A practical Ai enablement operating model for CHROs and Chief People Officers

Having worked with many organisations on cross functional Ai enablement programmes, I wanted to share my learnings and insights into what ACTUALLY works.

<aside> ✌️

AI enablement is not a tool decision. It is a people system.

• The organisations that win will not be those with the most licences or the most champions.
• They will be those that define expectations, standardise ways of working, redesign workflows, build real individual tool capability, manage risk openly, and measure outcomes credibly.
• Champions remain valuable, but only when they stand on a backbone that makes the organisation stronger even when champions rotate out. </aside>

Why does this matter?

Many organisations have invested in generative AI tools and “AI champions” programmes, yet adoption and ROI remain inconsistent. The pattern is familiar:

• A small group becomes power users
• The majority dabble, then plateau
• Risk behaviours vary by team
• Leaders cannot confidently quantify impact or explain what “great” or “good” looks like

This is not a tooling issue. It is an enablement system issue.

AI enablement needs to be treated as a company capability, comparable to leadership development, security awareness, or management fundamentals. It must include three connected layers:

1. Org-wide enablement

   Standards, guardrails, tooling strategy, capability expectations, governance, measurement, and incentives.

2. Team-wide enablement

   Workflow transformation, shared assets, cross-functional process ownership, and an operating cadence that drives compounding improvements.

3. Individual enablement

   Practical tool capability so employees can use AI reliably and safely, including persistent workspaces, reusable context, output standards, and evaluation habits.

A champions programme can accelerate adoption, but it cannot substitute for any of the layers above. Champions are a distribution layer. Sustainable impact comes from a backbone that sets expectations, scales learning, reduces risk, and produces measurable outcomes.

This report lays out a practical operating model for combining all three layers into a single enablement system.

Why this matters now

AI adoption is not a single change. It is a new way of working that touches:

• how employees create, analyse, and communicate