In this episode, HFS Research’s Dana Daher is joined by Genpact’s Ajay Vasal to unpack insights from a new study of over 500 enterprise leaders on what it really takes to scale agentic AI.

While most organizations believe the technology is ready, very few are prepared to let AI act autonomously. The conversation explores why this is not a technology challenge, but an operating model shift that requires rethinking processes, governance, and decision-making at a fundamental level.

Drawing from real-world experience, Ajay shares how enterprises can move beyond pilots and unlock value by redesigning workflows for AI, establishing accountability, and shifting how success is measured. This is a practical discussion on what separates AI ambition from execution.

What you’ll learn

• Why scaling agentic AI is an operating model challenge, not a technology one
• The gap between AI ambition and enterprise readiness
• How to redesign processes for autonomous execution
• What governance and accountability look like in an AI-driven environment
• Why productivity alone is not the right way to measure AI success
• How leading enterprises are moving from pilots to real business impact

Key takeaways

• Most enterprises trust AI to recommend, but not to act
• AI cannot be layered onto processes designed for humans
• Process redesign is critical to unlocking AI value
• Governance and decision ownership must be clearly defined
• Measuring AI through productivity alone limits its true potential
• Organizations that treat AI as a business transformation will scale faster

Also, read the associated Market Impact Report titled "Autonomy requires trust in AI", here: https://www.hfsresearch.com/research/autonomy-requires-trust-in-ai/