Chapters 16 and 17 looked at the manager who directs agents and at chains of agents. This chapter looks at the team in which people and AI agents take work from the same queue under one manager. Some of its members can be measured continuously at almost no cost and need no development or care, so their figures easily become the yardstick for the others. The chapter concerns four management functions: M1 Direction, because work is split and allocated between people and agents; M2 Evaluation, because agents' throughput must not become the measure of people; M4 Development, because the tasks people learn on are the ones agents take first; and M5 Care, because no agent notices a colleague in difficulty. The worked example is the team charter for Jana Petersen's claims team at Hansa Mutual.
The phrase that made the mixed team a management topic came from a vendor. Microsoft's Work Trend Index for 2025, based on a survey of 31,000 knowledge workers in 31 markets, describes an "agent boss" as someone who builds, delegates to and manages agents; it reports that 36 per cent of leaders and 21 per cent of employees expect to manage agents, and proposes a "human-agent ratio" for each role (134, Microsoft, 2025). The survey measures expectations, not outcomes.
The research is older and more cautious. Thomas O'Neill and colleagues reviewed the empirical literature on human–autonomy teaming (157, O'Neill et al., 2022). All 76 qualifying articles were simulations, 57 of them military or emergency, mostly one agent with one human. Where compared, human–human teams generally did better. Training people to work with the agent helped, whereas making its reasoning visible improved performance but could also produce complacency and extra workload; the authors suggest having people occasionally perform the agent's tasks themselves. The literature said almost nothing about the learning and need satisfaction of team members. For a line manager, therefore, practice in office and care work is an experiment to be recorded as one, and the unstudied gap is exactly where M4 Development and M5 Care lie.
Primary topics explored
- One manager, two kinds of worker
- Dividing the work
- Two sets of figures
- Handovers
- Recognition and competence
- Development and care
About AI Boss
AI Boss is Book 7 of The Transformed Architecture. It examines what happens when artificial intelligence takes the manager's chair: algorithmic management of direction, evaluation, consequence, development and care, the effects on people, the management of AI agents, Europe's legal answer, and how to design an accountable AI boss, for European enterprises and public authorities.
It builds on the conclusions of Architecture as Code, AI Governance, AI Platform and Security, AI Red Team, AI Threat and The Transformed Security Architect.
Executives, line managers, HR and people leaders, works councils and trade unions, public employers, architects and AI governance leads, data protection and legal officers, procurement and programme leaders, and risk, compliance and audit.
Gunnar Nordqvist
Conceived, directed and published the books of The Transformed Architecture.
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Chapter 18: The Mixed Team: People and Agents Under the Same Manager in AI Boss gives the detailed explanations, practical examples and implementation patterns behind this summary.
This whitepaper belongs to “Managing Machines” and is one of 37 drawn from the manuscript.