CivilsKash
Global AI Frenzy—Innovation Wave or Economic Bubble?
Global AI spending is projected to hit USD 375 billion in 2025 and over USD 800 billion by 2026, prompting debate on whether current valuations mirror the dot-com bubble or represent genuine long-term technological value.
Economists argue that unlike the dot-com era, AI already exhibits mass commercial adoption—from LLMs such as ChatGPT-4/5 to automated customer support, logistics, diagnostics and coding. Yet demand still exceeds users’ willingness to pay, creating uncertainty on monetisation at scale.
Key economic concerns include heavy investment in AI data-centres consuming ~0.5% of global electricity and concentration of profits among a small minority of firms, raising fears that large-scale capital burn may be unsustainable—characteristics associated with speculative bubbles.
Supporters counter that scientific progress requires high-risk experimentation and long gestation periods, similar to historical tech cycles in the 1960s–2000s; even if some firms fail, the sector advances. The larger policy risks relate to AI hallucinations, misinformation, skill disruption, labour displacement and regulation gaps, making AI governance a central public-policy priority for UPSC (ethics, economy, S&T).
Economists argue that unlike the dot-com era, AI already exhibits mass commercial adoption—from LLMs such as ChatGPT-4/5 to automated customer support, logistics, diagnostics and coding. Yet demand still exceeds users’ willingness to pay, creating uncertainty on monetisation at scale.
Key economic concerns include heavy investment in AI data-centres consuming ~0.5% of global electricity and concentration of profits among a small minority of firms, raising fears that large-scale capital burn may be unsustainable—characteristics associated with speculative bubbles.
Supporters counter that scientific progress requires high-risk experimentation and long gestation periods, similar to historical tech cycles in the 1960s–2000s; even if some firms fail, the sector advances. The larger policy risks relate to AI hallucinations, misinformation, skill disruption, labour displacement and regulation gaps, making AI governance a central public-policy priority for UPSC (ethics, economy, S&T).