How do you surmount the obstacles to implementing AI in project management?

Marc Lahmann
Partner, Advisory / Portfolio & Programme Management (PPM), PwC Switzerland

Compared with many other areas of application, the adoption of artificial intelligence (AI) in project management has been slow. In our last blog post, Have attempts to apply artificial intelligence to project management failed?, we identified three categories of obstacles preventing more rapid progress: technology & data readiness, people & capabilities, and market demand & readiness. This time we’ll look at how project managers overcome these obstacles to further the cause of AI in their field.

Project management undervalued

It helps to understand what you’re up against: even now, executives see project management as more of a tactical or operational discipline than a strategic one. This means they don’t fully recognise the value it can bring to the organisation – let alone the business case for AI in project management.

Project managers are painfully aware of the gap between the perception of what they do and the actual value they create. What lessons can the profession learn to reproduce the success AI is having in other fields?

Success stories from other fields

There are many examples of AI-based solutions that have been embraced in other fields: robo-advisory and fraud prevention in financial services, lane-keeping assistance and self-driving vehicles in the automotive sector, digital assistants and household robots for home use, image diagnosis in healthcare, and recommendation engines in retail.

What these successful applications have in common is that they have a measurable impact for the organisation or user of the AI solution. This seems obvious, but it’s important to make clear that the impact an AI delivers must be greater than what the process would be delivering without the AI. For the AI to deliver value it must result in higher sales, fewer cost overruns, timelier completions or similar benefits.

Why can’t reality live up to the AI hype in project management?

Take a deeper look into why progress has been so slow, especially compared with other business areas where the use of AI has skyrocketed in the past few years.

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How to sell the value of project management AI

For organisations that recognise the value of project management, the value drivers for AI are clear as day: project managers are more productive, there’s a better view of risks and issues, better budgeting, and an overall reduction in manual administrative tasks. But as we saw before, these organisations are few and far between. Most don’t yet fully appreciate the value of project management and its impact on the business as a whole.

This means that project managers wishing to further the cause of AI in their field – because they themselves are convinced of the benefits – have to address this lack of awareness gap. This means preparing the ground by addressing the obstacles to create a firm foundation for implementing AI.

Make an IMPaCT

Based on the categories of obstacles we identified earlier, we’ve come up with IMPaCT, a recipe for creating a solid basis for AI in PM:

I is for Impact: Project managers should formulate and communicate the impact and value of project management AI for the organisation as a whole.
M is for Measurements: Measurements are the nuts and bolts of AI: having sufficient data to enable the AI to learn and making sure your data collection and governance are up to the task.
PaC is for People & Capabilities: This involves fostering a culture where people are on board, able and motivated to work with AI.
T is for Technology: Affordable technology now exists to support artificial intelligence in project management. You have to commit to using it and communicate the benefits clearly.

What can you do?

If you’d like to learn more about how to create a solid foundation for introducing AI into your project management set-up, please download our white paper.

Also, feel free to contact us to discuss your own plans for AI in project management.

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