How Will AI Impact Project Management in the Next 5 Years?

How Will AI Impact Project Management in the Next 5 Years?

We know AI is expected to have a major impact on project management planning and decision-making — and, in some cases, it’s already transforming the way we work. But the question remains: How exactly will AI be implemented into the PM workflow in the coming years?

Will AI change some areas of project management before others? Will its adoption be slow and steady and happen all at once? And, most pressingly, will it impact the availability of jobs and careers in the field?

Proggio CEO Yaniv Shor addressed these questions and more in two recent webinars: Talks in AI Project Management and Unlocking Project Management’s Digital Frontier with PMI UK. Along with a group of project management experts, Shor unpacked the expected immediate and longer-term implications of AI in this industry.

“There are actually several domains within which [AI] technology can be implemented,” Shor said. “We believe that it will kick in gradually because it’s not in full maturity right now, and it will take time. So the first interaction [with AI] may be a little shaky, but […] AI will be a major part of the technology we’re seeing introduced into project management applications.” 

Here’s a closer look at the sequence of steps PMs may take to implement AI into the project processes within the coming years:

Establishing knowledge bases

First, project managers will have to gauge team members’ understanding of AI and start building a knowledge base to get them up to speed.

“As a profession, we need to understand what AI is, what benefits it offers us, the various types of AI tools that are at our disposal, and how we can tailor them for particular projects, outcomes, and organizations,” said said Antonia I., project management professional. “We can’t take that learning curve for granted.”

Project management leaders at global biopharma company GSK, for example, have already taken key steps to build their knowledge base. “We are implementing company-wide digital training [modules], and we want all 70,000+ people to take action,” said Amit Arkad, project management and product development leader at GSK. “They cover the basics about what machine learning and GenAI are.”

As Antonia Ifeanyi-Okoro said, “Then, we can move on to how we think about better collaborating with this additional tool at our disposal.”

Setting regulations

Project managers will also need to establish compliance standards and regulations for using AI tools and sharing data.

“There’s a whole team of people who oversee compliance related to project delivery, and that wouldn’t disappear overnight,” said Aoife Ahern, global executive director for delivery excellence at Novartis. “There would have to be test cases, sign-off, and gating. I think you would have to take a wide approach to oversight, and then start to reduce it as the trust level and confidence improves.”

Building high-quality data sets

Vast, high-quality data sets will be essential to effective AI implementation. As Arkad said, “The larger data sets that you rely on, the more accurate predictions you’ll get because you’ll have less bias.”

Shor provided an example: “If we tell ChatGPT, ‘I have a new project and I need three mechanical engineers,’ it will say, ‘I don’t have access to your database. I’m only a language model.’ So first the AI technology needs access to the data set that’s behind the projects. And, of course, that data should be organized in a way that can help the AI technology provide you with the solutions and the answers that you need.”

Enabling faster data access

Speaking of data, Shor said that once AI is implemented across project management organizations, it will first provide faster access to data. Meaning, project managers will be able to ask questions to their AI-powered PPMs and quickly receive answers and solutions based on historical data. 

For example, PMs might ask “Who can replace James on the development project next week?”, “How many tech writers are available in Germany in Q2?”, or “Do we have enough resources to complete our project goal by next month?”

Instead of fumbling through spreadsheets and reports themselves, project managers can save time — and make more informed decisions — by simply asking their AI platform.

Improving automation and documentation

Next, AI will be used to automate reports and document creation, freeing up project managers’ time for more high-level ideation and strategizing.

“If we initially try to dip our toes into the water in terms of using AI a project management tool, I think the safest areas will be [things like] automating your documentation process — whether at the inception stage or the monitoring and controlling stage, or at the end when you’re trying to share results and lessons learned,” Antonia said. “If you can automate the delivery of that communication to stakeholders, that would really begin to add value to this profession.”

Boosting job creation

Gartner predicted that AI will eliminate 80% of project management tasks by 2030. But that doesn’t mean it will necessarily eliminate jobs. In fact, Ahern believes that implementing AI will actually lead to job creation in the field.

“There will have to be people who really understand the technology and can gather insights around its continuous improvement,” she said. “The PMO itself will also transform from something that might’ve been seen as administrative overhead to something that’s driving the automation of reports, using AI to improve the selection criteria for projects, and [running] predictive analyses for better decision-making.”

So, when you consider that AI could help PMs automate away manual tasks and make more time for big-picture strategizing, the future of AI-enabled project management doesn’t look so scary. 

“It’s all really exciting,” Ahern added. “I don’t have any fears around [project manager] roles being no longer required. I think they’re just going to evolve.” 

To conclude, the implementation of artificial intelligence (AI) in project management (PM) workflows is anticipated to have a significant impact on planning and decision-making processes. While concerns about AI potentially eliminating PM tasks persist, experts believe it will actually lead to job creation by transforming roles and driving automation, ultimately enhancing decision-making and strategizing capabilities within the field. Watch this space!

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