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AI roadmap

AI roadmap & use-case prioritisation

Turn diffuse ideas into a defensible plan — workshop, scoring, prioritisation, .

You have several ideas where could help — but which one is actually worth it? And in what order? Without a clear , initiatives drain away into pilots that never go to production.

We evaluate your systematically by effort, value, data readiness and strategic relevance. Which workshop method we use depends on the maturity of your topic — for fuzzy starting points, under time pressure, for clear with sprint logic.

The result is not a 50-page document, but a prioritised plan with concrete next steps — first, strategic projects after, with dependencies and risks transparently documented.

Process4 steps at a glance

  1. workshop

    Method matched to maturity — , or , supported by canvas tools.

  2. Scoring & evaluation

    , or — every rated by effort, value, data readiness and risk.

  3. Prioritisation

    Effort/value matrix, dependencies, stakeholders — ordering with a rationale per position.

  4. & plan

    Living document with quarterly horizons, , budget range, risks, .

How we get to the roadmap

The workshop is the foundation of the roadmap. Which method we use depends on where your AI topic currently stands — fuzzy, accelerated or mature.

Three main approaches we combine based on maturity:

  • Design Thinking — when the AI topic isn't even in its infancy yet. We open up the possibility space together: identify personas and stakeholders, collect pain points, generate ideas divergently and then converge them at the end. The outcome is the first tangible use cases — grounded in real needs, not in tools.
  • Lean Management / Lean Startup — when time is short and results need to come fast. We compress a use case into a Minimum Viable Product, validate it with real users, and only plan the next steps based on what actually works. Hypotheses instead of assumptions, measured rather than believed.
  • Agile methods with backlog & sprints — when the use cases are already clear enough to translate into backlog items. Led by an experienced Scrum Master, use cases get prioritised, cut into sprints and equipped with a Definition of Done. Particularly useful when first prototypes are to emerge alongside the concept work.

Supporting tools depending on the setting:

  • Value Proposition Canvas — when the value to internal or external users needs to be precisely demarcated
  • Business Model Canvas — when AI usage affects the business model itself
  • Service Design Blueprint — when end-to-end processes with multiple touchpoints are involved
  • OKR framework — when the roadmap needs to tie back to overarching quarterly goals

The workshop format runs one to two days depending on complexity, on-site or remote. The output is a structured collection of use cases with clear descriptions, affected stakeholders, data requirements and expected value — the basis for the scoring step that follows.

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Every use case goes through structured use-case scoring — no gut feel, no political volume. Which model we use depends on the case.

Scoring frameworks in the toolbox:

  • ICE score — Impact × Confidence × Ease. Pragmatic, fast, well-suited for manageable use-case inventories
  • RICE — Reach × Impact × Confidence × Effort. Useful when use cases affect different numbers of users
  • WSJF (Weighted Shortest Job First) — when speed of value delivery is the main factor
  • Custom scoring — when industry- or company-specific criteria (compliance, collective agreements, customer proximity) need weighting

Concrete criteria that feed into the scoring:

  • Expected time savings — hours per week, FTE equivalents, processing throughput
  • Degree of automation — fully automatic, partially automatic, or assistive only
  • Data availability & quality — present, normalised, complete, possibly needing consolidation
  • Technical integration effort — API-ready, custom integration, new systems required
  • Organisational prerequisites — training, change management, role adjustments, works council
  • Business value — ROI estimate with payback time (range, not point)
  • Compliance aspects — GDPR, AI Act, industry-specific regulations

Every criterion is weighted transparently — you see not just the result but also why one use case ranks above another. That makes the scoring traceable internally and defensible politically.

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Effort/value matrix

From the scoring comes an ordering — and it is more than a points-sorted Excel sheet. Three factors decide which use case actually starts next:

1. Effort/value matrix in four quadrants:

  • Quick wins (low effort, high value) — start immediately, they build trust and budget for the next steps
  • Big bets (high effort, high value) — strategically important, plan carefully, often as a multi-sprint project
  • Fillers (low effort, low value) — good for gaps in a sprint, not as the main topic
  • Time sinks (high effort, low value) — deliberately not tackled, communicated honestly

2 . Dependencies and ordering logic:

  • Which use case needs which groundwork? (consolidate data, connect a system, run training)
  • Which platform building blocks emerge that serve multiple use cases? (e.g. a RAG system that later feeds several agents)
  • Where are the organisational bottlenecks? (change management before tool rollout)

3 . Acceptance and stakeholders:

  • Who benefits visibly? Quick wins in departments with high visibility create pull
  • Who could block? Engage early, take reservations seriously
  • What can be shown before the next quarterly report? Political reality is part of the roadmap

The output is a justified ordering — not a list, but a list with a rationale per position. That keeps the roadmap readable six months later, when no one remembers the workshop context anymore.

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Use-case scoringEffort/value matrix

Sounds interesting?

Let's talk it through in a free intro call and see how this would work for you.

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