How AI is changing work, and what stays human
In the next two years, most employees expect AI to reshape a meaningful share of how they work. The organizations that pull ahead won’t be the ones with the most AI, but the ones that develop and engage their people fastest while the ground shifts. That’s the future this conversation is about.
The urgency is that the language is moving faster than the practice. Six months ago everything was “AI-powered”; now everything is “agentic.” If you’re unsure how much of that is a genuine shift and how much is a label stuck on the same thing, you’re not alone. It was the question at every industry event this year.
Robin Daniels, Andy Roberts, and Nina Carøe sat down for an honest, unscripted conversation about how AI is changing work in practice — and where the human element still decides everything. They cut through the noise on what the technology can do, why most organizations are stuck between trying AI and actually adopting it, and what leaders, managers, and teams can do about it right now.
Key takeaways
- How agentic AI is changing work. Traditional AI hands you information and you decide what to do with it. Agentic AI takes a goal, plans the work, acts on it across your tools, and comes back when it’s done — closer to delegating to a colleague than prompting a chatbot. Andy explains the shift, and why it comes with a real cost model attached.
- Why experimentation isn’t adoption. Individuals are saving hours here and there, but those personal gains don’t roll up into organizational productivity on their own. The gap is design: most companies haven’t yet decided how people and AI work together. In 2026, an AI strategy is no longer optional.
- Clarity and alignment before automation. AI multiplies what’s already there — it makes good teams better and dysfunctional processes worse. Robin and Nina on why you fix the workflow first, get clear on the goal, and only then apply AI. Foundations before you build.
- Treat AI like a team member. You’d never approve a hire without knowing why the role matters. The same discipline applies to AI: define the goal, give it the right access, train it, and give feedback. Delegation, not magic.
- The manager’s role in the change. Change management is hard at the best of times, and this isn’t a new process — it’s a new way of working. How managers can model AI themselves, have honest conversations about how roles will evolve, and help their people find where they add the most value.
- How the org chart evolves. Roles are bundles of tasks we assembled in a world without AI. Nina on why those bundles are being redrawn around value flows — and why work, historically, expands rather than disappears.
Who should watch
CHROs, HR Directors, and L&D leaders navigating how AI is changing work — plus any manager or people leader responsible for bringing a team through this change and turning AI experimentation into real, human growth.
More Human Success in the age of AI
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