Because AI can cost far more than earlier IT to deploy and run, relies on cloud computing and can shift spending and risk profiles, the business case analyses value for money from the outset and costs are monitored across the lifecycle. The business case covers infrastructure, data, development, operational and unexpected costs, starts from the do-nothing option and considers the timing of adoption. Evaluation of process, impact and value for money is planned early with a clear purpose, a logic model linking inputs, outputs and outcomes, a log of planned and actual steps, adaptable methods, attention to differences in outcomes between groups, and a defined baseline.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.