The AI Adoption Gradient
My observation about AI adoption is that individuals within the same organization often have very different attitudes toward AI and very different patterns of use.
I've come to think of these differences as an AI Adoption Gradient, seven recognizable positions that help explain how people relate to increasingly capable AI systems.
This is not a maturity model or a progression from bad to good. There is no virtue in moving along the gradient. It is simply a way to understand individual behavior without assuming that everyone approaches AI with the same interests, confidence, or intentions.
1. Non-User โ Does not use AI tools, whether from skepticism, lack of interest, or a deliberate preference for established methods.
2. Ambient User โ Encounters AI through features embedded in familiar software, such as email, search, document editing, or business applications, often without consciously choosing to use AI.
3. Casual Experimenter โ Occasionally uses ChatGPT, Claude, or similar systems for brainstorming, drafting, research, or curiosity, but has not incorporated AI into regular work.
4. Practical Integrator โ Deliberately incorporates AI into recurring work processes, understands its limitations, and reviews the results as part of normal professional practice.
5. Power User โ Uses AI extensively across multiple activities, develops reusable methods, combines tools, and often becomes a resource for colleagues.
6. Builder / Developer โ Creates AI-enabled workflows, automations, agents, or applications, moving beyond using existing tools to designing systems for particular purposes.
7. Evangelist โ Strongly advocates for broader and faster AI adoption, often emphasizing its transformative potential. This describes an attitude toward adoption rather than a particular level of technical skill.
Why the Distinction Matters
A single law firm may contain individuals occupying every one of these positions. Some may overlap. Neither seniority nor professional competence determines where someone belongs, and none of these positions is inherently superior.
This distinction also provides a useful lens for evaluating AI vendors. A product demonstrated by an enthusiastic power user may be far less useful to someone who approaches the same work differently. Successful adoption depends partly on understanding the people expected to use the technology, not merely the capabilities being offered.
For law firm leadership, the question isn't how to move everyone up the scale. It's whether the firm's decisions about AI reflect an accurate understanding of how its people actually work.
Rex C. Anderson
The retired attorney law firms call about AI Adoption
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