There has never been a bigger opportunity for L&D.
Budgets may be under scrutiny, and learning is too often seen as a cost centre. But the tools to show your value have never been more accessible.
AI is one of them. Many teams are already using it to tackle the grey areas and challenges, but AI is only as useful as the thinking you bring to it. Give it a clear focus and the right context, you’ll receive better results.
This collection of AI prompts helps L&D champions, People/HR leaders, and Senior executives work through those questions. Use them with tools such as ChatGPT, Claude or Copilot to draft plans, challenge assumptions and decide what to do next.
Each prompt starts with a practical task and connects it to what should change at work. That matters because producing more training, plans or reports can leave us in The Activity Trap: measuring the work taking place without establishing the difference it makes.
Pick a starting point below.
AI prompts for training needs analysis and L&D planning
Use these prompts to investigate a business problem, agree meaningful priorities and make room for the work that matters most.
- Draft a Training Needs Analysis for a business problem: Investigate possible causes of a performance issue and produce a focused TNA with evidence, priorities and next steps.
- Give your objectives the ‘So what?’ test: Turn activity-based goals into clear priorities describing what should change for your people, customers or business.
- Decide what L&D should STOP doing: Review your portfolio and identify where to continue, reshape or stop work, while protecting mandatory commitments.
AI prompts for personal and team development plans
Use these prompts to connect development to everyday work, with opportunities to practise, support from managers and clear ways to review progress.
- Build a team development plan to improve performance: Turn a team performance problem into a practical plan for learning, workplace practice, and manager support.
- Turn feedback into a personal learning plan: Translate feedback into manageable development priorities, relevant learning activities, and progress checks.
- Equip managers to make development effective: Build practice, coaching and feedback into a realistic four-week manager routine.
- Make AI skills development deliver a useful result: Design a focused AI skills pilot and assess its effect on time, quality, rework and risk.
AI prompts for measuring training effectiveness
Use these prompts to assess what your evidence demonstrates, agree useful measures and explain the findings to leaders.
- Find The Activity Trap in your reporting: Review what your metrics establish, where evidence is missing, and how to improve your next L&D report.
- Agree the evidence with business leaders: Establish success measures, data owners, responsibilities and review dates before a programme begins.
- Check whether compliance learning actually changes risk: Examine how people apply their learning and what training records, observations and operational evidence show about workplace risk.
- Answer the board’s ‘so what?’ question: Turn programme results into a concise impact brief explaining what changed, what remains uncertain and which decision is needed next.
How to get a useful response
The prompts provide a starting point, but your context makes them relevant.
Before using one:
- Replace the bracketed fields (e.g. where it says [paste] or [insert]) before submitting. This usually takes the form of your relevant business problem, role, evidence, timeframe and constraints.
- Be specific about the improvement you want. Describe the task, behaviour or result that needs to change.
- Make uncertainty visible. If a baseline, target or cause is unknown, ask the tool to flag the gap and suggest how to investigate it.
- Check the response. Verify facts, question assumptions and discuss recommendations with the people responsible for acting on them.
Important to note: Ensure to use your organisation’s approved AI tools and follow its rules for sharing information. Speak to your organisation about AI policies if you are unsure. A polished answer still needs to make sense in your workplace.
Bring AI closer to your learning context with Kallidus intelligence
While tools like ChatGPT, Claude, and Copilot can help you explore a problem and produce a useful first draft, their relevance drops off the moment the data changes within your business. For many organisations, this sort of thing happens in a major way every week, or sometimes daily.
Kallidus intelligence, or K.i, is the intentional AI data layer within Kallidus. It already understands your learning, skills, and performance data in real time, so it can proactively spot development opportunities before you have to go looking for them.
What sets K.i apart is what it’s working towards: your business outcomes. Every insight K.i surfaces is tied to reducing risk, strengthening retention, improving productivity, and growing revenue.
These prompts help you practise that way of thinking. K.i brings it closer to the data and workflows your teams use.
Jace Allred
