Should AI Fluency Be a Promotion Requirement? A Three-Level Framework.
IN ONE MINUTE
AI fluency is already shaping who gets promoted, often informally. If organisations make it a formal criterion, they should measure how leaders think about redesigning work, not how often they log in to a tool. A simple three-level model helps: Awareness (understands what AI can do), Application (uses AI to solve real problems and can explain the business case) and Redesign (rethinks how a function works). Pair any new criterion with genuine support for experienced leaders to learn.
THE OBJECTIVE
To give HR and executive teams a fair, practical way to assess AI readiness in leaders, without turning it into a box-ticking exercise.
TWO VIEWS FROM THE SAME WEEK
In one week I heard two opposite views. An HR leader told me their company had added AI fluency to its leadership competency framework: leaders who can't show they are using AI to improve their function won't be considered for the next level. A banking executive told me the opposite: judging leaders on AI adoption is a fad, and when his firm did something similar with "digital" a decade ago, it told them little about who could really lead.
Both have a point. And the tension between them is one of the most practical talent questions leaders face today.
WHAT THE RESEARCH SHOWS
- BCG AI Radar 2026: 72% of CEOs now say they are the main decision-maker on AI, double the previous year. When CEOs lead, AI naturally becomes part of how senior people are judged.
- Gartner (Oct 2025): only 8% of HR leaders believe their managers have the skills to use AI effectively.
- Gartner (Mar 2026): 45% of managers say AI has lived up to their expectations in improving their teams' work.
So expectations are rising faster than capability. That is exactly when a clear, fair standard helps most.
MEASURE THINKING, NOT LOGINS
Many early AI criteria measure tool use: training completed, licences activated, prompts sent. That is a bit like judging leadership by whether someone uses email. Tool skills matter, but they are quickly learned.
The leaders I see changing their functions ask different questions:
- Process: where is human judgement being spent on work a machine could handle?
- Data: which decisions are we making on instinct that could be informed by evidence?
- Value: which workflows would we design differently if every manual step disappeared?
THE FRAMEWORK: THREE LEVELS OF AI LEADERSHIP READINESS
| Level | What it looks like | Evidence to look for |
|---|---|---|
| 1. Awareness | Understands what AI can and can't do; supports change | Can explain AI's relevance to their function in plain terms |
| 2. Application | Has used AI to solve specific problems | A real use case with a business case in P&L terms, not tech terms |
| 3. Redesign | Rethinks how the function works | Redesigned roles, workflows or measures; built team capability |
Level 1 is a reasonable baseline for any senior role. Level 2 is where many capable leaders are today. Level 3 is rarer, and is where the larger returns tend to come from.
THE PART THAT NEEDS CARE
Many excellent leaders built their careers before AI tools existed. Their market knowledge, relationships and judgement are hard to replace. If AI readiness becomes a rigid promotion gate overnight, some of them will be disadvantaged, not for lack of ability but for lack of time and safety to experiment.
The fair response is to be open about the new expectation, give people the time, support and permission to learn, and assess progress over a reasonable period. Passing someone over quietly, without telling them why, helps no one.
Questions leaders ask
Should AI skills be part of leadership promotion criteria?
Yes, if it measures how a leader applies AI to improve the business, not how often they log in. Tool skills are quickly learned; redesigning work is not. Be open about the new expectation, and give experienced leaders time and support to learn before it becomes a gate.
How do you assess AI fluency in a senior leader?
Ask for evidence: a real problem they solved with AI, the business case in P&L terms, and how their team's work changed. I use three levels: awareness, application and redesign. Many capable leaders are at application today; redesign is where the larger returns come from.
What is the risk of making AI fluency mandatory?
Two risks: rewarding visible activity over real impact, and losing experienced leaders who were never given time to learn. Their market knowledge and judgement are hard to replace. Make the expectation clear, support people to meet it, and assess progress over a reasonable period, not overnight.
THE LAST WORD
Tool fluency can be taught in a week. The judgement to redesign how work gets done is what deserves a promotion.
Has your organisation, formally or informally, started factoring AI into promotion decisions? And is it measuring tool adoption or transformation thinking?
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Until next week,
Artificial Ian
Tell your network: if your HR team is updating its leadership framework this year, the three-level table is free to borrow.
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Sources: BCG AI Radar 2026 (Jan 2026); Gartner HR research press releases (Oct 2025; Mar 2026).