5 Questions with Cisco’s Director of Product Management

2026-07-02 · Source: Execs In The Know · Field: Business & Management — Project & Product Management, Corporate Strategy & Leadership, Operations & Process Management · Depth: Novice, short

Summary

Cisco's Director of Product Management, Jyotsna Khandekar, highlights the transformative potential of AI in customer experience, shifting from reactive to proactive, predictive, and personalized support. She cautions against common pitfalls, such as prioritizing technology over genuine customer problems and optimizing for internal efficiency at the customer's expense. Khandekar defines "trustworthy AI" through three pillars: visibility, enabling observation, auditing, and explanation of AI decisions; governance, ensuring human oversight; and safety, involving guardrails and monitoring for abnormal behavior. She emphasizes that a human in the loop signifies maturity, not weakness, and that the goal is to strategically integrate human judgment. Khandekar closely monitors "adoption depth" as a leading CX metric and identifies "contextual velocity"—the speed at which customer understanding translates into action—as the emerging competitive differentiator, surpassing product or data alone.

Key takeaway

For AI Product Managers developing customer experience solutions, prioritize solving genuine customer problems over simply deploying AI technology. Your focus should be on building trust through transparent AI systems that offer visibility, human governance, and robust safety guardrails. Additionally, closely track "adoption depth" as a leading indicator of customer value, and cultivate "contextual velocity" within your organization to rapidly convert customer understanding into actionable, personalized experiences. This approach will drive sustained competitive advantage.

Key insights

AI in CX thrives by solving customer problems, building trust via visibility and governance, and rapidly converting understanding into action.

Principles

• Prioritize customer problems over AI technology adoption.
• "Trustworthy AI" needs visibility, governance, and safety.
• Human-in-the-loop is a sign of AI maturity.

In practice

• Monitor customer "adoption depth" as a leading CX metric.
• Implement AI systems with clear human oversight conditions.
• Design AI with guardrails and monitoring for safety.

Topics

• Customer Experience
• AI Product Management
• Trustworthy AI
• AI Governance
• Customer Adoption Metrics
• Contextual Velocity

Best for: Director of AI/ML, AI Product Manager, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by Execs In The Know.