Artificial Intelligence in Project Management Tools

Last March, Microsoft unveiled 365 Copilot, the new version of Microsoft Office powered by GPT-4, with the promise that it will revolutionize knowledge work. We will be able to ask Word to draft a document, PowerPoint to prepare a presentation, Excel to analyze some figures, Outlook to respond to emails, Teams to summarize the decisions made in the meeting, etc., considering the specific worker’s context within the organization, corporate policies, information confidentiality, etc.

Since then, artificial intelligence has monopolized discussions about knowledge worker tools. The undeniable productivity improvement from chatting with a program that saves us time from searching on Google and can respond in text that appears to be human, has made us dream of revolutionary technological advancements that will change how we work, interact, express opinions, make decisions, and even think by ourselves.

«ChatGPT avoids Google searches and responds with human-like text».

We can see the AI revolution has already transformed the digital advertising industry. Analogously, we easily extend these changes to other industries, such as project management tools. We think AI is able to plan projects, elaborate reports, assign tasks, automate notifications and recommendations, evaluate people’s performance, discover issues, analyze trends, and so on. We take for granted that all of this is already possible and dive into discussions about ethical, security, and compliance issues.

When we return to the reality of our projects, we continue to use the same tools as before. Software vendors claim to have incorporated AI features –they can’t resist joining the adoption trend. We use the same functions, but now they seem “intelligent” to us. For example, we may discover a button to view the list of projects in red, or a wizard to fill in a risk register, and that seems like artificial intelligence to us –but it’s the same program, in the end.

As of today, September 2023, it is still too early to speak of artificial intelligence in the professional project management field. For software to assist us in planning scope, time, and cost baselines, tracking progress, suggesting actions, anticipating issues, evaluating performance, and so on, it is essential to have a project database within the organization’s context, hosted on the organization’s private servers. This database should have enough data from numerous projects spanning over a year or more.

This project database should be structured in a model that captures management facts at various levels, including business units, portfolios, programs, projects, work packages, tasks, requirements, deliverables, individuals, actions, decisions, status data, and more. It should differentiate the various ways people use it based on their roles in the project, and, most importantly, it should record the different states the project has gone through in each status review.