dorsal

Methodology

From use cases to an AI adoption roadmap.

We start with how your organization works, identify where AI could add value and build a plan for adoption. A proposed phased approach with clear decisions, owners and deliverables.

Decide. Validate. Adopt.

How we work

We begin with leadership and the teams involved to agree business objectives, scope and access to information. The following approach is adapted to each organization’s maturity.

  1. Assessment and use-case mapping

    Review processes, tools and existing AI uses. Map opportunities by function: the problem to solve, intended users, data requirements and expected business improvement.

    With your team
    Interviews with owners and teams, existing processes and available tools.
    Deliverable
    A maturity assessment and use-case map, including needs, owners and dependencies.

  2. Prioritization and adoption roadmap

    Assess business contribution, feasibility, effort and risk. Decide which cases to validate first and what each initiative needs before moving forward.

    With your team
    Alignment on priorities, team capacity and available resources.
    Deliverable
    A prioritized portfolio and phased roadmap with milestones, owners and progression criteria.

  3. Pilot design and validation

    Define a bounded pilot for selected cases: required data, tools, human review and evaluation criteria. Support validation with business and technical teams.

    With your team
    A business owner, intended users and the relevant technical teams or providers.
    Deliverable
    A pilot brief and assessment against the baseline, with a recommendation to continue, adjust or stop.

  4. Adoption and ongoing review

    Support the transition from validated pilots to everyday work. Agree usage guidance, training and oversight; review each initiative’s contribution and update the roadmap.

    With your team
    Team participation, system owners and leadership decisions.
    Deliverable
    An adoption plan, usage guidance and tracking of outcomes, risks and outstanding actions.

LEADERSHIP AND OVERSIGHT

Leadership connecting business and teams.

The fractional CAIO coordinates the roadmap with leadership and department owners. Teams contribute their expertise and take part in validation; technical specialists and providers participate as needed. Implementation scope is agreed for each initiative.

Ongoing review with clear decisions.

At agreed reviews, we assess progress, outcomes and incidents. Decisions and next actions are documented: which case moves to a pilot, what needs adjustment and what is ready for wider adoption.

Oversight and transparency at every stage.

System inventories, ownership, human review and decision records are integrated from the start. New expectations for oversight and transparency become concrete practices proportionate to each AI use.

European context

European framework for artificial intelligence ↗

Let’s discuss your project