay off the people who could create the next big thing—good luck. You might run a tighter ship, at least in the short term, but don’t be surprised when your product roadmap starts to fall flat.
How AI can really unleash creativity
So, if you’re leading a large business, what should you do instead? Keep hold of your talent. Tell your team to use the extra time they have freed up with AI to innovate. Give your people the headroom to think.
Some of the world’s most successful—and perhaps more importantly profitable—products started as side projects inside Google, among them Gmail and AdSense. Not because they were asked for. But because smart people had the space and time to explore.
Imagine if those same people had been made redundant the quarter before. That’s exactly what is happening right now.
Too many leaders are taking the efficiency gains of AI and passing them straight to the bottom line. They’re juicing short-term profits and calling it innovation.
AI limitations
And that’s before you even factor in the risk that many of these so-called “efficiencies” may never materialize. For all the AI hype, humanity doesn’t have the greatest track record when it comes to predicting the future. If the magazines of the 1950s and 1960s were right, we’d be commuting to work with jet packs and cleaning our homes with nuclear-powered hoovers by now.
The same might apply here. Embedding AI into real-world business processes is hard, especially when it comes to sophisticated knowledge work. There are technical limitations, privacy minefields, and the unsolved problem of how to fix or debug AI agents when they go off course.
So, there’s every chance that some of the companies laying off staff today will find themselves quietly rehiring in a few years, once they realize the tech isn’t as capable as they thought.
Taken together, the winners won’t be the companies that cut deepest. They’ll be the ones that keep the right people, give them space, and leverage AI to push their creativity even further.
AI is rewriting the rules of business. What matters now is how you choose to use it. Where one company sees an opportunity to cut headcount, another sees a chance to build something new.
Only one of those will still be leading the market in five years.
The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.
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Read more:
- As tech CEOs predict AI will replace humans in just 5 years, this Fortune 500 boss says taking the focus off real people is a ‘recipe for failure’
- AI is replacing human connection as it boosts productivity. Success requires elevating relationships while embracing the technology
- Goldman Sachs CIO: We must prepare AI natives to shape the future of work—as only they can
- I’m leading the largest global law firm as AI transforms the legal profession. Lawyers must double down on this one skill
The companies laying off staff for AI today will regret it in five years | Fortune
Taking AI efficiency gains, leaders are juicing short-term profits and calling it innovation. But AI doesn’t invent—it imitates.
Indos
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OpenAI chairman says training your own AI model is a good way to 'destroy your capital'
Story by [email protected] (Henry Chandonnet)
- OpenAI chairman Bret Taylor said that companies trying to train their own LLMs will "burn through millions of dollars."
- "There's ones you can lease, there's open source ones," Taylor said on the Minus One podcast. "Don't do it."
- Taylor said the only companies that could handle the high training costs were OpenAI, Anthropic, Google, and Meta.
There's a scene in "The Dark Knight" where the Joker sets ablaze a massive pile of money. Deciding to develop your own frontier AI model today may be a similar exercise in burning cash — just ask OpenAI chairman Bret Taylor.
Taylor, who has worked for three companies that have trained LLMs, including Google, Facebook, and OpenAI, called training new AI models a "good way to burn through millions of dollars."
On a recent episode of the Minus One podcast, Taylor advised AI founders to build services and use-cases, but not new frontier models entirely.
"Unless you work at OpenAI or Anthropic or Google or Meta, you're probably not building one of those," said Taylor, who also cofounded Sierra AI. "It requires so much capital that it will tend towards consolidation."
That high bar of capital has stopped any "indie data center market" from forming, Taylor said, because it simply costs too much.
Taylor advised that founders work with the AI juggernauts instead — which, it's worth noting, is something that AI giants like OpenAI, where he's chairman, would directly benefit from. OpenAI sells "tokens" to access its API, which developers can build into their applications and programs.
While the American LLM market remains largely consolidated, international players have tested Taylor's theory. In January, DeepSeek released its R1 reasoning model and a corresponding chatbot. DeepSeek used fewer, less advanced chips to build its LLM, minimizing capital costs.
The Chinese AI app shot to No. 1 on the App Store charts, surpassing ChatGPT and igniting a debate in tech and on Wall Street about whether tech giants were overspending on AI model development.
In his podcast interview, Taylor laid out other paths that entrepreneurs could take in the AI market, rather than training a new model. One was the "AI tools market."
"This is the proverbial pickaxes in the gold rush," Taylor said. "It's a dangerous space because I think there's a lot of things that are scratching an itch today that the foundation model providers might do tomorrow."
Entrepreneurs could also try to build what Taylor called an "applied AI company."
"What were SaaS applications in 2010 will be agent companies in 2030, in my opinion," Taylor said.
Building a model from scratch, though, is a sure-fire way to "destroy your capital," Taylor said. He called handmade models "fast-depreciating assets," and not cheap ones either, costing the builder millions of dollars.
"There's ones you can lease, there's open source ones," Taylor said. "Don't do it."
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