It’s impossible to miss how AI has begun to impact every part of the modern business. As organisational leaders it’s important for us to understand two things: how to use AI effectively in our day-to-day roles, and how AI is going to disrupt our industries, workforces, and operational processes.

I’ve recently completed a short AI training course that has made me rethink what I thought about both of these things. The ProfAI course (free, under an hour) is one of many that have sprung up to teach the world how best to use generative AI systems like ChatGPT and Claude.

But what really struck me wasn’t what the training contained, but how it did it. Because ProfAI uses AI in a way that fundamentally changes what we think we know about L&D in our organisations.

It starts by asking two questions:

• Describe your industry/organisation
• Describe your role and responsibilities

It then uses these responses to personalise and contextualise the course content, the review questions it asks, and feedback on answers you give. Indeed, a generic answer won’t allow you to move on – you’ll need to provide an answer that aligns with your responses to the initial questions.

Perhaps surprisingly, the mechanics of this are relatively simple – indeed, you could recreate the concept in an AI chatbot like ChatGPT using just a few sentences.

Deliver training to me based on the following:

Q1: Ask me my job and industry

Using the answer to this question, customise the below to be highly relevant:

Section 1:

Effective prompting: You should explain how to assemble effective prompts, with the formula: [Instruction or goal] + [context or background] + [desired format/output]. Provide an example derived from the response to Q1 and then break it down. Then test me on the concept, setting the task of writing a prompt for a common process. You should create the task using my response to Q1 to identify a relevant process. When I have answered by creating a prompt, you should rate the response based on the earlier formula and recommend improvements. 

Copy and paste the above into an AI assistant to try it yourself.

---

Four Fundamental Shifts for L&D

This simple example reveals four fundamental shifts that will reshape how we approach learning and development in our organisations:

1. Conversational Learning at Scale

We’re witnessing the return of conversational learning, but without the traditional constraints. Historically, we learned from tutors who could answer questions and provide feedback, but this was limited by availability and cost. The printing press democratised knowledge through books, leading to self-directed learning that reached its peak with e-learning modules and multiple-choice assessments.

AI brings back the tutorial experience – learners can ask questions, receive immediate feedback, and engage in dialogue about complex topics. But unlike human tutors, AI is available 24/7, can handle unlimited learners simultaneously, and maintains consistent quality across all interactions.

2. Adaptive Learning Pathways

The ProfAI example shows basic personalisation, but AI’s true power lies in adaptive learning. Rather than following predetermined paths, AI can adjust content difficulty, pacing, and approach based on real-time analysis of learner responses, comprehension levels, and performance patterns.

Imagine compliance training that automatically provides additional examples when someone struggles with a concept, or leadership development that adapts scenarios based on the learner’s management style and challenges. This isn’t just personalisation – it’s intelligent responsiveness that evolves with each interaction.

3. Prompt Engineering as Core L&D Competency

This represents the most significant shift in required L&D skills. Prompt engineering – the practice of writing clear, comprehensive instructions for AI systems – is fundamentally a communication and instructional design skill.

L&D professionals are uniquely positioned for this transition. You already know how to:

• Break down complex concepts into digestible steps
• Anticipate learner questions and misconceptions
• Build guardrails to keep learning on track
• Consider how instructions might be misinterpreted

The difference is that instead of designing static content, you’re designing dynamic learning conversations. You’re not coding – you’re crafting the intelligence that will guide thousands of personalised learning experiences.

In fact, many AI failures stem from technologists with excellent coding skills but no experience managing diverse learning groups. Your expertise in guiding learners through complex topics is exactly what AI systems need to succeed.

4. From Content Creation to Learning Orchestration

With AI handling content delivery and adaptation, L&D’s role evolves from creating materials to orchestrating learning ecosystems. Your focus shifts from what content to include to what outcomes to achieve; from building courses to designing intelligent learning experiences.

This means:

• Defining learning objectives that AI can interpret and work toward
• Creating assessment frameworks that measure genuine understanding
• Building feedback loops that improve both learner outcomes and AI performance
• Integrating AI learning with human mentoring and peer collaboration

---

The Strategic Imperative

These shifts create both opportunity and urgency. Early adopters will gain significant competitive advantages through more effective, efficient, and engaging learning experiences. But success requires strategic action now.

For L&D leaders, the immediate priorities are:

Audit and Identify: Review your current learning portfolio to identify programmes that would benefit from conversational, adaptive delivery. Start with high-volume, standardised training that requires personalisation.

Build Capability: Invest in prompt engineering skills for your team. This isn’t a technical training need – it’s about applying your existing instructional design expertise to AI systems.

Pilot and Learn: Launch small-scale AI learning experiments. Test the technology, understand the challenges, and build organisational confidence in AI-enhanced learning.

Prepare for Scale: Develop frameworks for managing AI learning experiences, including quality assurance, learner support, and continuous improvement processes.

The organisations that master AI-enhanced learning will create more capable workforces, reduce training costs, and improve learning outcomes. Those that don’t risk being left behind with static, generic training that fails to meet modern learner expectations.

The question isn’t whether AI will transform L&D – it’s whether you’ll lead that transformation in your organisation or be forced to catch up later.