AI Capability Radar.
Maps an organisation's AI surface area — what is automatable, what is augmentable, what is human-bound — against its leadership readiness. The first deliverable in any AI engagement.
Three categories of work, made explicit.
Most AI conversations in boardrooms confuse three different categories of work. Some work can be fully automated. Some can only be augmented by AI without losing essential human judgment. Some must remain human-bound regardless of model capability. The Radar separates the three and produces a portfolio map.
Six steps to a deployable AI portfolio map.
Inventory the work
Every recurring activity in the leader's portfolio. By function, by frequency, by business impact.
Classify by category
Automatable · Augmentable · Human-bound. Each item gets one classification.
Score AI maturity
Where is the technology actually capable today? Where will it be in 12 months?
Score readiness
Is the team ready? Are the data foundations in place? Is the leadership prepared to redesign?
Plot the portfolio
Two-axis map: capability × readiness. Each item placed.
Select the first three deployments
Highest capability × highest readiness × highest business impact. Start there.
Three anonymised cases.
Pharma sales operations
Radar surfaced that 40% of sales-ops work was automatable but only 12% of the team was ready. Three deployments selected.
Sales-ops cycle time cut 35% over 9 months.
BFSI underwriting
Most underwriting work was augmentable, not automatable. Radar prevented an over-automation mistake.
Approval rate held steady. Cycle time cut 22% with full audit trail.
Manufacturing quality control
Two of the four QA steps were automatable; two were human-bound. Radar made the boundary explicit.
Defect rate cut in half. Inspector role redesigned around exceptions.
Cases anonymised by sector and seniority. Numerical outcomes are exact and locked in the engagement scorecards.
RE:CODE™ integration.
AI Capability Radar runs inside RE:CODE™ Step 1 (Diagnose) when the leader's accountability surface includes AI deployment.