A Workforce Split Into Five Distinct AI User Types

The report categorises employees into five groups based on their usage, knowledge, and prompting ability:

• AI Experts (1%): Highly skilled users with strong organisational support and significant time savings.
• AI Practitioners (9%): Competent but often lacking access to advanced tools or structured training.
• AI Experimenters (34%): Frequent users who overestimate their abilities and rely on basic use cases.
• AI Novices (44%): Workers with limited confidence, low access to tools, and unclear guidance.
• AI Skeptics (12%): Rarely use AI, largely due to lack of support rather than resistance.

Together, Experimenters and Novices account for 78% of the workforce, forming what the report describes as the “danger zone” for overconfidence and underperformance.

Indicators of Progress Mask Underlying Gaps

The report notes several positive trends. More companies now approve AI use. More employees receive training. Weekly usage has increased from 45% to 55% since 2024. Reimbursement for AI tools has also risen.

However, these indicators do not translate into higher proficiency. The average score across the workforce is 39 out of 100. Prompting skills remain low and objective knowledge of AI has declined across all user types. Most employees continue to use AI for basic tasks such as summarisation or drafting, rather than for strategic research or workflow redesign.

A significant perception gap also persists. 54% of workers consider themselves proficient, but only a small minority meet that threshold in practice.

Access and Training Remain Uneven

Four factors correlate strongly with higher proficiency. These include access to a large language model (LLM), clear organisational policy, managerial encouragement, and structured training. Yet these resources are not evenly distributed.

Executives are nearly twice as likely as individual contributors (ICs) to have access to an LLM. They also receive more training and more explicit support for AI adoption. ICs, who make up the largest portion of the workforce, are the least likely to receive training, reimbursement, or clear guidance.

Implications for the Creative Industries

For people working in creative fields the report’s findings carry relevance:

• Creative roles are highly augmentable by AI, but only when workers understand how to use tools beyond basic content generation. The report shows that strategic uses such as research, ideation, workflow optimisation remain underutilised.
• Access disparities. Freelancers and contractors who make up a large share of the creative workforce, may not have access to training or reimbursement. This is likely to widen the gap between well‑resourced organisations and independent practitioners.
• The pace of change increases the risk of skill stagnation. The report notes declining objective knowledge even among experts, acknowledging that keeping up with new models, tools, and workflows is becoming more challenging.

For industries that rely on innovation, experimentation, and rapid iteration, these findings point to a growing need for structured upskilling, not only to maintain competitiveness but to ensure that creative workers can meaningfully shape how AI is used in their fields.