published
Complete Version 1.0 master document.
Values
Build shared understanding, leadership, ownership and confidence for effective human–AI collaboration.
Dimension version v1.0
Definition
Build shared understanding, leadership, ownership and confidence for effective human–AI collaboration.
Contents
The complete document structure, including its introduction, chapters and closing sections.
—Introduction and source information—V – ValuesThe Values dimension examines the human and organisational conditions through which AI creates durable value: shared literacy, role and team capability, leadership and middle-manager behaviour, transformation-role development, human–AI collaboration, workforce transition, employee experience, open AI use and accountable human–AI/agent work.—Guidance for AssessorsAssess Values through observable work, not declared intent. Triangulate employee and manager interviews with workflow observation, decision records, learning evidence, escalation and override examples, community activity, workforce signals and value narratives. A published policy, training catalogue, champion list or leadership message is evidence V.1V.1 AI Literacy & Shared UnderstandingThe sustainability and scalability of AI transformation cannot be secured through technology investments, policy documents, or isolated awareness sessions alone. The organisation must develop a shared understanding of what AI is, what it is not, where it can create value, where it should be constrained, and how human judgement should continue to opV.2V.2 Leadership Mindset & Role ModelingLeadership mindset is one of the strongest behavioural signals in AI transformation. Employees learn what is genuinely expected not only from strategy statements, but from the questions leaders ask, the uncertainty they tolerate, the evidence they require and the way they respond when an AI-supported decision is challenged.V.3V.3 AI Stewards & AI Champions, AI Center of Excellence & Distributed OwnershipAI capability does not scale sustainably when knowledge, support and learning remain concentrated in a central expert team or a small number of strong users. It needs a distributed network through which local context moves toward central enablement, reusable capability moves back into the work, and recurring questions or failures become organizatioV.4V.4 Employee Experience & Human–AI CollaborationThe success of AI transformation is often assessed through strategy, technology, data, and governance. Yet its long-term durability becomes most visible in how employees actually experience the new way of working. When AI enters the organisation, what changes is not only the toolset or the process design. The meaning of roles, the distribution of dV.5V.5 Value Perception, Evidence Confidence & Narrative IntegrityA critical breakpoint in AI transformation appears when formal evidence, stakeholder perception and organisational narrative move apart. An initiative may create measured impact while employees or sponsors remain unconvinced; the opposite is also possible, with a highly visible use case receiving confidence that its evidence does not support. V.5 t—Dimension Synthesis and Transformation RoadmapThe five Values subdimensions form one human and organisational operating system. Section-level takeaways and prompts are inputs to the synthesis; they do not replace evidence from workflows, decisions, employees, leadership behaviour, capability development, workforce transitions and value experiments. The consulting task is to judge system cohere—Source headers, footers and notes—Practices & playbooksThe practical companion documents linked to this section.—Version historyChanges to this document, separate from the overall framework release history.
Related practices
PlaybookGuidance
Introduction and source information
This chapter is the execution companion to the Values dimension. Where the framework establishes what must be true, these practices establish how to assess it, strengthen it through real work and sustain it after an engagement.
Values
AR-V01
AR-V01 · Role-Based AI Literacy Baseline
Establish the minimum role- and context-aware AI literacy needed for responsible participation before deeper capability pathways are designed in AR-V21 and AR-V22.
Values
AR-V02
AR-V02 · AI Output Sensemaking and Calibration
Give teams a repeatable method to interpret confidence, uncertainty, context sensitivity and limitations before acting on AI outputs.
Values
AR-V03
AR-V03 · Human-AI Override & Escalation Readiness
Build the understanding, confidence and practiced behavior required to act within decision, override and escalation mechanisms defined by Alignment and Architecture & Rhythm.
Values
AR-V04
AR-V04 · Shared AI Language and Living Case Library
Create a small shared vocabulary and a living library of context-rich cases that anchors discussions in observable work.
Values
AR-V05
AR-V05 · Leadership Questioning and Trust-with-Verification
Shift leadership conversations from AI promotion or rejection toward evidence-based questions, explicit boundaries and accountable decisions.
Values
AR-V06
AR-V06 · Psychological Safety, Failure Learning and Visible Leadership Use
Make it safe to question AI-supported work, acknowledge that enthusiasm and workforce anxiety can coexist, and use failures, near misses and visible leader practice to improve the operating system.
Values
AR-V07
AR-V07 · Federated AI Capability Enablement
Use the formal operating architecture as an input and design how the AI Center of Excellence helps value streams build, reuse and sustain capability without becoming a permanent expert queue.
Values
AR-V08
AR-V08 · AI Steward & Champion Network Enablement
Create an AI Center of Excellence (CoE)-supported network in which champions translate and diffuse learning while stewards protect quality, responsible use and issue closure.
Values
AR-V09
AR-V09 · Hero-Dependency & Capability Continuity Review
Identify and reduce fragile dependency on individuals by creating paired capability, succession and independently usable knowledge assets; AR-V25 operates the wider community knowledge flow.
Values
AR-V10
AR-V10 · Human-AI Work and Role Redesign
Redesign a workflow around human and AI strengths while making new decisions, handoffs, controls and accountabilities explicit.
Values
AR-V11
AR-V11 · Cognitive Load and Decision-Friction Review
Reveal where AI and multi-agent work change attention, vigilance, context switching, supervision span, approval load and decision effort, then remove the highest-value friction.
Values
AR-V12
AR-V12 · Employee Trust, Explainability and Adoption-Friction Diagnosis
Understand why employees trust, distrust, work around or abandon AI and provide the operational explanation and support their decisions require.
Values
AR-V13
AR-V13 · Human-AI Performance and Incentive Alignment
Align goals, measures and recognition with team outcomes, sound judgement, verification, learning and appropriate non-use of AI.
Values
AR-V14
AR-V14 · Evidence Confidence & Claim Interpretation
Create shared language for interpreting claims and evidence without recreating the Impact dimension's value hypothesis, baseline, counterfactual, metric, ROI or attribution methods.
Values
AR-V15
AR-V15 · Experiment Decision Trust & Learning Response
Assess how people understand and respond to formal stop, pivot, continue or scale decisions while leaving decision rights to Alignment and evidence criteria to Impact.
Values
AR-V16
AR-V16 · Value Perception & Human-AI Narrative Integrity
Reconcile stakeholder perception with Impact-owned evidence and preserve human contribution, uncertainty and AI boundaries in organizational stories.
Values
AR-V17
AR-V17 · Middle Manager Adoption Gatekeeping & Team Enablement
Develop middle-manager behavior in coaching, workload trade-offs, honest opportunity-and-uncertainty conversations, psychological safety and rapid escalation while using Alignment for strategic message architecture and formal decision rights.
Values
AR-V18
AR-V18 · Workforce Transition, Reskilling and Career Pathways
Connect human-AI work redesign to transparent workforce commitments, protected reskilling, early-career and skill-adjacent pathways, preserved professional tradecraft and fair transition decisions.
Values
AR-V19
AR-V19 · Open AI Use and Shadow AI Learning Loop
Create a non-punitive cultural route for employees to disclose unapproved AI use, unmet demand and near misses, while routing policy and control decisions to the relevant Ethics, Security and Technology owners.
Values
AR-V20
AR-V20 · Agentic Work Supervision Experience
Develop and test the mental model, human behaviors, skills, workload and trust needed to direct and supervise persistent digital actors within boundaries defined by Alignment and the Agentic Operating Model.
Values
AR-V21
AR-V21 · AI Capability & Skills Architecture
Define the capability layers and proficiency evidence required for AI-enabled work without reducing capability to course completion or tool familiarity.
Values
AR-V22
AR-V22 · Role-Based AI Learning Pathways
Turn the capability architecture into differentiated, work-embedded learning journeys for executives, managers, transformation roles, specialist teams and employees.
Values
AR-V23
AR-V23 · AI Transformation Roles Development
Develop AI Transformation Leads, AI Stewards, AI Champions and other transformation roles through explicit profiles, applied assignments, coaching and succession.
Values
AR-V24
AR-V24 · AI Capability Dojo & Practice-Based Learning
Create a Lean, coached environment where cross-functional teams practise discovery, experimentation, evaluation, quality-bar definition, human-AI work design and single- or multi-agent supervision on real cases.
Values
AR-V25
AR-V25 · AI Communities of Practice & Knowledge Flow
Connect communities, role networks and team learning so useful patterns, failures and questions move across value streams and back into central enablement.
Values
PlaybookGuidance
Operating Rhythms
Practices create Values capability; operating rhythms keep that capability visible, exercised and responsive to evidence over time. AR-R17–AR-R21 are learning conversations and Values lenses designed to operate through the organization’s existing capability, leadership, human–AI work and portfolio value and evidence cadences. They do not create a p
Values
AR-R17Rhythm
AR-R17 · Weekly Champion Office Hours
Resolve local questions quickly, surface weak signals and keep champions connected to central expertise. This is a capability-support mechanism, not a governance forum.
Values
AR-R18Rhythm
AR-R18 · Biweekly Community Learning Loop
Convert local experience into reusable capability and reduce dependency on individual experts.
Values
AR-R19Rhythm
AR-R19 · Leadership Values Lens
Model evidence-based questioning, make uncertainty discussable and close executive-to-middle-manager learning loops.
Values
AR-R20Rhythm
AR-R20 · Human–AI Work Values Lens
Inspect total workflow experience, workforce transition, learning conditions, open AI use and agent-supervision load after AI changes.
Values
AR-R21Rhythm
AR-R21 · Value Perception and Evidence-Confidence Lens
Maintain calibrated confidence and credible value perception without duplicating Impact measurement or Alignment portfolio governance.
Values
PlaybookGuidance
90-Day Lean Experiment Loops
The loops below are a starting pattern, not a mandatory linear rollout. Tracks may overlap, repeat or stop early as evidence changes. Limit work in progress, select one or two value streams and adjust the practice set from observed need.
Values
PlaybookTemplate
Minimum Consulting Templates
The following templates define the minimum reusable artefacts for applying the Values practices consistently. They can be implemented in documents, workflow systems, catalogues or delivery platforms as long as the fields and decision intent are preserved.
Values
PlaybookGuidance
Consultant Application Guidance
Place a capability according to the strongest evidence demonstrated consistently across the assessed scope, not the most mature isolated example.
Values
PlaybookGuidance
Source headers, footers and notes
Values
Dimension version history
This history belongs to Values. Overall framework releases are recorded separately in Framework release history.