AI is reshaping industries at record speed, but is this boom a bubble – or the start of a lasting transformation?
Artificial Intelligence (AI) has moved from buzzword to backbone of markets. Innovation is accelerating, capital spending is surging, and investors worldwide are paying attention. The excitement has echoes of a modern-day gold rush – but beneath the hype lie real, long-term shifts in how companies create value and compete.
Last year, we were strongly optimistic about the AI opportunity. After another year of remarkable performance, we revisited our view. Our conclusion? We continue to see powerful reasons to stay constructive — but several risks are becoming increasingly important to monitor.
AI adoption is only just getting started. It is already automating tasks, enhancing customer experience and enabling new business models, yet as of as of mid-2025, only around four in ten U.S. companies say they use AI in their day-to-day business.[1]. The potential for wider deployment across sectors remains significant.
Investment trends underline this. The big global cloud and technology platforms, such as Alphabet, Amazon and Meta continue to pour capital into chips, datacentres and cloud infrastructure, while governments step up spending to stay relevant. This looks less like a passing fad and more like a long-term strategic race.
For companies, the gap between early adopters and laggards is widening. Firms that embed AI into their processes are seeing productivity gains, better client engagement and an edge in attracting talent. Those without a clear AI roadmap risk ceding market share as the technology scales.
Crucially, AI is a recurring, not a one-off, revenue opportunity. Every query, model update and agent action consumes compute, supporting durable demand for infrastructure and cloud services. Even after strong share-price gains, valuations still look more reasonable than during the dot-com bubble, and company balance sheets are generally healthier
One growing concern is that power constraints could slow the expansion of AI infrastructure. Datacentres already consume vast amounts of electricity, and U.S. facilities alone could account for 12% of national power demand by 2030[2]. Yet investment in new generation capacity has lagged for years. If supply cannot scale quickly enough, some planned datacentre projects may be delayed or downsized — with knock-on effects across the entire AI value chain.
The AI ecosystem is also becoming more interconnected through partnerships and financial links. This speeds up innovation, but it also means that if one major player runs into trouble, the impact can spread quickly to suppliers, customers and investors.
The AI boom is not only an equity story – it is also changing how companies use bond markets. Building data centres and buying the chips needed for AI is extremely expensive. Many large, established technology and cloud companies are now borrowing more to help finance this investment, on top of the cash they generate from their existing businesses.
At the same time, smaller and more speculative companies are also turning to bond investors and banks to raise money for AI projects. This means the amount of debt linked to the AI theme is growing, and investors are starting to look more closely at which businesses have strong balance sheets and reliable cash flows, and which are taking on a lot of borrowing in the hope that future growth will materialise.
Some smaller, newer companies specialise in building AI data centres. They can move quickly, but often rely heavily on borrowing and complex financing structures, which makes them riskier if demand slows or clients do not renew contracts.
We continue to believe the AI revolution is real and structural. The technology is still in the early phase of adoption, investment remains robust, and the economic potential is immense. The whole AI ecosystem now extends far beyond Nvidia, and a broader range of tech companies are positioned to benefit from this transformation.
But the path forward will not be linear. Power constraints, ecosystem fragility, and the financing required for large-scale infrastructure buildouts all deserve close attention.
At this stage, however, we see AI not as a speculative bubble, but as a long-term opportunity — one that still has significant room to grow.
[1] Corporate AI adoption may be leveling off, according to Ramp data | TechCrunch
[2] Charted: The Energy Demand of U.S. Data Centers (2023-2030P)
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