A key quantitative indicator that you're outpacing your organization's ability to govern AI is the utilization rate of provided tools. If you've deployed hundreds of licenses but only 20% of staff are weekly active users, you have an education and change management problem, not a technology one.

Providing AI licenses isn't enough. Companies must actively manage the transition of employees from basic users (asking simple questions) to advanced users who treat AI as a collaborator for complex, high-value tasks, which is where real ROI is found.

Formal AI competency frameworks are still emerging. In their place, innovative companies are assessing employee AI skills with concrete, activity-based targets like "build three custom GPTs for your role" or completing specific certifications, directly linking these achievements to performance reviews.

AI curiosity involves individuals testing tools in isolation. AI fluency is a collective capability where teams share a common language, integrated workflows, and a foundational understanding of how AI drives strategy. This fluency is built through consistent, shared learning and processes.

To make AI adoption tangible, Zapier built rubrics defining "AI fluency" for different roles and seniority levels. By making these skills a measurable part of performance reviews and rewards, you create clear incentives for employees to invest their time in developing them, as behavior follows what gets measured.

A successful AI rollout requires a holistic strategy. Start with "People" (training, identifying champions), define new "Processes" (how data is logged), select the right "Platform" (testing tools methodically), and measure success with "Proof" (attaching KPIs to every initiative).

To ensure AI adoption is a core competency, formally integrate it into your team's operating system. Webflow is redoing its career ladder to make AI fluency a requirement for advancement, expecting team members not just to use tools but to lead, own, and push the boundaries of AI in their work.

Recognizing that providing tools is insufficient, LinkedIn is making "AI agency and fluency" a core part of its performance evaluation and calibration process. This formalizes the expectation that employees must actively use AI tools to succeed, moving adoption from voluntary to a career necessity.

While pipeline is important, the real signal of a successful AI-driven business is the depth of customer engagement. Are customers expanding beyond their initial use case? Are developers integrating your tool into core workflows? Are communities actively discussing you? These leading indicators show a stronger foundation than top-of-funnel metrics alone.