The experimentation plateau
Every enterprise starts the same way: a few early adopters discover GenAI, word spreads, pilots launch, and usage climbs. Then it plateaus.
Teams are experimenting, trying prompts, testing tools, sharing tips in Slack channels. But the outputs remain inconsistent. What one person produces in twenty minutes takes another person two hours, and the quality gap between them is invisible until something goes wrong.
This is the experimentation plateau, and most organizations are sitting on it right now.
Three stages of GenAI maturity
Moving off the plateau requires a deliberate progression through three stages:
Stage 1: Diagnose
Before investing in training, understand where your teams actually stand. Not where they think they stand, but where they demonstrably are.
This means scenario-based assessment: realistic work situations where people use GenAI and their outputs are evaluated against objective criteria. The result is a capability baseline that shows exactly which skills are strong, which are weak, and which workflows would benefit most from intervention.
Stage 2: Enable
With diagnostic data in hand, enablement can be targeted rather than generic. Instead of "Introduction to GenAI" for everyone, you deliver labs focused on the specific skills and scenarios where gaps were identified.
Effective enablement is hands-on, scenario-based, and immediately applicable. Participants walk out with templates, checklists, and workflow artifacts they can use the next day, not slides they'll forget by next week.
Stage 3: Embed
The final stage is standardization. The skills and habits built in enablement get codified into playbooks, templates, and checkpoints that become part of how work gets done.
This is where GenAI stops being a tool people experiment with and starts being a capability the organization can rely on.
Why sequence matters
These stages are sequential for a reason:
- Enabling without diagnosing wastes budget on training that may not address the actual gaps.
- Embedding without enabling produces playbooks that people don't have the skills to follow.
- Diagnosing without acting generates a report that sits in a shared drive.
The progression (diagnose, enable, embed) ensures each investment builds on the last and the organization moves measurably forward.
The goal is not to have teams that use GenAI. It is to have teams that use it well, consistently, and safely, every time.