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How to measure your AI fluency—and move to the next level

The biggest gains from AI don’t come from having access to the right tools alone. They come from teammates who know how to work with AI thoughtfully: people who are curious, willing to experiment, and able to see where AI can meaningfully support their judgment and decision-making.

In 2026, businesses need a baseline level of AI fluency among their employees—not because everyone needs deep technical expertise, but because effective AI use today is about habits, mindset, and knowing how to apply AI in real work.

Here, gives you a practical way to assess your own AI fluency and understand what progress looks like, so you can move forward with clarity and confidence, one level at a time.

What is AI fluency?

AI fluency is your ability to use AI effectively, responsibly, and confidently in your day-to-day work. It affects how you decide when AI is useful, how clearly you communicate what you want, and how thoughtfully you evaluate what comes back.

AI fluency shows up in how you:

• Decide when AI is useful versus when a task needs a .
• Communicate clearly with AI systems through prompts, , and constraints.
• Evaluate and so they meet your standards for quality.
• Apply judgment around accuracy, bias, sensitivity, and downstream risk.
• , not just isolated or one-off tasks.

Why AI fluency matters

AI fluency matters because AI only delivers value when you know how to use it well. When you strengthen your AI fluency, the benefits compound and allow you to scale your impact as expectations and complexity grow. You can see the impact of it in a few concrete ways:

• You produce higher-quality work faster. Fluent users know how to use AI to handle routine or repetitive tasks—whether that’s using to , or building that , route work to other tools, and take next-best actions.
• You adapt more easily. As new tools emerge and evolve, you’re able to seamlessly —like prompting, evaluation, and task decomposition—instead of relearning everything from scratch each time.
• You make better decisions with incomplete or ambiguous information. AI fluency helps you question outputs, validate assumptions, and use AI as an input—not a final authority.
• You spend more time on judgment, creativity, and problem-solving. By offloading execution-heavy work, you create more space for the parts of the job that benefit most from human thinking.

An AI fluency rubric—and how to use it

This AI fluency rubric is a simple framework for describing how you’re currently using AI in your work and what meaningful growth looks like from there. It’s not a scorecard or a pass/fail test. Instead, it gives you concrete signals you can use to assess your habits and capabilities.

Here’s how to use it: 

1. Pick your baseline. Review all four levels and identify the one that best reflects how you work most of the time. It’s normal to see yourself in more than one level depending on the task. Use the examples and common signals to anchor on the level you return to most often.
2. Aim one level up. Focus on what actions you can take to move to the next stage through small, intentional changes in how you work with AI. The goal isn’t to jump levels or optimize everything at once. Instead, start with a single change you can repeat this week.

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Level 1: Unacceptable

This stage is a common starting point, especially for people who haven’t had the time, support, or context to explore AI meaningfully yet. It doesn’t reflect a lack of ability. Instead, it usually reflects limited exposure, uncertainty about expectations, or valid concerns about risk.

Common signals:

• Skepticism about AI’s usefulness or impact on work.
• Curiosity with no concrete examples of using AI for work or .
• Avoidance of due to uncertainty, discomfort, or . 

Examples of what this looks like: 

• “AI sounds interesting, but I don’t know how I’d use it.”
• “I’m not opposed to AI, but I have major concerns about it replacing human jobs, which is why I haven’t used it.”
• “I’ve heard stories of AI getting things wrong, so I’ll be eager to use it when it has improved.”

How to progress to the next level:

• Look for simple, real examples of how people in your role use AI today.
• Start with low-risk tasks to build firsthand experience.
• Focus on learning what AI is good at—and .

Level 2: Capable

At this stage, you’ve crossed an important threshold: you’re using AI on purpose. You may still be early in your journey, but you have real experience and momentum to build on.

Common signals:

• Purposeful use of one or more AI tools for work or personal productivity.
• Ability to explain why you used AI and how it helped.
• Willingness to experiment, even if usage isn’t deep yet.

Examples of what this looks like:

• “I often more efficiently—it consistently saves me time.”
• “I’ve used AI to , which saves me time in my daily work. I haven’t explored more advanced uses yet, but it’s been helpful.”
• “We use an internal AI tool to summarize meeting notes, which helps our team stay aligned.” 

How to progress to the next level:

• Use AI more consistently across similar tasks. and reuse approaches that work.
• Compare AI-assisted outputs against your own standards for quality.

Level 3: Adoptive

At the adoptive stage, AI is no longer an experiment—it’s a dependable part of how you work. You’re thoughtful about outcomes, aware of limitations, and continuously improving how you use AI.

Common signals:

• Regular, repeatable AI usage with clear impact on your work.
• Use of multiple tools or AI-enhanced workflows.
• Ability to articulate how AI improves outcomes, not just efficiency. 

Examples of what this looks like:

• “I’ve integrated AI and automation into my daily work, and am experimenting with X tools that have led to Y results.”
• “I regularly use AI to analyze customer feedback and improve our service. I’ve learned it speeds up analysis but can miss nuances, so I’m refining the process while considering ethical implications.”
• “I consistently use AI to forecast sales trends, which helps us adjust inventory planning. Over time, I’ve improved data inputs to address gaps in context and accuracy.”

How to progress to the next level:

• Redesign recurring workflows with AI in mind.
• Share effective AI patterns and lessons learned with others.
• Look for ways to extend impact beyond your own tasks.

Level 4: Transformative

This stage reflects impact at scale. AI has fundamentally changed how you approach work, and that new way of working influences others—your team, your projects, or even your function.

Common signals:

• Prioritizing AI-first solutions when solving problems
• Scaling AI usage across teams, processes, or initiatives
• Thinking strategically about why and how AI should be applied

Examples of what this looks like:

• “I introduced AI tools XYZ across my team—we now save 10-plus hours per week and improved quality.”
• “I was tasked with leading an initiative and used XYZ tools to build it, resulting in X impact for my company.”
• “I led a project to integrate AI in our supply chain management, aiming to optimize inventory levels. Through iterative testing and feedback, we reduced costs by 20%. I learned about AI’s limitations in real-time adjustments and addressed ethical concerns by ensuring transparency with stakeholders.”

How to keep progressing:

• Document AI workflows that work especially well.
• Expand those workflows to support other teams, projects, or use cases within your role.
• Experiment openly and mentor others by sharing AI workflows, patterns, and lessons learned.

Strengthen your AI fluency with hands-on use

AI fluency grows through hands-on use. The more you apply AI to real work—testing ideas, refining outputs, and integrating it into everyday processes—the faster your confidence and impact compound.

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