A sovereign wealth fund

The fund's Human Capital function came to us with a clear ask: apply AI and workforce analytics to the team's work, translate role-level activity into a quantified view of where AI could lift productivity, and turn that view into a prioritised set of recommendations.

The engagement

Six weeks of analysis, sequenced across several months and designed to take no more than a day of each stakeholder's time. The unit of analysis was the role; the unit of action was the task.

What we did

• Harmonised 20 job descriptions into a single task model
• Decomposed each task into discrete actions and scored them against four AI capabilities
• Validated the model with the fund's team and folded their feedback back through the analysis
• Built deliverable tracks from the same evidence base: use cases for employees and a vendor shortlist for procurement

What they took away

• A prioritised evidence base for where to deploy AI first
• Role-level automation profiles and a task-level heatmap
• 60 use cases — three per role, anchored to each role's top three tasks. Each is a workflow loop with step-by-step guidance and ready prompts an employee can run today
• A scored vendor shortlist — 150 AI products evaluated against the function's work, top 20 recommended for targeted procurement discovery
• A single skills taxonomy of 295 skills across the cohort, usable across both AI prioritisation and mobility planning

In numbers

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