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AI Strategy & Applied Transformation.
Advisory and selective implementation capabilities spanning AI strategy, governance, applied use cases and enterprise adoption, extending PROLOGUE's strategic and commercial advisory to decisions on artificial intelligence.
Decide, build, adopt.
Each AI decision is evaluated as an investment, with value, cost and risk made explicit before a programme scales. Clients engage a single stage or move through all three.
AI Strategy & Governance
- Assess
- Prioritise
- Govern
- Organise
- Assure
For leadership teams deciding where AI creates value, how it should be governed and why an existing programme has stalled. The work is advisory-led and vendor-neutral.
- AI strategy and value assessment: prioritised use cases, data and platform readiness, business cases and a roadmap for leadership approval
- AI governance: policy, risk register, model inventory, approval workflow and responsible-AI guidelines aligned with the Digital Personal Data Protection Act
- AI operating model: ownership, funding and approval of use cases, the role of a central team and the metrics that track value
- AI programme health check: budget, adoption, governance and platform choices, with a practical recovery plan
Prioritised AI use cases, investment cases, organisational readiness and a roadmap for leadership consideration.
Applied AI for Industry
- Prove
- Build
- Integrate
- Run
- Scale
For industrial and mid-market companies moving from an AI idea to a working application on their own data. PROLOGUE structures and leads selected applied-AI programmes, working with specialist technology practitioners and delivery partners where implementation capability is required.
- Proofs of value: a working prototype on the client's own data for one priority use case, with measured results
- Industrial use cases: demand forecasting and inventory, procurement, quality and yield, and predictive maintenance on plant and ERP data
- Workflow automation: AI agents and automation for procurement, finance, customer service and document-heavy processes
- Data foundations: data pipelines, dashboards and quality controls that applied use cases depend on
A focused proof of value, measured outcomes and a scale-up plan to inform subsequent investment.
Enterprise AI Adoption
- Assess
- Plan
- Adopt
- Embed
- Measure
For organisations that have invested in AI platforms, pilots and licences and need the value to show up in everyday work.
- Adoption strategy: role-based use cases, priorities and a rollout plan
- Operating-model change: AI built into planning, delivery and review, with new roles and ways of working where needed
- Capability building: leadership alignment, champions networks and practical enablement for teams
- Value tracking: programme governance, objectives and benefit tracking so each initiative reports measurable results
Role-based applications, internal capability development, adoption measures and value tracking.
Industry-focused AI applications.
Industry experience in chemicals, industrial products, manufacturing and automation informs applications involving plant, ERP and supply-chain data.
How AI mandates are run.
Commercial lens
Use cases are assessed on value, cost and risk, in the same terms as any other significant commitment.
Vendor-neutral
No platform to sell. Recommendations follow the business case and the client's existing technology estate.
Proof before scale
Applied work starts with a defined proof of value, and further investment follows measured results.
Specialist partners
Technology practitioners and delivery partners are brought in where implementation capability is required, with scope and responsibilities agreed for each engagement.
AI advisory is a specialist capability within PROLOGUE Advisory, alongside the firm's four core advisory capabilities. Implementation work is undertaken selectively. Scope, timelines and fees are agreed for each engagement.
Discuss an AI mandate.
Mandates may begin with a use-case question, a governance requirement, a stalled programme or an adoption challenge.