As AI evolves from simple automation to sophisticated autonomous agents, HR executives face one of the most important workforce transformations in modern history. This challenge is more than just understanding technology. Navigate cultural change, skill development and workforce planning when AI capabilities double every six months.
Simon Brown, EY's global learning and development leader, spent nearly two years helping 400,000 employees prepare for an AI-driven future. With past experience as Novartis' Chief Learning Officer and his work at Microsoft, Brown offers important insights into positioning organizations to succeed in the world of autonomous AI.
What top questions do C-Suite executives need to ask their team about the Agent AI initiative?
Do people know what is possible with agents? Are you experimenting with agents to find ways to help us? Do you have the skills and knowledge to do that properly?
But the most important questions are: Does culture support this? Most organizations feel how the tool works, what use cases are, and how to promote value. There are a lot of ambiguities. Some organizations manage well with uncertainty. Others need a clear answer and cannot fail – it is difficult when there is no clear path and people need to experiment.
How can leaders assess whether an organization has the right culture for agent AI?
See how AI tools like Microsoft Copilot are accepted. Are people experimenting and finding the value of productivity, or are they being blackmailed and not using it? If leaders use role modeling and encourage people, that leads to adoption metrics. Culture is displayed through communication, role modeling of leadership, skills building, and learning times.
What are common blind spots when executives assess AI preparation?
Two main issues. First, executives often don't know what is possible with modern AI systems due to security constraints and procurement processes that create delays of 6-12 months.
Second, the speed of improvement. If you try out AI tools a month ago and today, you could have a completely different experience, as the underlying model has been improved. Copilot currently has GPT-5 access and offers a massive overnight boost. Leaders need to move from thinking about AI to something that constantly improves and doubles every six months as static systems are upgraded annually.
How should leaders approach change management using AI agents?
Change management is essential. When Openai releases new features, everyone has access to technology. Whether an organization benefits depends entirely on change management, including culture, experimental abilities, skills, and whether people feel encouraged rather than fear. I work on this through AI badges, curriculum and enterprise-wide learning.
What is your framework for assessing whether AI investments promote real business value?
I'm thinking about three loops. First, can you use this to make your current task cheaper, faster and better? Secondly, can we realize new value that will serve more customers, new products and services? Third, if everyone is using AI, how do you reinvent yourself to create new value? It's not only doing the same thing better, but it's moving, so that AI can help us do it differently.
How should HR leaders rethink their workforce planning, taking into account the possibility that AI will automate job functions?
Understand which skills AI affects. This is unique to humans and understands what new roles are created. The World Economic Forum predicts a significant decline in certain roles, but overall net increases. New, more sophisticated roles are being created that will drive people higher in their value chains.
From an HR perspective, is the process fit for AI speed? How do you encourage reskills? Do you ensure access and time learning? How do you tell us which skills are in demand and the risk of automation?
How should HR measure success after implementing agent AI?
Why it was implemented – Return to business value. I'll use the same metrics as before, but look at what's changed. Probably the same output, but cheaper, faster, better. Or new features – Our third-party risk teams use agents to provide a much broader range of supplier analytics than before. Same team size, more client value.
What is your timeline perspective on when Agent AI becomes the need and benefits of competition?
That's the ultimate question. Every day I am amazed at how I achieved it using AI and agents. The recent features of ChatGpt-5 are astounding and quickly suggest dramatic effects. But it is understandable why leaders struggle to navigate this landscape when deep AI experts have a very different view from AGI decades away.
