Companies Are Still Betting Big on AI — Even If Returns Don’t Add Up
When hype meets corporate budgets, the bill can start to look like a risk signal.
The boardroom romance with artificial intelligence is getting expensive — and for a growing number of executives and investors, the relationship looks increasingly one-sided. A fresh Markets Pulse survey finds that while many firms treat AI as the engine of future growth, roughly the same number of respondents question whether the money being poured into AI programs is actually delivering proportional returns. That tension — between faith in AI’s promise and doubts about its present payoff — is now being flagged as one of the market’s riskier dynamics. (Bloomberg)
What the survey reveals (the hard facts)
- A sizeable share of respondents said AI continues to drive outperformance for companies, supporting the idea that AI is materially reshaping business lines and productivity. (OODAloop)
- Crucially, about as many respondents also said that the amount firms are spending on AI isn’t justified by the results — in other words, spending outstrips measurable benefit in many cases. (OODAloop)
- Those corporate spending patterns are being noticed by markets already riding a massive rebound: commentators point to a roughly $16 trillion rally off earlier troughs and dozens of record highs this year as context for why fears of a correction are rising. (Bloomberg)
Why this matters — the mechanics of a self-reinforcing bubble
There are two intertwined problems here. First is circular investment: companies use inflated market valuations or cheaper capital to spend on AI, which in turn helps sustain lofty valuations — regardless of whether those investments generate durable profits. Second is expectations creep: once investor narratives center on AI as the next economy-wide multipler, companies can feel compelled to accelerate AI projects (and budgets) simply to avoid being left behind. That dynamic risks creating a loop where perception drives investment more than performance does. Analysts and strategists are increasingly flagging that loop as a potential source of market fragility. (Bloomberg)
Real consequences for firms, workers and markets
- For CFOs and boards: justifying AI budgets will demand clearer KPIs. If companies keep spending without measurable ROI, they may face a cash-flow reckoning that coincides with any market pullback. (OODAloop)
- For employees: overinvesting in unproven AI projects can translate to wasted time, layoffs when projects fail to scale, or disappointment when “AI transformation” doesn’t improve day-to-day workflows.
- For investors and regulators: an abrupt reassessment of AI valuations could trigger market volatility; regulators and central banks have already begun warning about overheated pockets of the market that could amplify macro risk. (The Guardian)
The middle ground — not all AI spending is wasteful
Important nuance: skepticism about blanket spending doesn’t mean AI isn’t creating real value. Many AI-first companies and product lines are posting solid revenue growth; the challenge is distinguishing durable, profit-generating AI adoption from PR-driven or cosmetic projects that burn budgets. Investors and managers who learn to separate “hype” projects from genuine product-market fit will be better positioned when sentiment shifts. (computerspeak.co)
What leaders should do now
- Measure outcomes, not outputs. Track revenue attribution, productivity gains, or customer retention tied to specific AI initiatives rather than counting pilots launched.
- Stage spending. Break large AI programs into measurable phases with go/no-go gates.
- Stress-test valuations. Assume a scenario where AI multiples contract and ensure liquidity and cashflow can absorb stress.
- Be transparent with investors. Clear disclosure about realistic timelines and KPIs reduces the risk of a nasty repricing surprise.
Reflection — bubble or healthy correction?
History shows that many technological shifts produce manic investment cycles: canals, railways, and the internet all spawned booms that left winners and many losers. AI is unusual because its potential is broad and opaque — easy to talk up, hard to benchmark. That asymmetry creates fertile ground for both genuine transformation and overexuberance. The prudent play for businesses is clear-eyed experimentation coupled with disciplined finance; for markets, the watchword remains skepticism until cash flows — not proclamations — confirm claims. (Reuters)
Glossary
Markets Pulse — A frequent survey or series of market sentiment polls referenced by financial news outlets to gauge investor and corporate sentiment. (Bloomberg) Circular investment — When rising valuations encourage additional spending that in turn helps justify those valuations, creating a feedback loop. (Bloomberg) AI-first company — A firm whose products and business model are fundamentally built around artificial intelligence capabilities and services. (computerspeak.co)
Source: Companies Overpaying for AI Add to Bubble Risks, Markets Pulse — Bloomberg. https://www.bloomberg.com/news/articles/2025-10-10/companies-overpaying-for-ai-add-to-bubble-risks-markets-pulse?srnd=phx-ai&embedded-checkout=true (Bloomberg)
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