Defined purpose
Every AI use starts with a named business purpose, decision owner and success measure. Project 360 avoids adding AI where clear rules, improved process or standard reporting solve the problem with less risk and cost.
Client ownership and choice
Architecture decisions support client control of business data, configuration and operating knowledge. Third-party model and platform dependencies stay visible. Designs include practical export, replacement and exit paths.
Human oversight
People remain accountable for business decisions. Higher-impact actions need stronger review, approval and audit controls. AI output is treated as a supported recommendation unless an approved rule permits a bounded automated action.
Data use
AI services receive the minimum data needed for the approved purpose. Sensitive data, personal information and confidential material require documented authority, access control and supplier review. Client data is not used for unrelated model training without clear written approval.
Testing and monitoring
Testing covers accuracy, unsupported responses, access boundaries, failure modes and the real operating context. Performance is measured against an agreed baseline. Teams receive a route to question, correct and escalate output.
Transparency
Users should know when they are interacting with an AI-assisted service. Material limitations, data sources and confidence boundaries are explained in language suited to the user and decision.
Review and change
AI systems change as models, data and operating conditions change. Project 360 includes periodic review, controlled updates, audit records and retirement criteria in the operating design.
Questions about a proposed use belong in the assessment. Include the decision, affected people and available data in your description.