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Artificial Intelligence in Project Management Tools

By  Jose Barato

September 11, 2023

4 minutes read

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.

Artificial Intelligence in PMPeople

PMPeople is the tool for the Project Economy. All types of organizations manage projects, programs, and portfolios to turn ideas into reality. Organizations are getting “projectified” and need project professionals to ensure predictability, accountability, and final success of each project. In PMPeople we’ve maintained structured data since our launch in 2018. We keep data from users managing their projects in the free organization, primarily personal projects, project management practices in courses, and product tests. We also keep data from users in premium organizations who use the product mroe professionally. In any case, the data is curated to ensure confidentiality, ensuring that only authorized users have exclusive access to their information. Since the data is encrypted, no PMPeople employee could view clear information from any project. Premium organizations have the option to host PMPeople on their own servers. At the end of each project, we have recorded all data to manage initiating, planning, controlling, and closing, as well as data from stakeholders and team members. We observe how the number of stakeholders (some projects having more than 50) along with well-informed status reports, correlates positively with certain success indicators (time and cost variances, favorable feedback, team happiness index, etc.). Our artificial intelligence model applied to projects can be visualized in the following video (English captions): In the future, the person responding behind the chat box will no longer be a human but an AI that has been trained with information from the context of a significant number of the organization’s projects. The good news is that the technology is already available.

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