Output: A team working agreement covering ownership, fairness, coaching and review.
Before this: A real or hypothetical team workflow; AI/evidence basics assumed.
Work through the fictional examples and feedback. Short notes are enough.
LecXie suggested study allocations, not provider runtimes or verified learning time. Optional deeper work is outside the total.
0 / 4
Stops marked explored
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Stop 1 of 4
Make the handoffs explicit
Allocate ownership across people and AI-assisted steps.
Journey fit: Start with the prerequisite concepts above. The selected resource supplies context; the local case is where you use it.
Selected resource · Good Work Design and AI Adoption
IFOW · CIPD · University of Warwick
Good Work Design and AI Adoption
What you will learn: Use a qualitative case to ask how design choices affect the work people do.
Why this is worth the time: Grounds a team workflow discussion in eight cross-sector cases. The cases illustrate choices and mechanisms, not universal causal effects.
Before this
A workflow and a question about work quality
Study time
Suggested 25 minutes for one case; 60 minutes to compare selected cases
Access
Public report; no account needed to view the publication page
Self-reported and shared across routes. Source date: 2026-05-18 · Last update: not established · Checked 2026-10-15. Part of this stop’s selected reading.
Selected resource · Navigating the Jagged Technological Frontier
Harvard Business School AI Institute
Navigating the Jagged Technological Frontier
What you will learn: Ask which task and comparison a productivity claim actually tested.
Why this is worth the time: Introduces uneven task performance before you judge evidence for your own work.
Before this
Understand the basic idea of an AI model
Study time
15 min selected reading
Access
Free public research summary; no account needed
Currency / limits
21 Sep 2023; historical consultant study, not a 2026 benchmark
Self-reported and shared across routes. Source date: 2023-09-21 · Last update: not established · Checked 2026-10-15. Part of this stop’s selected reading.
Original local activity · Fictional case
Allocate ownership across people and AI-assisted steps.
A draft moves from a manager to HR and then to an employee. Where should the decision owner be clear?
Apply it to a working example
Use a hypothetical or approved non-sensitive example. Write the team protocol: decision owner, checker, handoffs and escalation.
A self-report of exploration, not verified proficiency. Your work is not sent to LecXie.
Stop 2 of 4
Inspect who gets the opportunities
Include worker preferences, constraints and access in allocation decisions.
Journey fit: Build on Make the handoffs explicit before this activity. The selected resource supplies context; the local case is where you use it.
What you will learn: Organise questions about job effects and what affected workers can tell you.
Why this is worth the time: Useful alongside a workflow redesign. PAI is an industry-participating nonprofit; consult people rather than guessing their experience.
Before this
A workflow and access to affected workers or clearly recorded gaps
Study time
Suggested 30–45 minutes for a bounded assessment
Access
Free web/PDF resource; no account needed
Currency / limits
7 Jun 2023; assessment guidance, not evidence that a particular implementation works
Self-reported and shared across routes. Source date: 2023-06-07 · Last update: not established · Checked 2026-10-15. Part of this stop’s selected reading.
Selected resource · Guidance on AI and data protection
Information Commissioner’s Office · UK
Guidance on AI and data protection
What you will learn: Identify data and accountability questions to take to the responsible specialist.
Why this is worth the time: Adds a UK data-protection lens to the general risk framework. Relevance depends on jurisdiction.
Before this
A candidate task and its information flows
Study time
15 min selected guidance
Access
Free public UK guidance; no account needed
Currency / limits
Under review after the Data (Use and Access) Act; UK-specific
Self-reported and shared across routes. Source date: not established · Last update: not established · Checked 2026-10-15. Part of this stop’s selected reading.
Original local activity · Fictional case
Include worker preferences, constraints and access in allocation decisions.
A scheduler optimises throughput but repeatedly allocates unpopular shifts to the same group. What should the leader do?
Apply it to a working example
Use a hypothetical or approved non-sensitive example. List worker constraints, preferences, burden measures and the route to challenge an allocation.
A self-report of exploration, not verified proficiency. Your work is not sent to LecXie.
Stop 3 of 4
Protect time to learn and review
Build a practice and coaching routine around the changed work.
Journey fit: Build on Inspect who gets the opportunities before this activity. The selected resource supplies context; the local case is where you use it.
Selected resource · Engaging stakeholders in AI
The Alan Turing Institute
Engaging stakeholders in AI
What you will learn: Map affected groups and plan how they can influence design.
Why this is worth the time: Adds a structured participation method to a workflow or change plan; paper can replace optional collaborative-board tools.
Before this
A candidate AI use and affected groups
Study time
Provider range 1–5 hours; suggested 45–60 minute initial mapping, not completion
Access
Free account and enrolment required; optional Miro or paper; no iframe permission assumed
Self-reported and shared across routes. Source date: not established · Last update: not established · Checked 2026-10-15. Part of this stop’s selected reading.
Selected resource · Bridging the AI skills gap
OECD
Bridging the AI skills gap
What you will learn: Distinguish broad AI literacy from specialised skills when planning learning.
Why this is worth the time: Makes the capability plan broader than training people to use a single tool.
Before this
A redesigned task and the people expected to do it
Study time
6-page brief; 10 min suggested reading
Access
Public brief and PDF; no account needed to read
Currency / limits
24 Apr 2025; policy context, not an organisation’s skills assessment
Self-reported and shared across routes. Source date: 2025-04-24 · Last update: not established · Checked 2026-10-15. Part of this stop’s selected reading.
Original local activity · Fictional case
Build a practice and coaching routine around the changed work.
Experts now spend all their time correcting AI outputs while newcomers lose access to learning tasks. What is a useful response?
Apply it to a working example
Use a hypothetical or approved non-sensitive example. Plan a team practice cycle, expert coaching time and a check of retained judgement.
A self-report of exploration, not verified proficiency. Your work is not sent to LecXie.
Stop 4 of 4
Review team outcomes, not adoption
Create a decision agenda that includes work quality and people.
Journey fit: Build on Protect time to learn and review before this activity. The selected resource supplies context; the local case is where you use it.
Selected resource · Impact Evaluation of AI Interventions
HM Treasury · Evaluation Task Force
Impact Evaluation of AI Interventions
What you will learn: Specify a baseline, comparison and outcome measures before starting a pilot.
Why this is worth the time: Connects the earlier notes to a testable pilot rather than a demonstration.
Before this
Task, safeguards, workflow and capability notes from stops 1–5
Study time
20 min selected sections; full guidance takes longer
Access
Free public guidance; no account needed
Currency / limits
Updated 15 May 2026; UK public-sector guidance, adapt to context
Self-reported and shared across routes. Source date: not established · Last update: 2026-05-15 · Checked 2026-10-15. Part of this stop’s selected reading.
Original local activity · Fictional case
Create a decision agenda that includes work quality and people.
Tool usage rises while staff report additional checking and less control. What belongs in the review?
Apply it to a working example
Use a hypothetical or approved non-sensitive example. Write the team review agenda, evidence to gather and one explicit decision threshold.
A self-report of exploration, not verified proficiency. Your work is not sent to LecXie.
A team working agreement covering ownership, fairness, coaching and review.
Assembled from your working notes. Empty sections remain prompts. This is a draft for discussion with the responsible people.
Optional deeper branches
Separate from the core route. Alternatives cover a similar outcome; deeper work extends it. Choose deliberately rather than repeating everything.
Investigate applicable UK data questions with the responsible specialist; replace with local guidance elsewhere. Before this: Inspect who gets the opportunities.
