Your Next Workforce Won’t All Be Human
AI agents are becoming part of the workforce. The next executive capability is managing them.
Earlier I argued that while AI may recommend, assist or even make decisions, accountability never leaves the human. I still believe that’s true, and I think it will remain true regardless of how capable AI becomes.
I’ve realised that accountability is no longer the most important conversation CEOs need to have about AI. A bigger management challenge is emerging, and I suspect it will become one of the defining leadership issues of the next decade.
The conversation has changed
For the past two years, organisations have measured AI adoption by asking sensible questions. How many employees are using ChatGPT? How many Microsoft Copilot licences have we deployed? How many hours have we saved? How much productivity have we unlocked?
Those questions made perfect sense because AI was largely acting as another productivity tool. Employees used it to write documents, summarise meetings, analyse spreadsheets and brainstorm ideas. AI was helping people do their jobs better, but it wasn’t becoming part of the workforce itself.
That difference is beginning to disappear.
From tools to workers
I’ve noticed three separate conversations arriving at the same destination.
Ethan Mollick argues that AI is moving beyond chat interfaces towards agents that perform work. Jason Ross reaches a similar conclusion, describing agents as systems that pursue outcomes rather than simply responding to prompts. And, Mark Chatterton captured the management challenge in a single observation: “Day 1 was deployment. Day 2 is management.”
Taken together, they describe a much bigger shift than better software. They describe the beginning of a workforce that now includes autonomous digital workers operating alongside people.
That might sound like semantics, but I don’t think it is. Organisations know how to deploy software. They have far less experience managing thousands of autonomous systems making decisions, interacting with customers and completing work across multiple business processes.
Management becomes the competitive advantage
Once AI starts performing work instead of simply assisting with work, the questions change completely.
Instead of asking whether employees are using AI, leaders need to understand where AI is operating, what authority it has been given and how its performance is being monitored. Those are no longer technology questions. They are management questions.
Think about how we manage people today. We recruit them, onboard them, grant access to systems, define their responsibilities, monitor performance, change their roles when required and eventually retire them from the organisation. Every one of those activities is supported by established processes, governance and management disciplines.
Now apply exactly the same thinking to AI agents.
Can you identify every agent operating across your organisation? Do you know what systems each one can access? Do you know who approved those permissions, how their performance is measured and who has the authority to stop them if something goes wrong? Those aren’t just technology questions. They’re questions about security, risk, governance and workforce management. If your CISO, Chief Risk Officer and CHRO aren’t already talking about AI agents together, they probably will be soon.
The Bank of England is already thinking this way
The interesting thing is that regulators are beginning to have exactly this conversation.
Sarah Breeden, Deputy Governor of the Bank of England, argued that existing regulatory frameworks were not built for autonomous AI agents operating inside financial systems. Her concern was not chatbots producing inaccurate summaries or writing poor emails. It was autonomous systems making payments, executing trades and participating in financial markets at machine speed, where the traditional idea of a human reviewing every action starts to break down.
That moves the discussion beyond responsible AI principles and into the practical mechanics of management. How do you supervise autonomous systems? How do you intervene when they behave unexpectedly? How do you recover when something goes wrong? And who has the authority to stop them?
I think that’s an important signal for every executive, regardless of industry. One of the world’s leading central banks is no longer asking whether organisations should adopt AI. It is asking how organisations will manage, control and, when necessary, stop autonomous systems once they become part of everyday operations.
“Our frameworks were not built to contemplate autonomous agents, and relying on a human in the loop for all agent actions is unlikely to be realistic.” - Sarah Breeden, Deputy Governor of the Bank of England
A new management discipline
Every major technology eventually creates its own management discipline.
The internet created digital marketing. Cloud computing created cloud operations. Cyber threats created cybersecurity as a board-level capability. Agentic AI will create something similar, although I don’t think we’ve settled on the name yet.
For now, let’s call it AI Workforce Management.
The label isn’t the important part. The important part is recognising that organisations are gradually building hybrid workforces made up of people and digital workers. The leaders who succeed won’t necessarily be those who deploy the most AI. They’ll be the ones who know exactly what their AI agents are doing, what authority they’ve been given, how they’re’re performing and when human intervention is required.
The next leadership question
When I wrote about accountability earlier this year, I argued that AI could never own responsibility for business outcomes. That remains my view, and I don’t think that principle changes simply because AI becomes more capable.
What has changed is the management challenge sitting above it. If the first question was who is accountable when AI decides?, the next question is who is managing the workforce that increasingly includes AI?
I suspect that will become one of the defining questions for CEOs over the next few years. The organisations that answer it well won’t just deploy AI more successfully. They’ll build an operating model that allows people and digital workers to contribute together, with the right governance, oversight and accountability sitting over both.
Related reading
Day 1 was deployment. Day 2 is management by Mark Chatterton
