Engagement Model
AI‑Enabled Organisational Design Engagement Model
Overview
This model treats each pillar as an independent entry point into transformation.
No matter where an organisation begins, the engagement expands naturally across the other pillars, creating a unified, AI‑enabled operating system.
1. Entry Points (Four Pillars)
Each pillar can serve as a starting point depending on organisational maturity, sector, or strategic priority.
| Pillar | Starting Focus | Immediate Benefit | Natural Expansion |
|---|---|---|---|
| AI Operating Models | Integrate AI into strategy, structure, and execution | Clarity on governance, decision‑rights, and measurable AI value | Extends into Adaptive Ways of Working and Strategy Into Outcomes |
| Customer‑Led Structures | Redesign around customer, patient, or citizen journeys | Improved experience, reduced friction, clearer accountability | Expands into AI Operating Models and Adaptive Ways of Working |
| Adaptive Ways of Working | Establish continuous flow and collaboration | Faster delivery, reduced waste, stronger cross‑functional alignment | Connects to Strategy Into Outcomes and Customer‑Led Structures |
| Strategy Into Outcomes | Link strategic intent to measurable execution | Transparent performance, evidence‑based decisions, real‑time insight | Extends into AI Operating Models and Customer‑Led Structures |
2. Engagement Phases
Each engagement follows four scalable phases, regardless of entry point.
Phase 1 — Discovery & Alignment
- Assess current operating maturity and AI readiness
- Identify strategic outcomes and regulatory constraints
- Define success metrics and governance principles
Phase 2 — Design & Integration
- Develop the chosen pillar’s framework (e.g., AI TOM, Journey Groups, Flow Model, Outcome System)
- Integrate AI‑enabled insight loops and orchestration tools
- Establish decision‑rights and accountability structures
Phase 3 — Implementation & Enablement
- Deploy new structures, workflows, and governance models
- Train leadership and teams on adaptive, AI‑supported practices
- Introduce transparent reporting and continuous improvement cycles
Phase 4 — Expansion & Continuous Optimisation
- Extend transformation across remaining pillars
- Embed AI into everyday operations and decision‑making
- Measure impact and refine models based on real‑world data
3. Benefits Delivered
Regardless of starting point, the engagement delivers:
- Strategic clarity — measurable link between intent and execution
- Operational agility — faster, smarter, compliant delivery
- Customer‑centricity — improved experience and trust
- AI‑enabled insight — evidence‑based decisions and predictive capability
- Governance confidence — transparent, regulator‑aligned operations
4. Example Pathways
- Start with AI Operating Models → establish governance → evolve into Adaptive Ways of Working → connect to Strategy Into Outcomes.
- Start with Customer‑Led Structures → improve experience → integrate AI insights → align strategy and delivery.
- Start with Adaptive Ways of Working → achieve flow → embed AI orchestration → expand into customer and strategic alignment.
- Start with Strategy Into Outcomes → clarify goals → connect work orchestration → evolve into full AI Operating Model.
5. Engagement Duration
Typical engagements run 12–24 weeks for MVP, depending on scope and maturity:
- Weeks 1–4: Discovery & Alignment
- Weeks 5–10: Design & Integration
- Weeks 11–16: Implementation & Enablement
- Weeks 17–24: Expansion & Optimisation
6. Executive Takeaway
This model ensures that AI adoption is not a project but a system one that can begin anywhere, scale everywhere, and deliver measurable, regulator‑aligned outcomes.