Every technological revolution brings both opportunity and uncertainty. The rapid rise of AI is no exception. It’s no wonder, then, that alongside the excitement and experimentation comes a familiar question: are we heading towards an AI bubble – and what would happen if it burst?
Managing Director at Slalom.
Investment in AI has accelerated across predictive, generative, and agentic technologies as organizations race to capture value. Slalom’s research shows that 62% of UK&I executives expect a return on AI investment within just two years, a level of impatience that echoes the early days of the internet boom.
Media narratives mirror this tension, fluctuating between optimism and warnings of a dot-com style correction.
The real test now is whether AI can consistently deliver measurable impact and move from promise to performance.
AI: Is it a bubble?
A “tech bubble” typically refers to over-inflated valuations caused by speculation rather than fundamentals. In this case, among companies developing and delivering AI technology.
Naturally, share prices fluctuate in every sector, but tech stocks often remain attractive thanks to ongoing innovation. When interest spikes, investment follows and anything tied to the latest buzzword risks becoming overvalued.
The smaller players especially are most exposed whether through investor overreach or simply the speed of change of AI evolution outdating products. At the same time, new, large players are emerging that could challenge the future AI landscape.
The largest technology firms continue to lead the charge. Alphabet, Microsoft, Amazon, and Meta are expected to invest nearly $370 billion in AI-related initiatives this year, a level underpinned by stable growth, strong financials, and operational efficiencies.
Others are seeing similar momentum; NVIDIA’s record revenues reflect real demand for compute infrastructure, and Sam Altman recently claimed that OpenAI will reach an annualized run rate revenue of $20 billion in 2025 and has plans to reach hundreds of billions in sales by 2030.
This lays the groundwork for an IPO with the potential value of up to $1 trillion. If Altman’s claim is accurate, this potential price to earnings ratio of 50x, while very high, is not unheard of for high growth technology companies with a strong competitive advantage.
Even policymakers see this as a structural shift rather than speculation. Federal Reserve chair, Jerome Powell, recently described the current surge in AI investment as “the beginning of real, profitable businesses” capable of driving sustained economic growth.
Encouraging as this may be, it only makes the competition for success fiercer. The race to turn AI capability into tangible business impact is accelerating and only those who can demonstrate value quickly will maintain momentum.
AI: Is it a wave?
There’s no denying the speed and scale of change. The surge of innovation and investment in AI feels overwhelming and that intensity naturally suggests comparisons to a bubble. But if this momentum isn’t building toward a burst, is it instead a building into a wave?
With this much hype, it’s essential to separate substance from noise. Some AI development is being driven by fear of missing out or board-level mandates rather than a clear understanding of value.
Building for the sake of jumping on a trend risks wasted investments and reinforces the perception of a bubble, even when underlying progress remains solid.
Across the industry, however, we’re seeing AI fundamentally reshape how software is delivered, modernized, and scaled. The tools and practices emerging today are shortening development cycles, accelerating legacy modernization, and enabling new forms of automation that simply weren’t possible two years ago. In our work with customers, these capabilities are already unlocking productivity gains and helping organizations deliver value faster and more reliably.
Experimentation remains essential but it must be grounded in a realistic view of business outcomes. Some initiatives will fail, as they should in a healthy innovation cycle. Others will redefine how companies operate and compete.
Slalom data shows 64% of UK&I organizations are creating or planning new AI-related roles, outpacing expectations of workforce reduction. This reinforces what economists call Luddite Fallacy – that technological change tends not to eliminate work long term, but to reshape it and create new forms of opportunity.
The pace of change shows no sign of slowing. Most individuals and organizations have only begun to explore AI’s full potential. Its ubiquity, spanning every role, industry and daily workflow, ensures adoption will deepen rather than decline.
As valuations stabilize and early-stage hype settles, today’s “bubble” will look more like the progress of a sustained wave of transformation.
AI: In summary
AI investment trends show characteristics of a speculative bubble, rapid funding, media hype, and inevitable comparisons to the dot-com era. However, AI is already delivering measurable value.
Organizations are moving beyond pilot projects into production-scale deployments, embedding AI in operations, customer engagement, and decision-making. The coming phase will test which innovations endure, but the broader trajectory points to sustained transformation, not collapse.
We’re not watching a bubble inflate; we’re surfing a powerful, sustained wave of technological change.
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