How to Build an AI Fluency Framework for Your Team

Written By Nicolle Merrill

As more companies embrace AI, it’s no longer enough to ask whether employees are using tools like ChatGPT or Claude. The real question is: how well are they using them and are those tools improving business outcomes?

That’s why Zapier’s approach stands out. Their AI fluency framework provides a clear, role-specific way to assess how teams are using AI—from entry-level experimentation to transformative impact. It’s not just a table. It’s a strategic tool that aligns hiring, onboarding, training, and performance expectations around a shared vision for AI capability.


Here’s how you can build a version of this framework for your own organization.

1. Define the Roles and Responsibilities That Matter

Start by identifying the functions where AI adoption is already happening—or where it needs to. Think across teams: engineering, product, support, HR, marketing, sales. Focus on the workflows that drive impact, such as writing code, handling customer inquiries, writing job posts, drafting marketing copy, or analyzing campaign performance.

2. Create a Progression Scale

*Note: In this version of the AI fluency framework, we’re taking a different approach that Zapier. Rather than highlighting what's missing or labeling behaviors as “unacceptable,” we’re focusing on what progress looks like. Our goal is to create a positive, forward-looking model that helps teams recognize their current strengths with AI and see clear, practical ways to grow. This approach encourages curiosity, experimentation, and skill-buildin without making anyone feel targeted or behind.

Use a three-level structure to define maturity modeled off of Zapier’s approach:

  • Capable: Basic tool use, often copy-paste prompting

  • Adoptive: Starts automating tasks and building workflows

  • Transformative: Rethinks strategy and delivers new business value with AI

Customize the labels if needed but preserve the underlying logic: AI fluency is not binary. It evolves.

3. Describe Behavior, Not Belief

The value of the framework lies in its specificity. Don’t define levels based on how someone feels about AI. Define what they do.

For example, in Marketing:

  • Capable: Drafts headlines with AI

  • Adoptive: A/B tests content with AI-generated variants

  • Transformative: Builds personalized, AI-powered campaigns at scale

This makes the framework usable in hiring, onboarding, and performance development.

4. Use It Across the Employee Lifecycle

The most effective fluency frameworks don’t sit in HR documents. They show up in:

  • Job descriptions

  • Interview questions

  • Onboarding programs

  • Training pathways

  • Performance reviews

At Zapier, even early-stage applicants are assessed on AI fluency. During onboarding, every new hire learns to build with AI from day one.

5. Make It a Living Tool

AI evolves rapidly—and so should your framework. Update it regularly. Invite teams to contribute new use cases. Treat it like a shared cultural artifact, not a compliance checklist.

Why This Matters

Moving from “AI-friendly” to “AI-first” isn’t about chasing the latest tools. It’s about developing the people who can make AI useful, trustworthy, and transformative.

An AI fluency framework helps you get there. It gives structure to your ambition. It keeps teams aligned and progressing. And it sends a clear message: AI isn’t optional. It’s how we work now.

Curious about building your employees AI fluency? Take our short AI Fluency Mapping mini course or get in touch.

Nicolle Merrill
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