AI Adoption Journey for Population Scale: The UCAF Framework

About this episode

The episode discusses the challenges of AI adoption at scale and introduces the Use Case Adoption Framework (UCAF) to facilitate this process in India.

In this episode of Interpreting India, Nidhi Singh is joined by Shalini Kapoor, chief strategist for Data and AI at the EkStep Foundation, and Tanvi Lall, director for strategy at People+ai. They unpack why so many AI initiatives get stuck after impressive demos, and what it takes to move from pilots to real, sustained adoption. Drawing on research spanning 1,000+ use cases across 25 countries, the guests introduce the Use Case Adoption Framework (UCAF) and explain how India can translate AI ambition into population-scale impact—especially across public services, agriculture, health, and other high-priority sectors. Why do AI pilots stall in “pilot purgatory,” even when the technology works? What does a concrete AI use case look like beyond a chatbot demo? And what institutional changes—trust, accountability, workflow redesign, safeguards, and data readiness—are required for adoption at scale?

People in this episode

Host: Nidhi Singh

Guests: Shalini Kapoor, Tanvi Lall

Topics covered

• AI adoption
• Use Case Adoption Framework
• public services
• agriculture
• health

Keywords

• AI initiatives
• pilot purgatory
• institutional changes
• data readiness

Mentioned in this episode

Products: Use Case Adoption Framework

Places: India

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