Unlike traditional B2B markets where only ~5% of customers are buying at any time, the AI boom has pushed nearly 100% of companies to seek solutions at once. This temporary gold rush warps perception of market size, creating a risk of over-investment similar to the COVID-era software bubble.
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Unlike past platform shifts that caught many off-guard, the AI wave is universally anticipated. This 'consensus innovation' intensifies all existing competitive pressures, as every investor—from mega-funds to accelerators—is aggressively pursuing the same perceived opportunities, pushing factors like Power Law belief to an extreme.
The current mass-adoption phase for AI tools means buying decisions that would normally take 5-7 years are being compressed into 1-2 years. Startups that don't secure customers now risk being shut out, as enterprises will lock in with their chosen vendors for the subsequent half-decade.
During a fundamental technology shift like the current AI wave, traditional market size analysis is pointless because new markets and behaviors are being created. Investors should de-emphasize TAM and instead bet on founders who have a clear, convicted vision for how the world will change.
The current AI investment surge is a dangerous "resource grab" phase, not a typical bubble. Companies are desperately securing scarce resources—power, chips, and top scientists—driven by existential fear of being left behind. This isn't a normal CapEx cycle; the spending is almost guaranteed until a dead-end is proven.
The current AI spending frenzy uniquely merges elements from all major historical bubbles—real estate (data centers), technology, loose credit, and a government backstop—making a soft landing improbable. This convergence of risk factors is unprecedented.
Vincap International's CIO argues the AI market isn't a classic bubble. Unlike previous tech cycles, the installation phase (building infrastructure) is happening concurrently with the deployment phase (mass user adoption). This unique paradigm shift is driving real revenue and growth that supports high valuations.
The startup landscape now operates under two different sets of rules. Non-AI companies face intense scrutiny on traditional business fundamentals like profitability. In contrast, AI companies exist in a parallel reality of 'irrational exuberance,' where compelling narratives justify sky-high valuations.
The AI fundraising environment is fueled by investors' personal use of the products. Unlike B2B SaaS where VCs rely on customer interviews, they directly experience the value of tools like Perplexity. This firsthand intuition creates strong conviction, contributing to a highly competitive investment landscape.
The narrative of "0 to $100M in a year" often reflects a startup's dependence on a larger, fast-growing customer (like an AI foundation model company) rather than intrinsic product superiority. This growth is a market anomaly, similar to COVID testing labs, and can vanish as quickly as it appeared when competition normalizes prices and demand shifts.
While AI investment has exploded, US productivity has barely risen. Valuations are priced as if a societal transformation is complete, yet 95% of GenAI pilots fail to positively impact company P&Ls. This gap between market expectation and real-world economic benefit creates systemic risk.
