Introducing Maturity Maps — A New Way to Measure AI Adoption
Episode
25 min
Read time
2 min
Topics
Artificial Intelligence
AI-Generated Summary
Key Takeaways
- ✓Adoption-Embedding Gap: High adoption rates mask shallow utilization across every function surveyed. Sales exemplifies this starkly — 88% of teams claim AI usage, but only 24% have integrated it into actual revenue workflows. Most "adoption" amounts to reps using ChatGPT in a separate browser tab for email drafts, not automated pipeline management.
- ✓People as the Neglected Bottleneck: Seven of ten business functions score "significantly behind" on the people dimension. Deloitte data cited shows 93% of enterprise AI spend goes to infrastructure, leaving only 7% for human upskilling and change management — the single largest barrier to converting AI capability into measurable business value.
- ✓Data as the Hard Ceiling: Eight of ten functions score 1 or 1.5 out of 5 on data readiness. Without proprietary context — customer history, deal data, internal codebases — organizations cannot progress beyond basic assistant usage regardless of how capable underlying models become. Data functions less as one pillar among six and more as a floor constraint.
- ✓Finance Governance Paradox: Finance is the only non-technical function to score on-track in any category, achieving it specifically in governance due to decades of regulatory muscle memory from SOX compliance and fiduciary requirements. However, finance scores significantly behind in every other dimension, raising the question of whether late-but-governed deployment will ultimately outperform fast-but-ungoverned functions.
- ✓Maturity Map Self-Assessment Tool: Superintelligent has published an 18-question quiz at bsuper.ai/quiz that plots an organization's position across all six maturity dimensions against both the on-track benchmark and estimated average. The tool covers all ten functions and is designed to surface gaps in deployment depth, governance, and data readiness without requiring a full formal assessment.
What It Covers
Nathaniel Whittemore introduces AI Maturity Maps, a six-dimension framework measuring enterprise AI readiness across deployment depth, systems integration, data, outcomes, people, and governance. Built from 480+ studies covering 150,000+ professionals, the Q2 maps reveal that most organizations lag behind on-track benchmarks across nearly all ten business functions.
Key Questions Answered
- •Adoption-Embedding Gap: High adoption rates mask shallow utilization across every function surveyed. Sales exemplifies this starkly — 88% of teams claim AI usage, but only 24% have integrated it into actual revenue workflows. Most "adoption" amounts to reps using ChatGPT in a separate browser tab for email drafts, not automated pipeline management.
- •People as the Neglected Bottleneck: Seven of ten business functions score "significantly behind" on the people dimension. Deloitte data cited shows 93% of enterprise AI spend goes to infrastructure, leaving only 7% for human upskilling and change management — the single largest barrier to converting AI capability into measurable business value.
- •Data as the Hard Ceiling: Eight of ten functions score 1 or 1.5 out of 5 on data readiness. Without proprietary context — customer history, deal data, internal codebases — organizations cannot progress beyond basic assistant usage regardless of how capable underlying models become. Data functions less as one pillar among six and more as a floor constraint.
- •Finance Governance Paradox: Finance is the only non-technical function to score on-track in any category, achieving it specifically in governance due to decades of regulatory muscle memory from SOX compliance and fiduciary requirements. However, finance scores significantly behind in every other dimension, raising the question of whether late-but-governed deployment will ultimately outperform fast-but-ungoverned functions.
- •Maturity Map Self-Assessment Tool: Superintelligent has published an 18-question quiz at bsuper.ai/quiz that plots an organization's position across all six maturity dimensions against both the on-track benchmark and estimated average. The tool covers all ten functions and is designed to surface gaps in deployment depth, governance, and data readiness without requiring a full formal assessment.
Notable Moment
The customer service function serves as a warning signal for all other departments: while leaders overwhelmingly rate their AI training programs as adequate, the majority of frontline CS workers disagree — and 87% report high stress as AI absorbs routine tasks, leaving humans to handle harder, more emotionally demanding interactions without adequate preparation.
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