Building an enterprise AI strategy
Our guide.
Read moreExodus A.C.T. Programme
AI strategy that starts with the business
A useful AI strategy is short: the goals, the few workflows that matter most, how you will measure them, and who decides.
What a good AI strategy answers
- Which business goals AI should support
- Which workflows to start with, and why
- Where AI acts and where people decide
- How results will be measured
- How access, data and approved sources are governed
How A.C.T. builds it
The strategy comes from the first three stages: Discover, Assess and Identify opportunities. It is grounded in how your team really works, not in a list of tools.
Related reading
Where this sits in A.C.T.
01 · Discover (this page)
Understand the business, its goals, constraints and how technology is used today. Output: Shared objectives and programme scope.
02 · Assess
Map current workflows, systems, data and team capability, and assess AI readiness. Output: A readiness assessment and a measured baseline.
03 · Identify opportunities
Find and prioritise AI use cases by business value, feasibility and risk. Output: A prioritised opportunity map.
04 · Redesign workflows
Redesign the process before automating it, defining where AI acts and where people decide. Output: Target workflow designs with human checkpoints.
05 · Build / integrate
Configure Base and its apps, or build custom components, and integrate with approved systems. Output: A working solution in a controlled environment.
06 · Deploy
Roll out in phases, with training, access controls and monitoring in place. Output: Live workflows and trained teams.
07 · Measure & optimise
Track agreed measures against the baseline and refine what is working. Output: Performance reporting and a roadmap for the next phase.
Related
The A.C.T. Programme
All seven stages.
Read moreA.C.T. FAQ
Common questions.
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Start the conversation.
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