Harjeet Khanduja of Reliance Jio on strengthening org structures for AI success

In the latest episode of the SHRPA Success Navigator Series, Harjeet Khanduja, SVP–HR at Reliance Jio, unpacked one of the sharpest gaps highlighted in the SHRPA 2025 State of HR Report notes: the disconnect between high change readiness (86%) and low AI readiness (24%) among HR leaders.

Through a deep, candid conversation, Harjeet explained why this readiness gap exists, what is holding back enterprise-level adoption, and how HR can strengthen existing structures to shift from AI anxiety to AI-enabled business impact in 2025–26.

Key takeaways from our conversation: 

• Trust deficit is the biggest cultural barrier
  Companies hesitate to invest because enterprise tools don’t feel as intuitive or powerful as publicly available ones. Without trust in output quality—and without clarity on hallucination risk—adoption lags.

• Market immaturity fuels a wait-and-watch approach
  With new tools emerging daily, leaders worry about sinking costs into technologies that may become obsolete quickly. “Buying iPhone 17 when iPhone 18 drops tomorrow” is how Harjeet positions the dilemma.

• AI adoption is fundamentally about unit economics
  Leaders aren’t blocked by mindset or technology. It's ROI that shaping a lot of their decisions. If a tool doesn’t reduce cost or improve accuracy, adoption stalls.

• The fear narrative around AI job loss is hurting internal change
  Much of the workforce panic came from misreported stories of layoffs “caused” by AI. This fear, Harjeet notes, slows down willingness to experiment and learn.

• HR’s true skill shift: from doing to discerning
  The future skill is not mastering tools. For HR is about creating the right org structures that can easily interpret AI outputs, align them to business context, and catch inaccuracies that models miss.

• Decision intelligence: the real promise of enterprise AI
  Harjeet describes how ensuring the right organisational structures that integrate people and business data allows leaders to leverage the most of AI. To be able to ask a simple natural-language question: like “Where is my revenue problem?” and get insights synthesized from multiple systems instantly will help create better use cases for improved adoption.