01AI Strategy, Change & Adoption
Identify where AI can help, decide what needs to change, and give the people involved a practical role in making it work. Connect the business decision to the information, delivery effort, and ongoing support it requires.
When this helps
The work & its outputs
Assess candidate use cases against the business problem, expected value, information available, and practical feasibility. Produce a prioritised shortlist with explicit assumptions and boundaries. Consider rules, conventional automation, and analytics alongside AI, so the chosen approach fits the work.
Map the current workflow and a proposed way of working. Identify what people review, where a solution can assist, and how exceptions move to someone able to decide. Make approval points, escalation paths, and the limits of automation visible before implementation.
Define the sponsor, decision owner, technical counterpart, and subject-matter expert responsibilities. Identify the business knowledge each person contributes, how much participation the plan needs, and who maintains that knowledge. Essential expert input belongs in the delivery plan, with time allocated to it.
Plan practical introductions, role-specific guidance, feedback opportunities, and support. Help users understand what the solution can do, how to check its output, and when to escalate. Training should connect to real tasks and fit the changes in the everyday workflow.
Describe a manageable next delivery increment and its dependencies. Agree how to examine use, usefulness, output quality, and relevant business outcomes. Establish what evidence is needed before extending the scope, without treating a completed prototype or login count as proof of operational value.
Clarify who supports users, reviews issues, updates source knowledge, and approves changes after the initial build. Define a practical rhythm for reviewing feedback and performance. Maintenance and improvement become explicit responsibilities, rather than work assumed to happen on its own.
A useful engagement needs a sponsor who can make decisions, access to relevant process information, and allocated participation from the people who understand the work. Your IT or data counterpart helps establish access and implementation constraints. We agree responsibilities early and make dependencies visible, including decisions that must stay with your organisation.
A sensible first engagement
Start with a business problem or a small set of candidate use cases. Review the workflow, available information, people involved, and important constraints. The review defines a sensible next increment; its scope depends on the decision you need to make.
A team considering a procedure assistant also needs to decide who maintains the procedures, how staff report an unsupported answer, and which questions require an expert. Those workflow and ownership decisions belong alongside the technical build.
A few useful answers
No. A single useful workflow can provide a sensible starting scope. Agree the problem, the people involved, and the evidence needed to decide whether to continue.
Yes. We can organise the work around agreed responsibilities for business decisions, information access, implementation, evaluation, and handover. Your existing environment and team shape the approach.
No. Rules, conventional automation, analytics, and AI solve different problems. The assessment considers which approach is appropriate before committing to an AI solution.
A useful next step
Tell us what you are trying to improve, where your information lives, and what is getting in the way.