A company is evaluating whether to implement AI for a project.

Within the PMI Certified Professional in Managing AI framework, once an organization has clearly defined its business objectives and selected the AI capability it intends to utilize, the next critical step before proceeding into development or implementation is to conduct ago/no-go assessment. PMI-CPMAI identifies this assessment as a formal checkpoint used to validate whether all foundational conditions—technical, organizational, ethical, and data-related—are sufficiently in place to justify advancing the AI project.

The PMI AI Project Evaluation Guidance explains that the go/no-go assessment “ensures alignment of business objectives, validates feasibility, confirms readiness of data and technical environments, and verifies that risks are understood and acceptable.” It serves as a structured decision-making mechanism that prevents premature adoption, scope misalignment, or investment in solutions that may not be viable. PMI stresses that this step is essential for reducing sunk costs and ensuring that only well-justified AI initiatives move forward: “AI projects must not proceed until baseline readiness indicators and feasibility criteria have been formally approved.”

While data quality assessment (D) is important, PMI confirms that it is one of the inputs consideredduringthe go/no-go process—not the decision gate itself. Implementing a preliminary version of the solution (A) would be inappropriate prior to confirming feasibility, and contingency planning (B) occurs later, within risk planning phases.