Built for institutions navigating AI transformation
Most institutions can't answer a simple question: how ready is your workforce to execute on AI, not just adopt it? SAGE measures that gap directly, across a defined cohort of 50–100 employees, and hands leadership a clear, evidence-based baseline in weeks, not quarters.
SAGE exists because the cost of not measuring these is no longer hypothetical.
Ungoverned AI deployment is becoming a legal liability. Nigeria's National Digital Economy and E-Governance Bill will require licensing and impact assessments for high-risk AI systems. Kenya's AI Bill, 2026 goes further, requiring workforce impact assessments wherever AI affects employment.
Different mechanisms, same signal: across Africa, workforce readiness is becoming a compliance question, not just an operational one.
Highly paid staff are trapped in manual middleware, moving data between systems, reconciling outputs, and performing work that should be automated. This is operational debt: the compounding cost of people doing what infrastructure should.
Every quarter it persists, the cost compounds and the talent disengages. SAGE measures exactly where that debt sits and what it's costing.
Every SAGE Institutional engagement produces three deliverables designed for a leadership audience, not an HR audience.
We identify exactly where your talent pipeline lacks automated execution. SAGE maps the functions where highly paid staff are trapped in manual middleware, moving data between systems and performing work that infrastructure should handle. You receive a prioritized list of bottleneck functions with remediation options, not a single prescribed path.
We map exact percentages of your workforce across the four readiness archetypes: Capable Operator, Visionary Without Infrastructure, Experienced Invisible, and Aware But Frozen. This tells you not just how many people are ready, but what kind of readiness gap each group carries, so interventions can be targeted rather than uniform.
We evaluate whether your workforce can handle 2030 autonomous agent integration. This goes beyond tool adoption to measure whether your operational architecture, data flows, and talent pipeline are structured to deploy AI agents at scale, or whether deployment would collapse on contact with legacy manual processes.
Timeline
3–4 weeks from kickoff to roadmap delivery
Price
$5,000 fixed, 50–100 person cohort
Share your context and our institutional team will schedule a scoping conversation within one business day.