Decision guide
How to Build an AI Business Case
Build an AI business case using baselines, value hypotheses, implementation costs, risks and measurable outcomes.
Key principles
Start with the current process baseline: volume, time, quality, cost, delay or lost opportunity.
Separate addressable capacity from guaranteed savings. Not every hour theoretically automated becomes cash savings.
Include implementation, integration, data, support, model/API, governance and change costs.
Decision checklist
✓ Define the baseline
✓ Estimate addressable value
✓ Identify one-off and recurring costs
✓ Set quality and risk thresholds
✓ Define adoption assumptions
✓ Agree how benefits will be measured and approved
How DataLgorithmics approaches the decision
Define the operating problem, identify the evidence required, compare realistic options, establish success and control criteria, and make the smallest justified investment that can answer the decision.