The sprint acts as a building block for your broader AI strategy. It allows you to test solutions quickly, prove ROI, and create a roadmap for scaling. By starting small and proving value, you reduce risk and set the foundation for sustainable AI adoption.

Absolutely. We offer ongoing support to help you optimise your pilot, scale it into production, and expand into other use cases. Our goal is to ensure your AI investment delivers long-term results.

Yes, if your organisation has the resources and data maturity to support it. Many clients start with a single use case and then expand into multiple parallel sprints once they see initial success.

Success is measured through clear KPIs defined at the start—such as accuracy, efficiency gains, or cost savings. By the end of the sprint, you’ll have a working pilot and measurable evidence of value.

An AI Use Case Sprint is a structured, fast-paced process that takes a high-value business problem and validates an AI solution in just a few weeks. It’s designed to deliver a working pilot quickly while reducing risks and proving ROI before scaling.

Most sprints take between 2–6 weeks, depending on the complexity of the use case and data readiness. This allows us to move fast while ensuring the output is high quality and actionable.

A sprint is focused on rapid prototyping and validation. It’s about testing whether an AI solution can deliver real business value. Full implementation takes this validated approach and scales it into a production-ready system that integrates across your business.

We recommend a mix of business stakeholders, subject matter experts, and technical team members. This ensures the sprint is aligned with business goals while also being feasible from a data and technology perspective.