How to Move Beyond AI Adoption to AI Depth

Key Takeaways

• Weekly meetings allocate half to AI learning sessions.
• Hackathon success built on multi‑week AI campaign.
• Performance reviews reward AI teaching, not just usage.
• Three talent types: builders, evaluators, tastemakers.

Pulse Analysis

The conversation around artificial intelligence in the enterprise is shifting from simple adoption counts to what experts call "AI depth" – the extent to which workers rely on AI for core tasks. Companies that only track how many users have an AI tool risk missing the real value, which lies in daily, automated decision‑making. In HR, this shift matters because people processes are highly repetitive and data‑rich, making them ideal for AI augmentation. By focusing on depth, firms can unlock efficiency gains, reduce manual errors, and create a culture where AI becomes a trusted partner rather than a novelty.

Gametime’s approach illustrates how depth can be engineered. Guillory dedicated half of the HR team’s weekly meetings to hands‑on AI sessions, letting the head of AI transformation showcase tools like Claude Cowork and Zapier. A six‑week pre‑hackathon "campaign" built anticipation, with leaders sharing personal use cases and employees posting ideas in Slack, resulting in a focused, productive two‑hour event. The company also rewrote performance reviews to score employees on teaching AI to peers, turning knowledge sharing into a measurable metric that reinforces continuous learning.

For other organizations, the lesson is clear: embed AI learning into existing workflows, define three talent archetypes—builders, evaluators, and tastemakers—and ensure leadership models the behavior. When executives use AI themselves, they legitimize its use and accelerate adoption depth across the board. Over time, this creates a virtuous cycle of innovation, higher employee engagement, and measurable ROI, positioning firms to thrive as AI becomes a baseline capability across industries.