Leading Hybrid Human-AI Teams Training Course for Team Leaders – Milan, 15–19 Feb 2027

Leading Hybrid Human-AI Teams is a 1-week training course for line managers, team leaders and department heads, in which each participant drafts a hybrid team operating charter that sets out who does what between people, AI assistants and AI agents. Assistants and agents now handle drafting, research and routine transactions inside many teams, so the manager's job shifts from allocating tasks to orchestrating people and machines. Jupiter Prime Training runs Leading Hybrid Human-AI Teams for team leaders.

Why Leading Hybrid Human-AI Teams Matters Now

Three forces reshape the team leader's role. AI agents can now complete multi-step tasks such as triaging requests or preparing reports, so roles built around those tasks need redesign. Employees feel both relief and anxiety, and their trust depends on how managers explain changes to workload and recognition. Senior leaders expect measurable productivity gains without loss of quality or accountability. Teams that handle this well free people for judgement, relationships and creative work; teams that handle it badly see duplicated effort, unchecked errors and disengaged staff. The course draws on ISO/IEC 42001 (Artificial Intelligence Management System) and the NIST AI Risk Management Framework (AI RMF).

Who Gains Most from Leading Hybrid Human-AI Teams

• Leaders who allocate daily work and set priorities for a team of specialists
• Managers who run performance conversations, objectives and recognition
• Heads of department who approve new roles and team structures
• Supervisors of service, operations or analyst teams where AI agents handle routine cases
• Project leaders who coordinate mixed groups of staff, contractors and AI tools

Management teams gain most when several leaders from the same department attend together and agree common delegation rules.

Leading Hybrid Human-AI Teams Capabilities

These outcomes shift attention from the tools themselves to the people who work beside them.

• Design role profiles that split tasks between people, AI assistants and AI agents — team members and department heads
• Apply delegation rules that set when AI acts alone, drafts for review or only advises — the team leader
• Build performance measures that credit human judgement as well as AI-assisted output — appraisal conversations
• Weigh workload, wellbeing and skill erosion when AI absorbs routine work — employees and occupational health
• Specify escalation and error-handling routines for agent mistakes — quality owners and customers
• Communicate team changes openly to build trust — staff, representatives and senior leaders

Key Leading Hybrid Human-AI Teams Terms

• Hybrid human-AI team — a working group in which people and AI systems share tasks under one leader's direction.
• AI agent — software that plans and carries out multi-step tasks towards a goal, using tools and data with limited supervision.
• Delegation level — the agreed degree of autonomy given to an AI system for a task, from advise to act.
• Human-in-the-loop — an arrangement where a person reviews or approves AI output before it takes effect.
• Skill erosion — the gradual loss of human expertise when a task is routinely handed to automation.
• Psychological safety — a shared belief that team members can raise concerns or admit mistakes without fear.

Leading Hybrid Human-AI Teams Day by Day

Day 1: The Changing Shape of Teams

• Task Decomposition Mapping — Which Work Suits People, Assistants or Agents
• AI Assistants Versus AI Agents — Capability and Autonomy Differences
• Team Sentiment Pulse — Hopes and Fears About AI Colleagues
• Productivity Baseline Measures — Output, Quality and Cycle Time Before Change
• Leadership Role Shift — From Task Allocator to Orchestrator

Day 2: Redesigning Roles and Delegation

• Role Profile Redesign — Human Strengths in Judgement and Relationships
• Delegation Level Matrix — Advise, Draft, Act With Approval, Act Alone
• Generative AI Workflow Redesign — Handoffs Between People and Assistants
• Agent Task Briefs — Goals, Boundaries and Stop Conditions
• Reskilling Pathways — New Skills for Redesigned Roles

Day 3: Performance, Trust and Wellbeing

• Hybrid Performance Measures — Crediting Judgement Alongside AI Output
• Psychological Safety Practices — Reporting AI Errors Without Blame
• Workload and Wellbeing Checks — Avoiding Hidden Overload
• Skill Erosion Safeguards — Rotating Manual Practice and Review
• Recognition and Career Conversations — Motivation in Changing Roles

Day 4: Guardrails and Accountability

• Responsible Use Guardrails — Data, Confidentiality and Acceptable Use
• Error Escalation Routines — When an Agent Gets It Wrong
• ISO/IEC 42001 and NIST AI RMF for Team Leaders — Accountability Lines
• Change Communication Plan — Explaining Changes to Staff and Representatives
• Productivity Gain Tracking — Evidence for Senior Leaders

Day 5: Practising the Hybrid Team Operating Charter

• Task and Role Split — Applying Day 1 and Day 2 Mapping
• Delegation and Agent Rules — Applying Day 2 Matrix
• People Measures and Safeguards — Applying Day 3 Practices
• Guardrails and Escalation — Applying Day 4 Routines
• Hybrid Team Operating Charter — Presentation to the Department Head

Applying Leading Hybrid Human-AI Teams After the Course

• Run a task decomposition session with the team and agree delegation levels for the ten most frequent tasks
• Add a short AI error and near-miss item to weekly team meetings and track what it reveals over a month

Leading Hybrid Human-AI Teams Questions (FAQ)

What is Leading Hybrid Human-AI Teams and why does it matter now?

Leading Hybrid Human-AI Teams is the practice of managing people who work alongside AI assistants and agents. It matters now because agents already handle routine tasks, so roles, delegation and performance measures must change.

Which roles gain most from Leading Hybrid Human-AI Teams?

Line managers, team leaders and department heads gain most. You benefit if you allocate work, run performance conversations, approve team structures or supervise teams where AI handles routine cases.

How does Leading Hybrid Human-AI Teams differ from a course on AI applications for managers?

Leading Hybrid Human-AI Teams focuses on people management rather than choosing tools. A course on AI applications helps managers select use cases; this one covers role redesign, delegation levels, performance, trust and wellbeing in mixed teams.

What do you bring back from Leading Hybrid Human-AI Teams?

You bring back a hybrid team operating charter. It sets the task split, delegation levels, people measures, guardrails and escalation routines for your team.

Leading Hybrid Human-AI Teams: The Way Forward

The hybrid team operating charter first informs which tasks move to AI assistants or agents and which stay with people. Team leaders, department heads and team members use it to agree delegation levels and performance measures. After the first quarter, revisit its skill erosion and wellbeing safeguards, because the effects on people show more slowly than the productivity gains.