Is this an AI Bubble or AI Boom?

In this episode of the Inspiring Tech Leaders podcast, I challenge the fear of an AI Bubble, revealing a compelling, evidence-backed case for an enduring AI Boom that's only just beginning.

Discover why the AI revolution is not just unfolding, but accelerating, and how structural adoption, vast investment, and the deep embedding of intelligence into core systems are converging to create a sustained period of growth unlike any we've seen before.

Tune in to understand why this pivotal moment represents a critical test of discipline for investors, executives, and policymakers alike. The future of AI isn't just arriving; it's exploding into existence, and the boom has only just begun.

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Transcript

Welcome to the Inspiring Tech Leaders podcast, with me Dave Roberts.

The news is filled with headlines at the moment predicting that the AI Bubble is about to burst, but could this actually be the start of an AI Boom period?  The AI revolution is not a fleeting mirage but is barely beginning to unfold. In this episode I’m going to talk about why I think this is actually Boom, not Bust! 

Many commentators and analysts have become fixated on fear of a bubble. Concerns of overinvestment, sky-high valuations and the risk that AI companies are spending relentlessly on infrastructure before they see a return. But if you look closely at the evidence, what emerges is not a bubble ready to burst, but a landscape that has investment and is already having a real economic impact.

So, let’s start with scale. In 2026, big technology companies are poised to invest unprecedented sums into AI infrastructure. Estimates suggest hundreds of billions of dollars will be poured into data centres, specialised chips and AI research and development.  In sheer scale, this is now one of the largest investment cycles in modern economic history. The sums are not just about hype; they are about building physical facilities that create capabilities. 

This kind of spending supports real economic activity. Data centres need land, energy, construction, engineers, logistics and ongoing maintenance. Those physical linkages to the broader economy means AI investments are not flimsy numbers on a balance sheet, they are jobs, factories, export opportunities and long-term industrial capacity.

And beyond the infrastructure, venture capital is flowing at historic levels into AI companies. In recent years, AI accounted for a larger share of global VC funding than almost any other sector. This reflects confidence that there are genuine markets and profits to be made across sectors.

It is not just investment, there is real revenue growth underlying the sector’s expansion. Global AI software and systems markets are now measured in the hundreds of billions. McKinsey, PwC and UN trade bodies forecast AI’s contribution to the global economy in the tens of trillions over the next decade. Gartner has suggested that by the end of 2026 the majority of enterprise applications will embed AI capabilities as standard.

This is not speculative future revenue; this is growth today. AWS, Azure and Google Cloud all report significant contributions to their broader business from AI-related workloads. Slowly but unmistakably, companies across sectors are deploying AI not for show but for tangible process improvements, cost savings and new products. These include automation efficiencies in coding, customer support and data analytics that lead to measurable returns on investment.

Economists sometimes warn that technology adoption follows an S-curve. Early use is slow, then accelerates, and finally plateaus. Look at the data now, AI is right in that steep growth phase where adoption and monetisation are beginning to intersect. That suggests that the boom is far from over.

One of the most compelling shifts we are seeing is AI’s movement from experiment to core infrastructure.

Five years ago, generative models and machine learning tools were laboratory curiosities. Today they underpin cloud services, enterprise workflows, supply chain management and even critical systems in sectors like health and finance. The companies leading in AI are not selling gimmicks, they are embedding intelligence at the heart of how other businesses operate.

Information from across enterprise earnings calls shows that companies are no longer just mentioning AI, they are quoting specific numbers and outcomes tied to Return on Investment. Firms are cutting development time, enhancing productivity, and reallocating capital from older technologies to AI-driven solutions. This is not fad behaviour. It is operational transformation.

And more broadly, AI has become a strategic priority for national governments and regional development agencies. Strategies are being updated, funds are being earmarked, and public investment complements private sector spending. In some regions, whole towns are becoming AI hubs, attracting global capital and high-skill jobs.

Now, don’t get me wrong. There are credible concerns about excessive valuations and near-term profitability. Surveys show that some fund managers worry about over-investment relative to revenues. And there is legitimate scrutiny of whether some parts of the AI ecosystem may be too heavily leveraged.

But there is an important distinction between short-term market exuberance and a boom grounded in structural transformation. In much of the AI landscape, we are seeing solid fundamentals, meaningful product adoption, growing revenue streams, enterprise integration and worldwide demand. The fear of a bubble states that the entire structure is unsustainable.  However, the evidence suggests instead that some valuations may be high because investors are pricing for long-term future impact, not because the underlying technology lacks substance.

Consider this, in past technological revolutions, such as electricity, railways, the internet, there were moments of speculative excess even as the broader transformation unfolded over decades. Bubbles can coexist with booms. The existence of speculation does not disprove the reality of structural change.

History suggests that bubbles rarely eliminate the underlying technology. After the dotcom crash, thousands of companies disappeared, yet the internet economy ultimately became stronger and more disciplined.

What makes this AI moment different is twofold. First, the breadth of application. AI is not limited to a single product or niche; it is spreading across industry after industry. The use cases for AI are diverse, and the opportunity space is vast.

Second, the pace of improvement in core capabilities. Computing power, model efficiency and generative systems continue to advance rapidly, lowering barriers to entry and expanding what is technically possible. Adoption follows capability, and capability is growing at a pace few anticipated.

These dynamics point not to an imminent collapse, but perhaps a more sustain period of growth.  This is the next generational technological shift, akin to the rise of the internet in the 1990s or electrification in the early twentieth century.

As we come to the end of this episode, it’s important to recognise that the debate around bubbles captures attention, because it resonates with historical memory. But to focus only on the fear of a bubble, is to miss the wider story of transformation that is already reshaping economies and institutions worldwide.

The AI boom is not over. In many ways, it is just beginning. Structural adoption, vast investment in real infrastructure, real revenue growth and the embedding of intelligence into core systems all point toward a revolution that will unfold over years, not months.

What this moment truly represents is a test of discipline. For investors, it is a test of valuation rigour. For executives, it is a test of strategic focus. For policymakers, it is a test of balance between encouragement and oversight.

For listeners who want to understand not just whether AI is a bubble, but why the boom is real and enduring, keep watching the developments in enterprise adoption, global capital flows and policy frameworks. This is not a sprint. It is a marathon. And we are only a few miles in.

Well, that is all for today. Thanks for tuning in to the Inspiring Tech Leaders podcast. If you enjoyed this episode, don’t forget to subscribe, leave a review, and share it with your network.  You can find more insights, show notes, and resources at www.inspiringtechleaders.com

Head over to the social media channels, you can find Inspiring Tech Leaders on X, Instagram, INSPO and TikTok.  What do you think, are we in an AI Bubble about to burst, or just the start of the AI Boom.

Thanks for listening, and until next time, stay curious, stay connected, and keep pushing the boundaries of what is possible in tech.