Asia investors demand AI revenue proof, not just exposure: BofA

Chris Oberoi, head of Asia-Pacific research at Bank of America Global Research, is telling investors to sharpen their pencils. In comments reported by the South China Morning Post, Oberoi said the AI trade has moved past the phase where exposure alone is enough. “The issue increasingly is: does it add to productivity, and is it being monetised,” he said. His conclusion? “And the answer is, ‘absolutely yes’.”

That blunt quote captures a shift already underway across Asian markets. After a year in which AI-linked stocks, from chip designers to power utilities, soared on narrative alone, investors are now demanding the earnings proof behind the pitch. The focus is no longer on who has the best AI story, but on who can show AI translating into actual revenue and a fatter bottom line. That is a much higher bar, and it separates companies with real AI economics from those riding the theme.

The shift is not a rejection of AI. It is a maturation. For context, the same pattern played out with the internet in the late 1990s and cloud computing a decade later. Early experiments and big spending eventually gave way to a focus on unit economics, customer acquisition costs and revenue growth. AI is hitting that point sooner than some expected, partly because the capital costs are so enormous. Companies across Asia, from semiconductor fabs to software-as-a-service upstarts, have been investing heavily in AI infrastructure. Now their boards and shareholders want to see the return on that investment in quarterly numbers, not just in roadshow slideware. Oberoi’s “absolutely yes” signals that he believes the proof is already showing up in productivity and monetisation for some companies, but the burden is on management to demonstrate it clearly.

For management teams, the message is simple: be ready to answer the monetisation question. Executives who can point to specific AI products, subscription tiers, or productivity gains in their own operations will have a clear edge with investors in Asia. Those who cannot may find their multiples compress quickly, as the market rotates out of AI-themed names into AI-proof businesses. This is not about abandoning AI investments; it is about translating them into financial language that investors can model and trust.

Oberoi is confident the proof exists. His answer suggests that behind the headline chatter, there are companies already generating tangible results from AI, whether through automated customer service, software that boosts developer output, or industrial AI that cuts waste. The challenge for investors is identifying which companies are genuinely monetising versus those still in the pilot phase. That requires a more granular look at financial reports, segment disclosures and customer behaviour, rather than simply tracking which stocks have the word “AI” in their investor presentations.

The regional angle matters. Asia is home to some of the world’s largest AI hardware supply chains, including Taiwan’s advanced chipmaking and Korea’s memory makers, as well as a fast-growing enterprise software ecosystem. The investor demand for revenue proof will ripple through these supply chains, forcing companies to disclose more about AI-related revenue segments and to set clearer key performance indicators. It could also accelerate consolidation, as companies with strong AI monetisation acquire smaller peers that have interesting technology but less proven business models. For boardrooms, this means the AI strategy conversation must now include a financial architecture for tracking and reporting AI-driven returns.

Globally, the same dynamic is emerging. While Oberoi’s comments are specifically about Asia investors, they echo concerns on Wall Street and in Europe. For CEOs and CFOs everywhere, the takeaway is to treat AI not as a story driver but as a financial driver. Start with the productivity gains inside your own operations, measure them, and then look outward for revenue opportunities. If you cannot show the numbers, the market will show you the door.

Ultimately, this is a healthy correction for the AI sector. A trade built on promises is fragile; one built on revenue is durable. By demanding proof, Asia’s investors are doing what good investors do: pricing the future on evidence rather than hype. The companies that emerge from this phase will not just be AI stories. They will be AI businesses.