Generative AI Team Workflow Redesign Training Course – London, 31 May – 4 Jun 2027
London · 31 May – 4 June 2027
Course Details
- Ref.
- # 942_35634
- Date
- City
- London
- Fees
- 5900 £
31 May – 4 Jun 2027
This Generative AI Team Workflow Redesign Training Course session in London runs from Monday 31 May to Friday 4 June 2027 (week 22, Q2 2027). It is the only date in London in 2027, at a fee of 5,900 £. Registration is open for this date. It is held in person.
- Dates
- Monday 31 May – Friday 4 Jun 2027
- Week
- 22 of 2027
- Duration
- 5 days
- Fee
- 5,900 £
- Status
- Open for registration
- Format
- In person
Generative AI Team Workflow Redesign is a 1-week training course for team leaders, administrators and knowledge workers who share recurring work and it ends with a Team Workflow Redesign Map. Organisations now see assistants arrive in every inbox and spreadsheet, yet few teams have agreed where drafts are machine-assisted, who checks them and which information may be entered. Jupiter Prime Training runs this course on Generative AI Team Workflow Redesign.
Why Generative AI Team Workflow Redesign Matters Now
Three forces shape this subject. Assistants built into office suites have made machine drafting a default rather than an experiment. Clients and auditors increasingly ask how a document was checked, while staff adopt tools faster than shared rules appear. A team that redesigns routines gains faster, traceable work; one that drifts risks leaks and invented facts in client documents. The course draws on the ISO/IEC 42001 artificial intelligence management system standard and the NIST AI Risk Management Framework (AI RMF).
Who Gains Most from Generative AI Team Workflow Redesign
- Leaders who allocate recurring tasks and approve outgoing documents within a unit
- Administrators who run calendars, minutes, correspondence and shared filing
- Analysts who prepare spreadsheets, briefing notes and desk research for decision makers
- Coordinators who own handbooks, templates and standard operating procedures
- Specialists who check quality, records or information handling for a department
The strongest gains come when a leader attends with two or three colleagues from the same unit and tests the new hand-offs on real tasks.
Generative AI Team Workflow Redesign Capabilities
Participants decide which routine steps a model drafts, which a person owns and how output is checked.
- Map a recurring team task step by step and mark candidate points for machine drafting — task owners
- Design prompt templates and reference packs for drafting, summarising and minute-taking — the wider unit
- Apply a source-checking routine to model answers, figures and quotations — reviewers and approvers
- Specify information classes that may or may not enter an assistant — records and security leads
- Build spreadsheet formulas and research digests with assistant support, then test them — analysts and their readers
- Communicate a revised hand-off sequence with clear human sign-off points — leadership and colleagues
Key Generative AI Team Workflow Redesign Terms
- Task decomposition — Breaking a recurring piece of work into discrete steps assignable to a person or a model.
- Prompt template — A reusable instruction with fixed context, tone and format slots that colleagues complete for a recurring task.
- Hallucination — A fluent model statement unsupported by any source, such as an invented figure.
- Grounding — Supplying the model with the specific documents or data it must base its answer on.
- Human sign-off point — A defined step where a named person checks and approves machine-assisted output before it moves on.
- Information classification — Labelling material by sensitivity so staff know what may enter an assistant.
Generative AI Team Workflow Redesign Day by Day
Day 1: Where Assistants Enter Shared Work
- Recurring Task Inventory — Which Routines Consume Most Unit Time
- Task Decomposition Canvas — Splitting Work Between People and Models
- Assistant Capability and Limit Profile — Matching Tools to Task Types
- ISO/IEC 42001 and NIST AI RMF Principles — Framing Team-Level Controls
- Stakeholder Expectation Scan — What Clients and Auditors Will Ask
Day 2: Drafting, Summarising and Minute-Taking
- Prompt Template Library — Consistent Tone and Format Across Colleagues
- Reference Pack Assembly — Grounding Drafts in Approved Source Material
- Long Document Summarisation — Choosing Length and Emphasis for Readers
- Meeting Transcript to Action Minutes — Owners, Deadlines and Decisions
- Correspondence Drafting in Two Sectors — Utilities and Professional Services
Day 3: Spreadsheets, Research and Verification Habits
- Formula and Pivot Assistance — Testing Model Suggestions Against Known Totals
- Desk Research Digests — Separating Sourced Claims From Model Inference
- Source-Checking Routine — Tracing Figures, Quotations and Citations
- Hallucination Pattern Spotting — Red Flags Reviewers Should Catch
- Second-Reader Protocol — Proportionate Checking by Document Risk
Day 4: Information Handling and Hand-Off Design
- Information Classification Grid — What May Enter Each Assistant
- Personal and Client Data Rules — Redaction Before Prompting
- Human Sign-Off Point Placement — Accountability for Outgoing Documents
- Swimlane Hand-Off Diagram — Sequencing People and Model Steps
- Usage Log and Disclosure Note — Traceability for Reviewers and Clients
Day 5: Practising the Team Workflow Redesign Map
- Live Redesign of a Participant Routine — Applying the Decomposition Canvas
- Template and Reference Pack Trial — Applying Drafting Methods to Real Tasks
- Verification Drill on Sample Outputs — Applying the Source-Checking Routine
- Time and Error Baseline — Measures to Compare Before and After
- Team Workflow Redesign Map — Hand-Offs, Checks and Data Rules Agreed
Applying Generative AI Team Workflow Redesign After the Course
- Run a two-week trial of one redesigned routine using the swimlane hand-off diagram and record time and error baselines.
- Publish the unit's prompt template library and information classification grid, then hold a short review of first usage logs.
Generative AI Team Workflow Redesign Questions (FAQ)
What is Generative AI Team Workflow Redesign and why does it matter now?
Generative AI Team Workflow Redesign is the deliberate reshaping of shared routines so that assistants draft where useful and people check where it counts. It matters now because assistants are already built into everyday office tools.
Which roles gain most from Generative AI Team Workflow Redesign?
Team leaders, administrators and analysts gain most from Generative AI Team Workflow Redesign. They own recurring documents and decide who approves what leaves the unit.
How does Generative AI Team Workflow Redesign differ from a personal productivity course?
Generative AI Team Workflow Redesign works at unit level rather than on individual tips. A personal productivity course improves one person's prompting; this course agrees shared templates, sign-off points and data rules.
What do you bring back from Generative AI Team Workflow Redesign?
You bring back a redesigned routine ready to trial. It includes a hand-off diagram, templates, a checking routine and baseline measures.
Generative AI Team Workflow Redesign: The Way Forward
The Team Workflow Redesign Map sets out which steps an assistant drafts, which a colleague checks and which information stays out of prompts. It first informs which routine to trial, and the unit leader and approvers use it daily. After the first trial, revisit the sign-off points, since checking effort often differs from expectations.
Generative AI Team Workflow Redesign Training Course
Ref. 942_35634Generative AI Team Workflow Redesign Training Course runs in London over 5 days, with 1 upcoming date in London. The course fee is 5,900 £.
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| Dates | Price | Actions |
|---|---|---|
| 31 May – 4 June 2027 This session | 5,900 £ | Register |
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London, 31 May – 4 June 2027. The fee is 5900 £ per delegate.