Three Common Questions About AI in Project Management

Since first speaking about AI in project management at PMI events in 2018, I have been asked hundreds of questions by conference attendees, workshop participants, students, and project leaders. Three questions appear more often than any others.

1. How much data is required to implement AI in a project?
The answer is that “it depends”. In project management, useful results can often be achieved with relatively small datasets. For example, optimization techniques based on genetic algorithms work effectively with only project-specific data. In other situations, success depends on finding a set of similar historical projects. To validate the budget for mass transit projects, I used just over 100 projects and 16 project characteristics per project, yielding a significant result (p < .001). For a complex megaproject, compiling a list of risks might require more historical data. So, the amount of data required depends on the problem being solved and the AI method being used.

2. How do I control the use of AI within my project?
The answer is governance. Organizations should establish a clear governance plan that defines how AI will be used, what data can be accessed, who is accountable for the process, and how outcomes are applied. AI adoption is not simply a technology initiative; it is also a governance and leadership challenge.

3. What proof is there that AI works?
AI is not being used to manage entire projects (yet), but it can significantly improve specific activities such as scope definition, risk identification, forecasting, resource optimization, and decision support. Evidence can be found in the growing number of organizations deploying AI-enabled project solutions and in the expanding body of research supporting their effectiveness.

I am encouraged by these questions because they demonstrate that project professionals are moving beyond curiosity about AI and focusing on practical implementation. Understanding data, governance, and evidence of effectiveness provides a strong foundation for using AI responsibly and successfully within projects.