Which AI skills should you prioritise by role and sector?
The AI skills to develop as a priority depend on role, not sector. Three levels structure a relevant AI training plan: basic AI literacy (understanding what a language model is, what it can and cannot do) for everyone; prompting and critical evaluation of AI outputs for regular users; and AI governance and deployment skills for decision-makers. Sector modulates concrete use cases, not core skills.
The initial mistake: AI training "for everyone"
The first generation of corporate AI training plans sent all employees to the same general session on "AI and ChatGPT". The result was systematically disappointing: too theoretical for operational staff, too superficial for technical profiles, and disconnected from the company's real use cases.
Effective AI training starts from real tasks, not tools. The question is not "how do you use ChatGPT?" but "which tasks in my daily work can AI handle in whole or in part, and with what safeguards?"
The priority matrix by profile
Profile 1: all employees.
Priority skills: understand what a language model is and why it sometimes makes mistakes (hallucination), identify tasks suitable for AI in daily work, know what data must not be entered into an external LLM (customer data, personal data, confidential information), know how to verify an AI output before using it.
Recommended format: 2-hour awareness session, online or face to face.
Profile 2: regular users (marketing, communications, HR, administration, finance).
Priority skills: effective prompt writing (basic prompt engineering), assessing the quality and reliability of an AI output, advanced use of AI tools built into business software (Copilot in Office, AI in CRMs, assistants in HR tools), awareness of algorithmic bias and its impact on decisions.
Recommended format: 4 to 6 hours of training, differentiated by business area.
Profile 3: technical and data teams.
Priority skills: fine-tuning and model adaptation, integrating LLM APIs into existing systems, model evaluation and benchmarking, data quality management and governance.
Recommended format: in-depth technical programme, often 2 to 5 days plus continuous practice.
Profile 4: managers and decision-makers.
Priority skills: identifying high-value AI use cases, assessing risks and compliance (AI Act, RGPD (GDPR)), managing AI-augmented teams, measuring ROI.
Recommended format: half-day to one-day executive session with case studies.
Sector nuances
The core skills are the same; the examples change. In finance, the focus is on risk and compliance; in marketing, on content generation; in operations, on process automation.