The Agentic Organisation: How AI–Human Collaboration Is Redefining Work, Leadership, and Performance.
Digital HR Leaders with David GreenShow Notes
As we begin a new year, it’s natural to reflect on what’s changed - and what’s quietly no longer fit for purpose.
AI investment is accelerating at pace, and autonomous and semi-autonomous agents are moving from experimentation to everyday work. And yet, many organisations are still operating with leadership models, workforce structures, and planning assumptions designed for a world where humans were the only actors in the system.
In this episode of the Digital HR Leaders podcast, David Green is joined by Sandra Durth, Partner at McKinsey & Company, to explore what happens when work is no longer just human-to-human, but human-to-agent - and what that means for the future of organisations.
Drawing on McKinsey’s latest research, Sandra shares her perspective on:
How AI-human symbiosis is reshaping the very definition of work Why traditional hierarchies and leadership models are starting to break down What “agentic leadership” really looks like in practice The implications for performance, management capability, and strategic workforce planning The biggest opportunities - and the biggest risks - HR leaders need to be paying attention to right now
Links to research: The agentic organization: Contours of the next paradigm for the AI era Six shifts to build the agentic organization of the future
Rethink management and talent for agentic AI Hosted on Acast. See acast.com/privacy for more information.
More from Digital HR Leaders with David Green
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Your organisation has committed to an AI strategy. But what does that commitment mean for the people who have to work differently because of it?
What if the thing slowing down AI in HR isn't the technology at all, but the way the function is set up to deliver it?
As AI reshapes work, the people function has an opportunity to play a much bigger role in how organisations navigate the transformation. At Snowflake, that starts with trusted data, strong people analytics and a clear view of what technology should automate, where it should augment human capability, and what should remain human.