Decompose a job into discrete tasks and score each one for generative AI augmentation potential.
Digital Transformation & Artificial Intelligence
Redesigning Roles and Workflows Around Generative AI Assistants
Learn to decompose jobs into tasks, decide which tasks an AI assistant should take on, and rebuild role profiles, workflows and skills plans around that split.
🗓️Duration5 training days
📚Content4 modules · 8 sessions
🎓On completionAccredited attendance certificate
About the programme
Course Overview
Generative AI assistants are landing inside teams faster than job descriptions, standard operating procedures or workflow diagrams can be rewritten, leaving staff to bolt a chatbot onto a role that was never designed for it. This course gives managers and process owners a disciplined method for pulling a job apart into its component tasks, testing each task against what a language model or copilot can reliably do today, and rebuilding the role around that split rather than leaving adoption to individual habit. Participants map current-state workflows, classify tasks by augmentation potential, redraft job profiles and skills matrices, and rewrite standard operating procedures so the assistant's output has a defined place, a named owner and a check step. The course also covers the human side: how to sequence changes so people are not made to feel replaced, how to redeploy freed capacity into higher-value work, and how to track productivity and quality after the redesign rather than assuming the tool alone improves outcomes. By the end, participants leave with a redesigned workflow, an updated role profile and a measurement plan for at least one real function in their organisation.
Expected Learning Outcomes
Document a current-state workflow using swimlane diagrams before proposing any redesign.
Rewrite a role profile to show which tasks a person retains, delegates or reviews.
Build a skills matrix that identifies reskilling needs created by the redesigned workflow.
Draft standard operating procedures that specify prompts, review steps and escalation points.
Sequence a change management plan that addresses staff concerns about displacement and trust.
Design a measurement plan that tracks cycle time, error rate and output quality after go-live.
Who Should Attend
Operations managers redesigning team workflows around AI assistants
HR business partners updating job profiles and skills frameworks
Process owners responsible for standard operating procedures
Team leads introducing copilots or chatbots into daily work
Change managers sequencing AI-related workforce transitions
L&D specialists building reskilling pathways for augmented roles
Course Modules
Select any module to see its sessions and points.
01Mapping Work Before Redesigning It
2 sessions · 8 points
Session 1Task Decomposition and Automation Potential
- Break a role into its constituent tasks using a task inventory rather than the existing job description.
- Score each task against criteria such as data sensitivity, judgement required and error tolerance.
- Distinguish tasks suited to full delegation from those suited to assisted drafting with human review.
- Flag tasks where generative AI output cannot currently meet accuracy or accountability requirements.
Session 2Building the Current-State Process Baseline
- Produce a swimlane diagram of the existing workflow showing handoffs, decision points and delays.
- Capture current cycle time, rework rate and volume so post-redesign gains can be measured fairly.
- Interview task owners to surface undocumented steps that formal process maps usually miss.
- Identify bottlenecks and quality issues the redesign should target rather than automating them unchanged.
02Redesigning Role Architecture
2 sessions · 8 points
Session 1From Task Lists to Augmented Job Profiles
- Rewrite job profiles to separate tasks a person performs, tasks a person reviews and tasks fully delegated.
- Define accountability so an AI-assisted output always has a named human owner before it is used.
- Redraft competency frameworks to add prompt design, output verification and escalation judgement.
- Design career pathways that show how augmented roles progress once routine tasks are automated.
Session 2Skills Matrices and Reskilling Pathways
- Build a skills matrix comparing current staff capability against the skills the redesigned role requires.
- Group staff into reskilling cohorts based on the size of the gap identified in the matrix.
- Design short, task-specific training rather than generic AI literacy sessions with no application.
- Plan redeployment of freed capacity into work the organisation has been unable to resource previously.
03Embedding Assistants into Daily Workflows
2 sessions · 8 points
Session 1Tool Selection and Workflow Integration
- Match assistant capability to task type, choosing between drafting, summarising, coding and research tools.
- Integrate the assistant at the step in the workflow where it removes the most friction, not the first step.
- Set data handling rules so confidential or regulated information is never pasted into an ungoverned tool.
- Pilot the integration with one team before scaling it across the function to surface edge cases early.
Session 2Prompt Libraries and Standard Operating Procedures
- Build a shared prompt library so staff are not each reinventing instructions for the same recurring task.
- Rewrite standard operating procedures to specify the prompt, the review step and the sign-off owner.
- Version-control prompts and procedures so improvements are captured rather than lost in individual habits.
- Define fallback steps for when the assistant is unavailable or its output fails the review check.
04Change, Governance and Measurement
2 sessions · 8 points
Session 1Change Management and Adoption
- Sequence communication so staff hear about role changes from their manager before rumour fills the gap.
- Address displacement concerns directly rather than promising outcomes the redesign cannot guarantee.
- Identify early adopters who can model the new workflow and coach sceptical colleagues informally.
- Set a feedback channel so frontline problems with the redesigned workflow reach the process owner quickly.
Session 2Measuring Productivity and Quality Impact
- Track cycle time, volume per person and error rate against the baseline captured before the redesign.
- Audit a sample of AI-assisted outputs regularly to confirm the review step is genuinely being performed.
- Distinguish productivity gains from simple task-shifting where review work replaces drafting work unnoticed.
- Report redesign outcomes to sponsors using the same metrics agreed before the change, not new ones after.
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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