As world leaders gather in New Delhi for the Global AI Impact Summit this week, India is positioning itself as a bridge between AI haves and have-nots. The world’s most populous nation wants to create a “global AI commons” – a shared repository of AI applications and standards that could democratize access to technology for developing nations. But this ambitious vision collides with a stark reality: while governments talk cooperation, markets are experiencing AI-induced volatility that’s making investors rethink everything.
The Commons Vision: Sharing AI’s Benefits
Abhishek Singh, chief executive of India’s AI mission, frames the commons as essential for ensuring AI doesn’t become “private infrastructure controlled by a few companies.” The concept builds on India’s success with digital public infrastructure like the India Stack, which has connected millions to government services. “Frontier AI is being built, trained and controlled by a handful of firms and states, mostly in the US and China,” notes Jibu Elias, an AI researcher who has worked with the Indian government. For the global south, the commons represents a way to argue that foundational AI capabilities should be accessible to all.
Market Realities: Investors Hit Pause
While diplomats discuss cooperation, financial markets tell a different story. Recent weeks have seen violent sell-offs in sectors threatened by AI disruption, with investors showing unprecedented caution. “The world is changing very, very quickly… we wouldn’t have the conviction to try and bottom-fish,” says Robert Schramm-Fuchs, portfolio manager at Janus Henderson. The numbers are stark: trucking giant CH Robinson fell 12%, investment firm Charles Schwab dropped 11%, and commercial real estate firm CBRE plunged 16% – all within a single week.
What’s remarkable isn’t just the sell-off, but investors’ reluctance to buy the dip. “We see no sign of institutional investors trying to buy the dip in the [software] sector,” reports Marija Veitmane of State Street. Instead, money is flowing to hardware – the physical infrastructure that powers AI. This hesitation reflects deep uncertainty about which business models will survive AI’s advance.
The Productivity Paradox Finally Lifts
Amid this uncertainty comes a significant development: AI’s impact on productivity is finally showing up in the data. New figures suggest US productivity increased by roughly 2.7% in 2025 – nearly double the sluggish 1.4% annual average of the past decade. This aligns with what economists call the “productivity J-curve” – the pattern where general-purpose technologies require massive investment before delivering measurable gains.
“We are transitioning from an era of AI experimentation to one of structural utility,” explains Erik Brynjolfsson, director of Stanford’s Digital Economy Lab. His research shows AI-exposed sectors are already changing hiring patterns, with entry-level roles declining by about 16% while AI-augmented positions grow. The challenge now is spreading these productivity gains beyond early adopters.
Global Players, Local Challenges
India’s commons initiative comes as global AI giants face their own challenges in emerging markets. Anthropic’s expansion into India has hit a trademark dispute with a local software company that’s used the name since 2017. Meanwhile, OpenAI’s decision to test ads in ChatGPT has sparked criticism about commercialization versus accessibility. These tensions highlight the complex dance between global scale and local realities.
Europe offers another perspective on AI development. Investors poured �66 billion into European venture capital in 2025, with AI-related deals accounting for over 35% of transactions. “European governments seem to really care about building their own stack,” notes Siraj Khaliq of deep-tech fund Kembara. “The sovereignty tailwind is not to be underestimated.”
Balancing Cooperation and Competition
India’s commons proposal raises fundamental questions about AI governance. Can nations agree on shared standards when their economic interests diverge? Will companies share valuable AI applications in a commons when they’re competing fiercely in the marketplace? The tension is palpable: while India hosts a summit promoting collaboration, its own government just approved a $1.1 billion venture fund to boost domestic AI startups.
The market volatility suggests investors believe AI disruption is real and accelerating. As Goldman Sachs strategists note, some software “requires physical execution, regulatory entrenchment… or human accountability” that AI can’t easily displace. But for everything else? The sell-offs suggest investors aren’t waiting to find out.
India’s commons vision represents an important counter-narrative to winner-take-all AI development. But its success will depend on whether nations and companies can balance cooperation with competition, and whether shared resources can keep pace with private innovation. As the productivity gains finally materialize, the question isn’t whether AI will transform economies, but how evenly those transformations will be distributed.