Shalini Kapoor and Tanvi Lall
This program focuses on five sets of imperatives: data, strategic technologies, emerging technologies, digital public infrastructure, and strategic partnerships.Learn More
A government department pilots an AI assistant for citizen service requests. It can triage applications, draft responses, and translate queries across languages. The pilot looks like a leap in efficiency. A month later, staff still follow the old process in parallel, supervisors are nervous about accountability, and the “new system” is a side screen that nobody trusts.
This is the most common AI story today—a failure of adoption, not the model.
The warning signs are visible in the data. Gartner expects a meaningful share of generative AI projects to be abandoned after proof of concept, citing poor data quality, inadequate risk controls, escalating costs, and unclear business value. IDC research, as reported by CIO.com, similarly finds that most AI proofs of concept do not reach widespread deployment.
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