AI CAPABILITY • PEOPLE
AI Skills & Fluency
Building capability, not just access
In 30 Seconds
AI tools are increasingly available. Knowing how to think with them is still rare. AI fluency isn't about using ChatGPT – it's about understanding when AI helps, when it doesn't, and how to get consistent value from the collaboration.
The gap isn't usually willingness – employees are ready. It's organisational: unclear guidance, missing workflows, no time to experiment.
Where we help: Moving teams from access to fluency. Assessment, practical training for real work tasks, and redesigning workflows so AI is built in – not bolted on.
DEEP DIVE
Two Roles for the AI Era: The Agent Manager + Enterprise Operator Framework
Two critical skill sets for AI success. When execution becomes cheap, knowing what to build and how to direct AI becomes the competitive edge.
DEEP DIVE
The AI Literacy Gap: Why Tool Access Isn't Fluency
Comprehensive guide to understanding the gap at every level – from board directors to front-line teams – and what actually works to close it.
Access Is Not Fluency
AI access means you can use the tools. Most organisations have this now.
AI literacy means you understand what AI is, broadly. Training courses cover this.
AI fluency means you can think with AI – knowing what to delegate, how to communicate effectively, when to trust outputs, and how to iterate toward quality.
| Access | Literacy | Fluency | |
|---|---|---|---|
| Question | Can I use it? | What is it? | How do I think with it? |
| Result | Occasional use | Informed opinions | Consistent value |
| Effort | License purchase | Training course | Deliberate practice |
The Readiness Gap
People are more ready than their organisations realise.
Research consistently shows employees are curious and willing to adopt AI. The blockers are usually organisational: unclear guidance, missing workflows, no time to experiment, and leaders who underestimate their teams' readiness.
The Permission Gap
People want to use AI but aren't sure what's allowed. Clear policies enable adoption; ambiguity creates paralysis.
The Integration Gap
AI exists alongside work, not within it. Tools are available but workflows haven't been redesigned to incorporate them.
The Confidence Gap
Knowing a tool exists is different from trusting your ability to use it well. Fluency builds confidence through practice.
The 4D Framework
Four capabilities that define AI fluency, from Anthropic's AI Fluency course
1. Delegation
Knowing what to hand off
Not everything benefits from AI. Fluent users understand which tasks suit AI assistance, which need human judgment, and which work best as human-AI collaboration.
2. Description
Communicating effectively
The skill of providing context, not just instructions. What does AI need to know? What constraints matter? What does “good” look like? Clear communication drives quality output.
3. Discernment
Evaluating AI output critically
AI output looks confident whether it's right or wrong. Fluent users know how to verify, spot weaknesses, identify when AI is guessing, and apply appropriate skepticism.
4. Diligence
Working responsibly
Understanding data sensitivity, privacy implications, and appropriate use. Knowing when human review is essential. Building habits that scale safely.
The Deployment Overhang
Your team isn't just using AI differently – they're using far less of it than they could.
Research published in early 2026 measured how people actually use AI agents in practice. The finding: AI can handle tasks lasting up to five hours. The most demanding real-world usage peaks at 42 minutes. The median task? Forty-five seconds. That gap – between what AI can do and what people ask it to do – is the deployment overhang. It exists in every organisation using AI today.
This extends the 4D Framework above.
The 4D skills tell you how to work with AI (delegation, description, discernment, diligence). The deployment overhang reveals a fifth dimension: scope. Most people aren't just interacting with AI poorly – they're asking it to do tasks that are too small and too safe. Closing the gap means giving AI bigger, more complex work.
Trust Maturity: From Approving to Monitoring
The same research revealed a clear pattern in how AI fluency develops:
New Users
- • Approve most AI actions manually
- • Rarely interrupt the AI mid-task
- • Treat AI like a subordinate needing constant oversight
- • Stick to short, familiar tasks
Expert Users
- • Auto-approve 40% of actions
- • Interrupt nearly twice as often as new users
- • Treat AI like a trusted colleague they actively oversee
- • Delegate longer, more complex work
The shift from new to expert isn't “hands off” – it's “hands different.” Expert users give more trust upfront but intervene more assertively when something matters. They monitor rather than approve. This is a learnable skill, not an innate talent.
One surprising finding: AI agents stop themselves to ask for clarification twice as often as humans interrupt them. The concern that AI will “run away” with a task is less supported by data than the concern that people won't push AI far enough.
Related: Read the full analysis in the February 2026 AI Signal – including practical steps for closing the deployment overhang in your team.
Learned, Then Practiced
Fluency can be learned. Courses like Anthropic's AI Fluency course provide solid foundations in the core competencies.
But like any language, fluency develops through regular use. The course gives you the framework; practice builds the intuition.
What Builds Fluency
Regular interaction builds intuition. Occasional users never develop the feel for what works.
Time to try things without pressure. Learning what AI can and can't do through exploration.
Teams that share prompts, techniques, and failures build collective fluency faster.
Organisations that enable this practice see compounding returns. Those that don't remain stuck at the “access” stage.
Where Fluency Lives in Organisations
Champions
Early adopters who experiment and share learnings. Often in middle management – close enough to the work to see opportunities, senior enough to influence adoption.
Teams
Fluency spreads through teams faster than through training. When one person finds something that works, the team learns. Shared context accelerates everyone.
Workflows
The strongest fluency gets embedded in process. Not “use AI if you want” but AI built into how work gets done. Systematic, not optional.
How We Help
Capability Assessment
Understand where your team's AI fluency actually is. Identify gaps and opportunities. Build a realistic development plan.
Practical Training
Hands-on skill building for real work tasks. Not generic AI overviews – specific capabilities for specific roles.
Workflow Integration
Help teams redesign how they work, not just add AI to existing processes. The practice that correlates most with success.
Related Capabilities
Fluency connects to how AI systems are built and governed in your organisation.
Agents & Orchestration
Fluent teams can create and use skills. Learn about the skills-based approach to AI capability.
Learn more →Strategy & Governance
Fluency needs clear guardrails. How governance enables safe experimentation.
Learn more →Context Engineering
The foundation that makes AI useful. Knowledge architecture for your specific context.
Learn more →From Access to Fluency
Whether you're developing AI fluency across a team, assessing current capability, or designing how AI fits into workflows – we can help you move from tool access to genuine capability.