Turning AI usage data into targeted enablement
A digital sports entertainment company monitors and accelerates company-wide AI adoption in Airtable, aggregating AI assistant usage data via API, managing an internal coaching network, and capturing self-reported use cases. The solution generates AI-driven weekly insights and recommendations, giving functional leads and executives actionable adoption metrics that replace static reports and drive targeted enablement.
The problem
Company-wide AI adoption was hard to see. Tracking lived in decentralized spreadsheets with limited per-user telemetry, so nobody had a clear read on training completion, awareness gaps, or which teams were actually using the tools they had been given.
Security constraints ruled out some tool-to-tool connections, and without actionable insight, departmental leaders had no way to measure AI return on investment or target coaching where it would matter most.
What they built
The AI Enablement Team stood up a shared Airtable base that tracks AI assistant licenses and usage via API, maintains a custom assistant catalog and internal coaching network, and captures an AI use case inventory with backlog triage.
A portfolio rollup of AI initiatives feeds automated weekly insights generation, baseline self-assessment and quarterly goal setting, and an automated internal newsletter, connected to the HR system, team messaging, and a data warehouse.
The outcome
Functional leads and executives now get measurable movement along AI maturity curves instead of anecdotal updates, with automated executive reporting on AI return on investment replacing static reports.
Centralized visibility across thousands of employees sped up identification of power users and gave the AI Enablement Team a scalable template other functions have started to reuse for their own governance.
Inside the solution
AI Adoption Monitoring and Enablement
People & Talent Operations
- AI assistant license and usage tracking via API
- Custom assistant catalog and internal coaching network management
- AI use case inventory and backlog triage
- Portfolio rollup of AI initiatives
- Automated weekly insights generation
- Baseline self-assessment and quarterly goal setting
- Automated internal newsletter generation
- Low visibility into company-wide AI adoption
- Decentralized tracking in spreadsheets
- Limited per-user telemetry
- Low training completion and awareness gaps
- Lack of actionable insights for departmental leaders
- Security constraints preventing some tool-to-tool connections
- Difficulty measuring AI return on investment
- Measurable movement along AI maturity curves
- Targeted enablement and coaching
- Automated executive reporting on AI ROI
- Centralized visibility for thousands of employees
- Scalable template for other functions
- Faster identification of power users
- Centralized AI governance
- AI Enablement Team
- Marketing
- Workforce Operations
- HR
- Learning & Development
- Engineering
- Finance
- AI assistant APIs
- HR system
- Team messaging
- Spreadsheet tool
- Data warehouse
AI Adoption Monitoring & Enablement
Track company-wide AI adoption in one base: per-user assistant usage rolled up by team, a custom assistant catalog, an internal coaching network, and a self-reported use case inventory with backlog triage. Airtable AI then writes the weekly insight brief, the internal newsletter, the per-function adoption brief and the executive ROI narrative, while automations open coaching requests the moment telemetry shows a licensed employee has gone quiet.
From static reports to automated weekly insights
Copy the templates
Pull in usage data
Automate the insights
FAQ
Frequently asked questions
AI assistant license and usage data comes in via API on a schedule, so adoption metrics update automatically instead of depending on someone exporting a spreadsheet each week.
A combination of API-based usage tracking and self-reported use case capture. Together they give functional leads a fuller picture than raw license counts ever could.
Coaches are tracked alongside the custom assistant catalog, so when weekly insights flag a team with low adoption, there is already a coach and a relevant assistant ready to route to them.
Spreadsheets could not aggregate usage data via API or generate automated insights. Centralizing the workflow gave the AI Enablement Team one governance layer that scales to thousands of employees.
Yes, directly. Automated weekly insights generation and the internal newsletter are both AI-driven, built on top of the structured usage and use case data the base collects.