Why AI isn’t a bubble, it’s the next Industrial Revolution

The talk of an AI bubble completely misses the point. Hype is doing the job it’s always done, pulling in investment and attention. That is necessary fuel in a market this young. Yes, 95% of GenAI pilots will fail, as MIT reminds us, and that naturally creates bubble jitter. But what’s inflated isn’t the technology itself, it’s the expectations stacked on top of it: the belief that AGI is just around the corner and that early-stage companies should already be delivering world-changing breakthroughs.

The tech is progressing at its own steady pace while expectations balloon far faster than the capabilities. Investors chase the promise, founders pitch the future, and suddenly the market is priced for miracles instead of milestones. That’s the distortion. Valuations drift into science-fiction territory, built on assumptions about breakthroughs that don’t exist, and may not even be possible with current models. Which is why hype then ends up becoming part of the business model.

Meanwhile, the underlying capability keeps advancing, indifferent to who flames out or who gets funded. So when something finally bursts, it won’t be AI collapsing, it’ll be the financial bubble and the expectations wrapped around it - not the innovation itself. AI remains a transformation. Once the speculation drains out, the real builders will still be here, moving the field forward while the rest of the market catches its breath. You can’t uninvent intelligence.

Built on usage, not hype

And that’s the real difference between AI and a classic financial bubble; unlike financial bubbles, AI is already delivering tangible, compounding value. You can see it in daily workflows. Faster decision-making, sharper analysis, productivity gains, these will not vanish when the market dips. 

Gartner’s 2026 predictions underscore this shift, by 2027 it expects 75% of hiring processes to test for AI proficiency, turning generative-AI skills into a baseline requirement, and a lever for higher salaries. Candidates will develop those capabilities because employers will demand them, making it no different than checking for proficiency in Microsoft Office.

Real-world benefits make AI more like infrastructure than speculation. When a technology becomes embedded in how people work, hire, and compete, it stops behaving like an asset class and starts behaving like the backbone of the modern economy.

Lessons from past bubbles, the value remains

History backs this up, as every major “bubble” around transformative technology has left something enduring behind. The dot-com crash didn’t kill the internet, it cleared out the noise, and what remained became essential infrastructure. 

The same pattern played out with cloud, mobile, and every wave of innovation that looked overheated from the outside but proved foundational once the dust settled. 

Even going further back to the Industrial Revolution, the era wasn’t a bubble, but speculative frenzies formed around the new industries it created. “Railway Mania” is one of the clearest examples. Investors poured money into railroads at a pace the economy couldn’t sustain, fortunes evaporated when it crashed, yet railroads themselves became critical national infrastructure. The speculation disappeared, but the transformation stayed. AI is following that same arc.

The wrong fears entirely 

The conversation around the “AI bubble” needs to shift from fear of collapse to managing expectations realistically. Investors and CEOs must separate the hype from the enduring technological shifts, because the companies that embrace AI now will drive the transformation, while those waiting for a “pop” risk being left behind. The landscape is moving fast: the U.S. leads in innovation, China copies at scale, and Europe focuses on regulation. Success won’t wait for caution; it favors the builders, adopters, and those integrating AI into the core of their operations today.

Another common misconception, often from people outside the financial frenzy surrounding AI, is that it will replace humans and hollow out industries. This argument resurfaces with every wave of automation and is consistently proven wrong. AI isn’t eliminating jobs - it’s changing the value people bring to the table. The organisations that thrive won’t use AI as a cover for headcount cuts, they’ll use it to make their teams more capable, more decisive, and more strategic across the board.

Across industries and use cases, from fraud detection to supply chain resilience to clinical analysis,  the pattern is the same. AI surfaces the signal, humans apply the meaning. The myth of “AI replacing analysts” disappears the moment you see that analysts’ roles become more important when the noise is filtered out, allowing them to focus on higher-value work.

The bubble pops, the Revolution doesn’t 

When the bubble bursts, it won’t be AI itself that fails, it’ll be the inflated expectations and speculative valuations around it. 

The technology is already embedded in daily workflows, delivering measurable productivity gains and driving a real demand for AI skills across the workforce. History shows this pattern: every major tech boom has its froth, but what lasts is the infrastructure, the capabilities end up reshaping the world.

This means that if the bubble pops, the revolution will not. 

The smart move now isn’t to sit on the sidelines waiting for a “pop.” It’s to get in early, invest in skills, integrate AI into how you work, and focus on practical deployment. When the hype fades, the organisations that did this will be the ones shaping the next industrial era.

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