By Sharique Hassan Manazir
Artificial Intelligence (AI) has been evolving for decades. But the world is now abuzz with talk of an “AI bubble”. What explains this? The excitement is driven by rapid and often over-claimed technological breakthroughs, leading to excessive expectations about AI’s utility, social impact, and economic benefits. Massive investment inflows, amplified media coverage, and warnings from global financial institutions have intensified this discourse. Skyrocketing valuations of AI startups, along with aggressive investments by tech giants and conglomerates worldwide, have created unprecedented speculation around a potential AI-driven market bubble.
Investors are pouring billions into AI ventures, often assigning valuations in the billions for companies that are yet to achieve claimed output, let alone consistent profitability. OpenAI, for instance, is valued at over $500 billion despite lacking a sustainable revenue model. Media coverage fuels this excitement, emphasising the transformative potential of AI while often glossing over the real-world challenges, regulatory uncertainties, and the slow pace at which societal benefits materialise. The result is a perfect storm of enthusiasm, speculation, and concern.
Yet, this surge in interest comes with growing alarm. Financial institutions and economists have begun issuing warnings reminiscent of the dot-com era. Recently, the Bank of England has highlighted systemic risks from overstretched equity valuations, and veteran economist Gary Shilling has cautioned that “tremendous speculation” in AI stocks could trigger a sharp market correction. Even former UK Deputy Prime Minister and ex-Meta executive Nick Clegg, has described AI company valuations as “crackers”, questioning the sustainability of their business models. The US and global markets have reacted accordingly, volatility indices have spiked, AI and tech stocks have experienced rapid profit-taking, and investors are reassessing risk exposure. India, closely tied to global markets, has not remained insulated. Aggressive investments in AI infrastructure, though signalling optimism, also raise questions about near-term returns and opportunity costs.
Beyond financial markets, the AI bubble has profound social and labour implications. While investment flows are enormous, the measurable social and economic utility of many AI projects remains limited. Much of the spending is speculative, targeting future possibilities rather than delivering immediate, tangible benefits. This makes AI a distinctly double-edged sword.
On one side, the speculative frenzy around automation and generative technologies is driving a wave of job rationalisation across both blue- and white-collar sectors. Firms are investing heavily in AI to cut costs and signal technological leadership to investors, often framing human intervention as increasingly redundant. This marks a sharp departure from earlier technological booms such as the dot-com and telecom waves, which initially expanded employment and market participation before their eventual collapse.
On the other side, a new generation of professionals is rushing to specialise in AI regulation, governance, and ethics, perceiving these as future-proof domains. Yet this too may prove precarious: If the bubble bursts, demand for such roles could evaporate quickly; if the boom sustains, automation may itself limit the scope of these professions. Either way, AI’s promise of career stability appears far less secure than its advocates suggest.
Yet, the gap between expectation and actual societal benefit is widening. Unlike past technological waves, this bubble combines financial speculation with potential social displacement, creating a dual-layered risk. History offers lessons but no guarantees. The dot-com bubble of the late 1990s and the 2008 financial crisis showed that speculative excess can destroy wealth and careers alike. However, its current valuation levels, combined with speculative investment and narratives, make it vulnerable to sharp corrections. Those who overestimate the stability of AI-driven markets or the permanence of AI-related jobs may bear the brunt if optimism collides with reality.
The writer is assistant professor of Public Policy at the Kautilya School of Public Policy, Hyderabad
