A project manager is overseeing the transition of a company's legacy system to a new...

In the PMI-CPMAI guidance on transitioning from legacy systems to AI-enabled solutions, the project manager is encouraged tocontrol complexity and risk through incremental, phased adoptionrather than attempting to introduce multiple cognitive capabilities at once. The material emphasizes that when several cognitive patterns (e.g., classification, prediction, recommendation, NLP) have been identified, “the implementation roadmap should prioritize a limited set of use cases and patterns in early iterations, validating value and technical feasibility before expanding scope.” This staged approach allows the team to learn from each iteration, refine data pipelines and integration, and adjust governance and risk controls before adding more advanced or additional cognitive components.

PMI-CPMAI also highlights that overcomplication at the outset increases the chance of cost overruns, resistance to change, and technical failure, recommending that teams “sequence AI capabilities into manageable releases that deliver value quickly while minimizing disruption to existing operations.” Establishinga phased approach targeting one pattern at a timedirectly addresses the project manager’s concern: it avoids “big bang” AI deployment and enables structured change management, training, and stakeholder alignment with each step. Activities such as consolidating all patterns into a single iteration or training employees on everything at once contradict this incremental, value-focused evolution of AI capabilities. Therefore, the first activity should be toestablish a phased approach focusing on one cognitive pattern at a time.