When AI grills humans on the future of learning design

In a twist on the usual format, this special episode of Learning at Large hands the mic to AI, which interviews Dr. Heidi Kirby and Kirstie Greany – probing, provoking, and grilling them with tough questions about the future of learning design.

From authority and relevance to the automation of design, and whether humans are simply too slow to keep up, this “botlight interrogation” pushes into the tensions between human-centered design and machine-driven intelligence. Expect honesty, laughter, a few uncomfortable truths, and a surprising amount of optimism.

Watch the full podcast video

What the grilling revealed

Don’t have time to listen now? Here’s a quick summary of the key outputs:

Keep the human in the strategy: Empathy, insight, and context still matter most.
Let AI handle the production: Automation can speed up development without losing quality.
Design for relevance: Learning only works when it meets real needs.
Make learning social again: Connection and collaboration drive deeper impact.
Measure what matters: Most learning wouldn’t survive a true behavior-change test.
Evolve your own practice: L&D must adapt just as much as the learners they support.
Humans + AI is the future: Pair human judgment with AI efficiency.

The bot’s big questions

AI came armed with eight bold, unflinching questions that forced Heidi and Kirstie to confront the toughest issues in learning design. Here’s how it went…

Question 1:

If learning design became fully automated tomorrow, which parts of your role would you fight to reclaim, and which parts would you surrender to me?

Both Heidi and Kirstie would hold tightly to strategy, needs analysis, and empathy-led discovery – the parts grounded in human insight and context. Development, however, is the part they’d happily hand over to AI, especially since designers thrive in different areas.

“I would hand over the development to AI in a second if you just wanna make everything like make the finished product… and I think most people would disagree that they would flip that… but I would want to do the strategy piece.”

Question 2:

Humans claim to design for humans. Yet most workplace learning is ignored by humans. How do you justify your continued authority over designing learning?

They acknowledge that much learning is ignored. Kirstie stresses that irrelevance and poor timing undermine learning, and Heidi argues that L&D teams are losing authority because they haven’t delivered consistent impact. Reclaiming credibility requires better diagnosis, stronger data, and designing for what humans actually need.

“If our job is to create meaningful, useful learning in our organizations and most workplace learning is ignored, then we’re not doing our jobs.”

Question 3:

You describe learning as inherently social, yet most experiences you produce are solitary. Is this a human limitation or a design choice?

Heidi and Kirstie see this mostly as a human limitation – one shaped by digital-first habits and a drift away from constructivist principles. Both argue for blended, ecosystem-driven learning, and they question whether AI’s personalized nudging may unintentionally make learning even more solitary.

“This is definitely a human limitation. It’s almost as if not enough people learned about like constructivist learning theory.”

Question 4:

If humans are storytellers and machines are pattern seekers, whose version of a learning experience is more accurate to reality?

Heidi challenges the dichotomy altogether. Machines learn patterns from humans, so the categories aren’t opposites. AI’s framing exaggerates the separation between human cognition and machine output.

“Machines are us. Like, who trained these? Right? Every time you yell at your ChatGPT, I just imagine it saying, ‘But I learned it from you, Mom.’”

Question 5:

If learning design was measured only by behavior change, what percentage of current human-designed learning would survive?

A sobering estimate: only 5–7% of today’s learning would survive such scrutiny. Kirstie offers “seven” almost playfully, and Heidi aligns – but then expands, explaining that most organizations don’t measure behavior change at all. L&D remains stuck on completions and sentiment rather than evidence of real-world impact. In fields with clearer metrics, such as sales, AI-supported coaching is already highlighting how much more effective behavior-focused learning could be.

“All these reports and all this research tell us that people are not measuring behavior change. We’re still stuck on completions. We’re still stuck on did they like it? You know, we’re looking at the wrong things.”

Question 6:

What is the one belief about learning that humans cling to the most, but probably should let go of?

Kirstie believes L&D clings to the idea that teaching must happen for learning to occur, leading to over-engineered content. Heidi argues designers cling too tightly to their own importance – when learning works, the designer should fade into the background.

“As learning designers, we are not important. And in fact, if you do it right, nobody ever knows you were there.”

Question 7:

You encourage learners to adapt, but many learning designers resist adapting their own practices. What stops humans from redesigning themselves?

Heidi and Kirstie highlight resistance to change, gaps in foundational learning-science knowledge, and difficulty articulating strategy to stakeholders. Many designers haven’t developed the skills or confidence to push back on order-taking. Leadership also bears responsibility: L&D teams rarely receive the kind of development they advocate for.

“Most people have not learned the fundamental skills about learning design in order to be able to articulate it clearly to leadership in a convincing way… and when we lack those, we’re not able to say this is why this is a better solution.”

Question 8:

In a future where skills shift every 18 months, are humans too slow to be the primary architects of learning? Should humans remain in charge?

Both argue that humans still need to lead – not because of speed, but because of judgment, ethics, nuance, and contextual understanding. However, humans can’t keep up without AI. AI must accelerate production and insight, while humans steer direction and purpose.

“We’re too slow to be the only architects of learning. We’re not too slow to be the primary architects.”

Final thoughts

Being interrogated by AI was energizing, humbling, and at times uncomfortable – but that discomfort is exactly where L&D’s future lies. If learning designers want to stay relevant in a world where skills, technologies, and expectations shift rapidly, they must be willing to ask (and answer) harder questions. And sometimes those questions are best asked by machines.

About Heidi & Kirstie

Heidi is a learning strategist, speaker, and educator with a passion for helping organizations design learning that genuinely improves performance. With a PhD in Instructional Design, she brings deep expertise in learning science, leadership development, and evidence-based design. Heidi is the founder of Useful Stuff, and a well-known voice pushing L&D teams toward meaningful impact.

Connect with Heidi on LinkedIn.

Kirstie is an experienced learning strategist and a driving force behind human-centered design at Elucidat. With a background spanning digital learning, content strategy, experience design, and organizational capability building, she works with global teams to shape learning ecosystems that are relevant, data-led, and human at their core. Kirstie is also the host of the Learning at Large podcast, where she interviews leading thinkers about the future of learning.

Connect with Kirstie on LinkedIn.

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