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5 AI questions HR and L&D are stuck on - and how to finally answer them
Date created
August 8, 2026
Last updated:
August 12, 2026
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5 min read
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Table of Content
Article summary
- AI adoption is a people challenge, not just a technology challenge.
- Measure impact, not just AI usage.
- Equip managers to coach change, not just understand AI.
- Make training practical through real tasks, feedback, and new workflows.
Across most organizations, the AI rollout followed a familiar script: IT selected the tools, set up access, and sent out the announcement. Leadership called it a win, and for a while, it looked like one.
Then the real questions started:
- How are employees supposed to leverage AI in their day-to-day work?
- What changes are needed in the current procedures?
- How can managers support their teams in changing their approach?
- And, perhaps most importantly, how will the organization prove the success of its AI investments?
Those questions rarely land with IT. They end up on HR and L&D's desk.
Because AI implementation is not only a technological challenge. It is a human challenge as well, and human challenges do not come with an easy solution. There are always five common questions that keep arising in the process. We asked different HR and L&D leaders how they would approach these questions, and here are their answers.
1. IT has already rolled out the tools. What’s left for us to do?
Dr. Marna van der Merwe, Research & Insights Lead at AIHR, captures the core challenge:
“AI only unlocks value when people actually change how they work. AI is not a technology or a training problem, but a systems problem that requires redesigning the conditions that make new behavior the easiest path.”
The deployment of the technology itself is the easy part. The hard part of making people do things differently falls squarely on HR and L&D.
What still needs to be done by HR and L&D:
- Developing the roles and processes so that the integration of AI in work becomes easy
- Setting behavioral standards, rather than access standards
- Allowing managers to train on AI
- Developing a psychologically safe environment to allow for experimentation
- Measuring usage through behavior, not just logins
2. Leadership wants to see the return from AI investments. What do we report?
Dr. JooBee Yeow, Founder of Learngility & People and Org Director at Notion Capital, explains the shift:
“Leaders invest in AI to improve business performance, not prompt usage. HR needs to make the causal chain visible: AI changes systems, better systems improve execution, and better execution delivers business outcomes.”
Statistics of AI usage can only determine whether AI is helping the company or not. The adoption of AI needs to be judged according to any improvement in speed of processes, errors, decision making, cost, or effect on customers.
The main connection is: AI usage → change in behavior → improved performance → business impact.
3. How do we ask managers to lead AI adoption when they’re already at capacity?
Bernardo F. Nunes, Data & AI Transformation Specialist, summarises the real capability gap: “Managers score well on the strategic side of AI adoption. But they consistently fall short on developing their people’s capability day to day.
"The gap isn’t AI literacy; it’s coaching and change-facilitation. L&D and HR should build that as its own capability.”
Managers don’t have to be AI experts but they need to possess the skills to facilitate changes, give feedback, and develop clear guidelines for their teams to make the best use of AI.
4. We ran an AI training but nothing changed. What did we miss?
Christopher Weggler, People Operations & Innovation Director at commercetools, explains why training alone fails:
“Employees don’t need to understand how AI works. They need to know how to use it. Put people in front of a real problem from their own job and let them build something. That’s what creates behavior change.”
Knowing something does not guarantee a change in behaviour.
Employees require chances to put their skills to use in real business settings. Training could become useless if it is too theoretical and does not relate to any mentoring or feedback process. A better way is to use actual business scenarios and let employees put into practice their AI techniques while getting feedback. Behavior is learned by doing and not by training only.
5. Some of our people are skeptical about using AI. How do we bring them along?
Daria Rudnik, Team Architect and Partner at AI Leader’s Compass, describes the foundation:
“To learn something new, people need to feel it is safe to ask questions, make mistakes, and feel like a novice even when they have vast professional experience."
"You should create a culture where trying, sharing, and improving with AI become part of everyday work.”
Experimentation should be integrated into the learning process for HR and L&D. It is through celebrating small successes, sharing the experience of peers, and reflecting upon what worked well and what did not work that AI transformation becomes more comfortable.
It is not about eliminating skepticism altogether but fostering a curious, experimental and learning-oriented organizational culture.
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Senior leadership and boardroom teams invest heavily in commercial strategies to win market shares. Yet the most important and honest information driving strategy circulates in teams underneath, never making it to the table where decisions are made.Jeroen Kraaijenbrink, Executive Coach and Strategy Consultant at Kraaijenbrink Advisory, has spent years working on what he calls the honesty gap. We sat down with him to understand what the honesty gap actually is, where it lives in organizations, and why fixing it requires a leadership shift.How do you define the honesty gap?There's a narrow definition and a broad one. The broad one is: we have created organizations and systems where it's barely possible to be honest to yourself, about yourself, and honest to other people.Honesty isn't just lying. 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You don't need to be a perfect leader, but you need to be open enough to admit that there is an issue.You talk about the 'persona trap', what is that?You're stuck in a persona where you perform in a certain way within your company. You have a role, a position, a reputation, and that locks you into specific behaviors. The worse the match between who you are as a person and how you need to show up in your organization, the more inner conflict that’s created. Especially at the top, it’s a problem for many executives. They're supposed to be the people who know it all and be decisive. While if you're honest, you don't necessarily know everything, you’re uncertain and have anxieties.The inner core of the honesty gap is breaking the performance, breaking the acting you feel you must do. If you've put yourself in a role of being the strong, decisive, number-oriented leader, that's how you have to behave. 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Frequently Asked Questions
What stops AI adoption in organisations?
Behaviour change, unclear expectations, lack of coaching and missing workflow redesign.
What should HR focus on after IT rolls out AI tools?
Role clarity, behaviour change, manager capability, psychological safety and measurement.
How can managers lead AI adoption without burning out?
Give them coaching tools, simple rituals and permission to deprioritise low value work.
What’s the biggest capability gap in AI adoption?
Coaching and change facilitation not AI literacy.