The Accountability Gap: India Builds The AI, But Who Answers For It?

Aditya Vikram Kashyap

Distributed AI systems create an accountability gap due to fragmented ownership across global teams, infrastructure, and data.

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Consider a system like many now in production. An AI agent that helps adjudicate credit disputes is engineered by a team in Bengaluru. It runs on a foundation model from a US lab, on cloud infrastructure in Virginia, retrieving customer data governed from Frankfurt, to affect a borrower in Ohio.

The institution that owns the outcome is headquartered in New York, and its board approved an AI policy last year.

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One day the agent does something it should not have done. Who answers? The engineer who wrote the orchestration logic, the GCC leadership, the model provider, the cloud provider, the executive who signed the deployment memo, the risk function that validated the system months and several model versions ago, the regulated legal entity, its home regulator, or the regulator of the country where the engineering happened?

The uncomfortable answer is not that nobody is accountable. It is that several parties are each accountable for a slice of the system, while no single instrument represents the system end to end. That is the accountability gap, and India’s GCC ecosystem now sits closer to its centre than almost any other part of the global technology industry.

The Scale Of What India Now Builds

The Nasscom-Zinnov GCC Landscape Report 2026, released in July, puts the number at 2,117 global capability centres, employing 2.36 million professionals and generating $98.4 billion in FY26 revenue, up 32 per cent since FY21, with over 500 Forbes Global 2000 companies now running a centre out of India. It ranks India as the world’s number one AI hiring market, with nearly half of all GCCs established since FY21 built with AI as a core mandate from inception.

It matters what these centres are, and that they are not all the same. A GCC is not a vendor; it is generally part of the multinational enterprise itself, staffed by the company’s own employees, governed by its policies. Many remain execution centres doing what a delivery contract specifies.

The more mature GCCs have become closer to the enterprise’s own engineering core: they own architecture decisions, run the data platforms, train and adapt the models, and staff the leadership deciding how a system behaves in production. The shift worth naming is not the relocation of work, but the distribution of institutional capability and technical agency, and accountability structures have mostly not kept pace.

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