Identify the specific problem worth solving
Begin by selecting a workflow or task where AI or automation could make a meaningful difference. Look for issues such as slow response times, repeated data entry, or information that is difficult to access. Engage the people who perform the work to map the current process, identify where time or quality is lost, and define what a useful improvement would look like. This initial step ensures the project has a measurable purpose, such as reducing enquiry response times or improving handover completeness.
Assess existing tools and data readiness
Before considering AI models or vendors, review your current software systems and data quality. Understand how data flows between systems, what access permissions exist, and where human decision points occur. This assessment helps determine whether simpler automation or process improvements might suffice. If AI is appropriate, it informs the scope of a focused pilot, including acceptance criteria and support needs. Clear scoping here avoids overambitious projects and aligns expectations.
Define measurable outcomes and pilot scope
Establish clear metrics to evaluate success, such as task completion rates, time saved, or error reduction. Design a pilot that tests the AI solution on representative cases, including handling missing information or questions outside the agreed scope. Include plans for staff review, escalation, and fallback to human intervention where necessary. Tracking these measures during the pilot provides evidence to decide whether to expand, refine, or reconsider the approach.
Plan for integration and ongoing support
Consider how the AI solution will connect with your existing workflows and systems, including handling duplicate records and integration failures. Define roles, responsibilities, and processes for monitoring, updates, and issue resolution after launch. This planning ensures that the AI tool works reliably in everyday use and does not depend on a single individual’s enthusiasm.
Engage your team with training and feedback
Prepare your staff to use the AI tool effectively by training them on real tasks, including how to give clear instructions, check outputs, and recognise when to escalate issues. Develop simple guidance and escalation paths to maintain consistent use. After rollout, gather feedback and review performance metrics regularly to identify opportunities for improvement and ensure the tool continues to deliver value.