AI Adoption Sprint

Stalled AI pilots are rarely a technology problem.

Teams everywhere have tested AI tools. Most pilots have stalled, not because of the technology, but because roles, inputs, and success criteria were never defined. Risk owners received neither decision support nor clear assessments. The result: pilots that produced learnings but never scaled.

The gap is not technology. It is structure, roles, and a process that makes it possible to say yes.

What you get after 4 to 12 weeks

Risk mapping. AI use cases mapped and classified by risk level (EU AI Act). Gap analysis against your existing policies and controls. Clear view of which use cases are ready to pilot.

Adoption and governance model. Role descriptions: who decides, who reviews, who implements. Approval flow that fits your existing review processes. Data handling policy for AI tools. Vendor evaluation guidelines.

Use case prioritisation. Prioritised backlog based on business value, risk, and feasibility. Quick-win use cases ready to pilot within 30 days. Long-term roadmap with clear decision points.

Pilot plan. Detailed plan for 1 to 3 priority pilots. KPIs, timeline, and resource needs defined. Governance check before, during, and after pilot.

EU AI Act: what every organization needs to know

The EU AI Act classifies AI systems by risk level, and its transparency obligations take effect on 2 August 2026. For many organizations that means AI used in customer-facing communication, decision support, and content production may require documented routines, risk assessments, and human oversight.

Organizations preparing now are building an advantage. Those who wait risk having to retrofit governance onto live AI initiatives under time pressure.

The sprint gives you that structure, adapted to your organisation's size, maturity, and risk appetite.

Who the sprint is designed for

Designed for teams that already have AI on the agenda but lack a model to move on it:

• Marketing and Communications: Streamline content production and customer engagement with AI without losing control.
• Operations and Digital: Turn scattered AI experiments into a governed, scalable capability.
• Risk, Legal and Compliance: Get decision support for AI policies and risk management.
• Leadership and Transformation: Build an organisation-wide strategy for responsible AI adoption.

Sprint, not project

We believe in progress in weeks, not months. The sprint combines workshops, analysis, and implementation in short, intensive cycles:

1. Weeks 1 to 2: Discovery. We map your current AI usage, your risk and compliance requirements, and your organisational maturity.
2. Weeks 3 to 6: Design. We build the adoption and governance model, prioritise use cases, and design the pilot plan.
3. Weeks 7 to 12 (optional): Pilot. We support execution of 1 to 3 pilots with hands-on coaching.

Each phase ends with a concrete deliverable and clear view of next steps.