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The AI Team Redesign Lab™
Rethinking Tasks, Roles and Workflows to Build More Effective Human \+ AI Teams
Download Course BrochureFlexible delivery options to suit your leadership team and organisational needs.
Duration
5 Days
Certificate
Executive Certificate
Level
Manager / Emerging Leader
Format
In-Person / Virtual
Delivery Mode
Instructor-led Workshops, Discussions, Case Studies, Simulations
Online
Date: 23rd – 27th Nov 2026
Location: Virtual
Fee: £3,495
Online
Date: 30th – 4th Nov 2026
Location: Virtual
Fee: £3,495
Online
Date: 2nd – 6th Nov 2026
Location: Virtual
Fee: £3,495
In Person
Date: 23rd – 27th Nov 2026
Location: London
Fee: £4,495
In Person
Date: 30th – 4th Nov 2026
Location: London
Fee: £4,495
In Person
Date: 2nd – 6th Nov 2026
Location: Dubai
Fee: £4,495
In Person
Date: 9th – 13th Nov 2026
Location: Madrid
Fee: £4,495
Online
Date: 21st – 25th Dec 2026
Location: Virtual
Fee: £3,495
Online
Date: 28th – 1st Dec 2026
Location: Virtual
Fee: £3,495
Online
Date: 7th – 11th Dec 2026
Location: Virtual
Fee: £3,495
Introduction
AI creates the greatest value when organisations rethink the work itself rather than simply add technology to existing processes. This practical programme equips managers to examine how work currently happens across their teams and redesign tasks, workflows and responsibilities around the best combination of human and AI capability. Participants identify what should remain human-led, what can be AI-assisted or automated and what should be redesigned entirely, creating a practical future-state model for their own teams.
Middle & Experienced Managers
Functional & Departmental Managers
Operational & People Managers
Managers Leading AI & Workforce Transformation
Participants will leave the Programme with stronger strategic capability and practical approaches that can be immediately applied within their organisations.
Understanding existing team work before introducing AI
Identifying tasks suitable for augmentation, automation or redesign
Designing effective Human \+ AI workflows
Rethinking roles, responsibilities and capability requirements
Testing whether redesigned work genuinely improves performance
Map how work is currently performed across your team
Identify where AI can create meaningful value
Decide what to retain, augment, automate or redesign
Build effective Human \+ AI workflows and responsibilities
Translate redesign into practical implementation
Work & Task Diagnosis
AI Opportunity Assessment
Human \+ AI Work Design
Roles, Skills & Accountability
Future-State Team Design
Core Areas
Understanding why AI adoption should begin with work, not technology
Defining the outcomes the team exists to deliver
Mapping current team activities and workflows
Breaking work into tasks and decision points
Understanding where time, effort and expertise are currently used
Identifying duplication, bottlenecks and low-value activity
Distinguishing necessary work from inherited ways of working
Building the current-state team work map
Understanding different forms of AI contribution to work
Identifying tasks AI can assist or augment
Identifying potential automation opportunities
Recognising activities that should remain predominantly human
Assessing repetitive, analytical and knowledge-intensive activities
Evaluating opportunity against value, complexity and risk
Avoiding automation of fundamentally poor processes
Building the team's AI opportunity portfolio
Moving from individual AI use to integrated work redesign
Determining the optimal contribution of people and AI
Redesigning end-to-end workflows
Defining Human-to-AI and AI-to-Human hand-offs
Identifying points requiring human judgement
Establishing review, verification and exception handling
Removing unnecessary steps rather than simply digitising them
Building the future-state Human \+ AI workflow
Understanding how workflow redesign affects roles
Identifying tasks that may reduce, expand or disappear
Identifying new responsibilities created by AI
Determining emerging human capability requirements
Assessing team reskilling and upskilling needs
Clarifying ownership for AI-supported outputs
Maintaining human accountability for critical outcomes
Developing the future team capability model
Testing whether redesigned work creates measurable value
Comparing current-state and future-state performance
Identifying implementation risks and dependencies
Selecting appropriate activities for pilots
Defining success measures and performance indicators
Gathering employee feedback and learning from implementation
Refining and scaling successful redesigns
Developing The AI Team Redesign Lab™ implementation roadmap
Register your interest and we'll let you know when new dates become available.