Decompose an existing team workflow into discrete tasks and classify each as AI-suited, human-only or hybrid review.
Leadership & Management
Redesigning Team Roles and Workflows Around Generative AI
Equips managers to redesign team structures, role descriptions and workflows so generative AI tools take on defined tasks while people retain accountability and quality control.
🗓️Duration5 training days
📚Content4 modules · 8 sessions
🎓On completionAccredited attendance certificate
About the programme
Course Overview
Many teams have added generative AI tools to existing workflows without changing the underlying roles, so the tools sit alongside old processes rather than reshaping them, and accountability for AI-assisted output remains unclear. This course treats generative AI as a trigger for redesigning team structure, not merely adopting a new tool: decomposing work into tasks suited to AI drafting, human judgement or hybrid review, rewriting role descriptions and RACI matrices to reflect new task allocation, redesigning approval and quality-control steps for AI-assisted output, and managing a change process with a team that may feel threatened or sceptical. Teaching combines live workflow-mapping exercises on participants' own processes, redesigned job description drafting, and a simulated rollout planning exercise. Participants leave with a redesigned workflow map, revised role descriptions and a phased adoption plan ready to take back to a real team.
Expected Learning Outcomes
Rewrite role descriptions and a RACI matrix to reflect new task allocation once generative AI tools are introduced.
Design quality-control and sign-off steps specific to AI-assisted output, including fact-checking and bias review.
Redesign a workflow diagram showing handoffs between AI-generated drafts and human review or approval points.
Identify roles at risk of being hollowed out by redesign and plan redeployment or reskilling before implementation.
Sequence a phased rollout that tests redesigned workflows on low-risk tasks before wider adoption.
Address team scepticism and job-security concerns through transparent communication during workflow redesign.
Who Should Attend
Department heads and team leaders introducing generative AI tools into existing workflows.
Operations managers responsible for redesigning standard operating procedures around new technology.
Human resources business partners updating job descriptions affected by AI adoption.
Change managers leading workflow transformation programmes involving generative AI.
Process owners in shared services, marketing or customer service functions piloting AI tools.
Senior managers who must reassure teams and unions about role changes during AI adoption.
Course Modules
Select any module to see its sessions and points.
01Decomposing Work for AI-Augmented Teams
2 sessions · 8 points
Session 1Task Analysis and Classification
- Break an existing team process into individual tasks using a workflow-mapping technique such as a swimlane diagram.
- Classify each task as suited to AI drafting, requiring human judgement, or needing hybrid human-AI collaboration.
- Identify tasks where AI output carries reputational, legal or safety risk that demands mandatory human review.
- Estimate time and cost currently spent on each task to prioritise which to redesign first.
Session 2Redesigning the Workflow
- Draft a revised workflow diagram showing where AI drafts enter the process and where human checkpoints sit.
- Design escalation paths for cases where AI output falls outside defined confidence or quality thresholds.
- Reduce unnecessary handoffs and approval steps that a redesigned workflow makes redundant.
- Pilot the redesigned workflow on a single task category before extending it across the wider process.
02Redefining Roles and Accountability
2 sessions · 8 points
Session 1Rewriting Job Descriptions and RACI
- Rewrite affected job descriptions to reflect new responsibilities for prompting, reviewing and correcting AI output.
- Update a RACI matrix so accountability for final decisions remains clearly assigned to a named person, not the tool.
- Distinguish roles that shift towards oversight and quality assurance from roles that are substantially reduced.
- Consult affected employees on redesigned role descriptions before finalising them.
Session 2Quality Control for AI-Assisted Output
- Design a fact-checking and source-verification step for AI-generated content before it reaches a customer or decision-maker.
- Build a bias and accuracy review checklist appropriate to the specific AI use case in the workflow.
- Set error-rate thresholds that trigger a review of whether a task should return to fully human handling.
- Assign named accountability for sign-off on AI-assisted deliverables to avoid diffusion of responsibility.
03Managing the Redesign Process
2 sessions · 8 points
Session 1Planning a Phased Rollout
- Sequence a phased adoption plan starting with low-risk, easily reversible tasks.
- Set success criteria and review points before extending redesigned workflows to higher-risk tasks.
- Build contingency plans for reverting to the previous workflow if redesigned processes underperform.
- Coordinate timing of workflow redesign with other concurrent organisational changes to avoid change overload.
Session 2Redeployment and Reskilling
- Identify roles most affected by task automation and plan redeployment before headcount decisions are made.
- Design a reskilling pathway that moves affected staff towards oversight, quality-assurance or exception-handling roles.
- Negotiate redeployment or role change with employee representatives where required by consultation obligations.
- Track redeployment outcomes to demonstrate the redesign process treated affected staff fairly.
04Sustaining Redesigned Workflows
2 sessions · 8 points
Session 1Communicating Change to the Team
- Explain the rationale for workflow redesign transparently, including which roles change and why.
- Address scepticism and job-security concerns using open forums and structured question-and-answer sessions.
- Involve team members in refining the redesigned workflow rather than presenting it as a finished decision.
- Recognise and respond to early signs of disengagement or resistance during the transition period.
Session 2Monitoring and Continuous Refinement
- Track workflow performance metrics such as cycle time, error rate and rework after redesign implementation.
- Hold periodic reviews to adjust task allocation as AI tool capability and team confidence both change over time.
- Capture lessons from the first redesigned workflow to accelerate redesign of subsequent processes.
- Update role descriptions and RACI matrices again as the workflow matures beyond its initial redesign.
What the participant receives
4 course modules
A structured syllabus
8 training sessions
across 5 days
32 detailed points
Applied, detailed content
Accredited attendance certificate
On completing the programme
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