Where to invest in AI — and what to ignore
A scored, prioritised AI roadmap built around your actual constraints — budget, team, and regulatory context — with AWS-funded discovery for qualifying customers.
The Challenge
AI investment decisions get made on enthusiasm, not evidence. The result is a portfolio of pilots with no production builds and a board that's losing patience. Without a scoring framework, spend follows the loudest voice in the room — not the use case with the clearest return.
Too many options, no framework
Every vendor, every conference, every article points at a different use case. The team chases the shiny thing. The backlog fills with AI initiatives that have no owner, no budget line, and no agreed definition of success.
Fix
What's missing is a scoring model — one that weights value against complexity, ROI against regulatory fit, and ambition against what the team can actually deliver in the next six months.
Pilots with no production path
The team builds a proof of concept that demoes beautifully. Then it sits. Nobody owns the path from notebook to production, and the use case that looked transformational in a slide deck turns out to be a £40k experiment.
Fix
The roadmap should identify which pilots are worth taking to production before the pilot is built — not after the budget has been spent.
Board pressure, no answer
The board wants an AI strategy by Q2. Without a shared, scored framework, the answer to every one of these conversations is a different slide deck — and none of them are the same.
Fix
A defensible AI roadmap ends that loop. One document. One priority order. One conversation.
A Practical Path
Discovery & use case mapping
Weeks 1–2Structured workshop series to map your AI landscape, surface every candidate use case, and understand the constraints any prioritisation has to respect.
- •Stakeholder interviews across tech, ops, growth and exec
- •Existing AI initiative audit — what's running, stalled, or quietly abandoned
- •Constraint mapping — regulatory, team capability, infrastructure readiness
- •Use case longlist — typically 20–40 candidates across business functions
Output
Longlist agreed. Scoring criteria signed off by sponsor before weighting begins.
Scoring & prioritisation
Weeks 3–4Weighted scoring model applied to every use case. Value, complexity, ROI timeline, regulatory exposure, team readiness, and AWS service fit — each scored and weighted to your context.
- •Value × complexity matrix for every candidate use case
- •ROI modelling for the top ten use cases
- •Regulatory and compliance exposure flagged per use case
- •AWS funding eligibility assessed per use case
Output
Priority list of five to eight use cases agreed. Bottom half explicitly parked with rationale.
Roadmap build & handover
Week 5The prioritised list becomes a living roadmap — sequenced, costed, and mapped to AWS services, with funding eligibility and the first build recommendation already scoped.
- •One-page executive summary for the board conversation
- •Detailed roadmap with sequencing, dependencies, and funding options
- •First build recommendation scoped and ready to move into discovery
- •Handover document: what the roadmap is and when to revisit it
Output
Roadmap signed off by sponsor. First build recommendation accepted or deferred with documented rationale.
What You Get
A defensible AI strategy: Scored against real business constraints — not consultant instinct. The board conversation changes from 'what are we doing with AI?' to 'here's our prioritised investment thesis and why.'
A funded build plan: AWS-funded discovery for qualifying customers means the roadmap often costs nothing to produce and the first build has a funding route before the ink is dry.
Priority, not noise: Five use cases you're explicitly not doing this year — with the rationale documented — so the team can focus on the three they are.
One partner for build: Every solution on the roadmap connects back to a Cloud Combinator build offering. The roadmap and the delivery are in the same hands.
Choose Your Engagement
Funded Discovery
Two-week discovery. AWS-funded for qualifying customers. Scored use case list and costed build proposal.
- • Use case longlist and scoring
- • First build scoped and costed
- • AWS funding eligibility confirmed
Cost
AWS-funded
Duration
2 weeks
Full Roadmap Programme
The complete five-week engagement. Use case mapping, scoring model, prioritised roadmap, board-ready summary.
- • Full stakeholder workshop series
- • Weighted scoring across all candidates
- • Board-ready executive summary
- • First build scoped and AWS-funding assessed
Cost
Fixed fee
Duration
4–5 weeks
Multi-horizon Roadmap
Three-horizon planning for organisations running multiple AI initiatives across business units.
- • Horizon 1/2/3 use case mapping
- • Cross-BU dependency and sequencing
- • Governance model for roadmap maintenance
Cost
Enterprise scope
Duration
6–8 weeks
Related success stories
Right Revenue
From discovery call to a working AI agent in a single AWS AI Accelerator build day.
Funding Xchange (FXE)
A scoped, phased path from pilot to an AWS Summit keynote-stage agentic system.
CentralNest
Architected the AWS foundation alongside the founders from an early stage, then kept scaling it.
Ready for a defensible AI roadmap?
Let's map your AI landscape and build a scored, prioritised roadmap that the board will actually sign off on.
Why talk to us:
Outcome-driven recommendations
AWS-recognised delivery expertise
Risk-aware AI adoption
Clear next step, not a sales pitch
Start with a focused 20-minute conversation about your goals — no pressure, no commitment.