Every major disruption creates a strategic window – a period when established rules are shifting but new norms haven’t yet solidified. The shift to cloud computing didn’t just move data storage – it shifted IT departments from hardware maintainers to enablers of remote work and digital collaboration. Mobile technology didn’t just make communication portable – it redefined customer service sales and how entire industries operate.
Now AI is creating the same kind of window for the Learning and Development profession.
Generative AI is rapidly reshaping business by expanding who can perform complex tasks and accelerating automation of work. As its use becomes more widespread, leaders are questioning long-held assumptions about which roles require deep expertise, how work should be organised, and where human judgement is still essential.[i] That uncertainty creates space for us to reposition strategically.
Yet most L&D conversations are stuck asking the wrong questions. While we’re debating which AI tool creates content faster, we’re missing the fundamental question: What if AI doesn’t just change what we do – but who we are as learning professionals and how we create value?
The Conversation We’re Having
Across L&D the dominant focus is on how to create content faster, and speed is being prioritised over quality. According to recent survey research from Donald H Taylor and Eglė Vinauskaitė about use of AI in L&D, the key benefit we expect to see is to ‘Create learning content faster’ which topped the list with 20.6% of all votes cast, whilst ‘Improve the quality of learning design’ only reached #5 with 11.4%.[ii]
We’re experimenting with prompt engineering, automating existing processes, and celebrating productivity gains. The survey of 420 L&D practitioners found that whilst 45% are using AI in some parts of their work, few are exploring more advanced applications beyond content creation – like AI coaching and personalised learning paths.
This experimentation with AI tools isn’t unimportant, but it’s only part of the picture.
What we’re not discussing is strategic repositioning. We’re not exploring what human development looks like when AI increasingly handles content creation or questioning our value proposition as these capabilities evolve.
What We Should Be Talking About
I attended two sessions at Association for Talent Development (ATD) 2025 Conference that moved beyond ‘how to use AI’ to ‘how might we redefine our role and value.’
Maise’s Vision: Champions of Human Potential
Elliott Masie challenged us to move beyond our fascination with AI capabilities and ask bigger questions: ‘How can we support others to adapt when AI changes the very nature of work, performance and careers?’[iii] He wasn’t talking about prompt engineering. He was talking about our fundamental purpose as learning professionals. Jobs will change. Skills will shift. People need support navigating career uncertainty.
Masie sees L&D professionals becoming champions of human intelligence (HI) working alongside AI. This means ensuring human-centred skills like empathy and critical thinking don’t get lost in the rush to automate everything. It means supporting people through massive reskilling – not just teaching new tools but helping them navigate fundamental changes to their careers.
Cavalier’s Exploration: Human-Machine Performance Analysts
Josh Cavalier offered a different angle, one that is more tactical but equally challenging: ‘What if we move from being content creators to performance optimisers?’[iv] Instead of designing courses, we might design systems. Instead of delivering training, we might orchestrate human-machine collaboration.
Cavalier calls this role ‘Human-Machine Performance Analysts’ – professionals who optimise the partnership between people and technology, orchestrating how humans and AI work together.
These aren’t the only possibilities. They offer different starting points for reimagining our strategic value.
How You Can Start Shifting the Conversation Today
Here’s some ways you could use the window of time we have as AI continues to develop to have a different conversation.
Experiment with Purpose: Yes, test AI tools – and document both what works and what doesn’t to both create more effective learning and performance impact. Note and share your learnings about where human expertise remains essential. These insights help to inform our ongoing adjustments as we continue to deepen our value.
Ask Different Questions:
Instead of: “How can I use AI to create content faster?”
Try: “What human capabilities will matter most in a world of human-AI collaboration, and how do I help others to develop them?”
Instead of: “How do I integrate AI into my current processes?”
Try: “How can I shift what I do and the value I create as I work alongside AI?”
Instead of: “How do I stay relevant?”
Try: “How can I lead conversations about human potential in an AI world?”
Think Strategically: Begin positioning yourself as someone who thinks strategically about human development in an AI world. Small steps to get started:
- Interview three people who’ve recently changed roles about what helped them adapt – then apply those insights to your next programme.
- Map out the human skills your organisation will need to strengthen in the coming two years and identify how you can support development in partnership with others.
- Partner with other functions to explore how people in their teams are adapting to AI-enhanced work.
The Future is Ours to Shape
These ideas from Masie and Cavalier aren’t the only possibilities; they’re examples of the kind of strategic thinking we need more of. They show what happens when we move beyond ‘How do I use this tool?’ to ‘How might our profession take advantage of disruption to evolve?’
It’s clear we have a choice to make about our future role and value; however, I’m not clear about what all the options are. That’s a conversation worth having with the broader L&D community.
What strategic repositioning are you exploring? What questions are you asking that are worth wider consideration? How are you experimenting with new ways to create value?
The future is ours to shape – all the more so if we shape it together.
[i] For a deeper exploration of these shifts see World Economic Forum (2025) Future of Jobs Report 2025
[ii] Donald H Taylor and Eglė Vinauskaitė(October 2024), AI in L&D: Intention and reality
[iii] Elliott Maisie, ATD 2025 session: Beyond AI Fascination. Reskilling, Job Redesign and Career Models.
[iv] Josh Cavalier, ATD 2025 session: Implementation Strategies for AI in Human Machine Performance.
2 comments
Damien Woods
Thanks for the share Michelle. A few additions from me. I’m convinced AI is moving far quicker than most really think, with the likelihood of far more profound changes than most would considering possible. A recent Gallup poll indicated 64% of people are resisting AI as long as they can. This is the biggest danger for me. Its happening, and resistance is a really poor choice. We also need people involved in the ethical conversations, just because AI might eliminate the need for workers, should we allow that outcome or restructure the very nature of work? I think the likelihood of radically changing the role of L&D over the next decade is almost inevitable. We all need to constantly stay focused on what it is we do better than someone else or a bot, and increasingly that will be how we work alongside AI. So time to ditch the resistance, get curious, upskill and focus on how we create more value for our businesses faster than we can do alone. And consider our opportunity to help the rest of the business with this. One final thought, AI will eliminate the need for a lot of learning. I don’t need to learn how to code, AI will do this for me. I can create images without knowing how to take great photos. I can make videos. I can make music. Increasingly we will see the need to learn something made obsolete, as AI will just do it for us.
Learning Uncut
Things are moving so quickly with AI that it’s difficult to stay abreast of what it does well now and what it will do well into the future. When I speak 1:1 with some L&D leaders they tell me about how they are pushing the boundaries and experimenting with AI with their teams, as well as looking to future possibilities. Then in other forums I’m part of people who I trust to have their finger on the pulse share that they think that currently what AI can actually do well for AI is significantly over-hyped. Don Taylor and Egle Vinuskaite’s research is giving us a pulse check on what L&D teams are actually doing right now – and the overall sense I get from their work is that we’re adopting it relatively slowly and mostly within our current view of our role. Like you I do think our role is going to shift dramatically and that we are better getting on the front foot and reshaping it ourselves. This is a conversation I’m keen to keep having, so thanks for continuing to be part of it.