How to make AI a success in your project management organisation

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

In two previous blog posts, Have attempts to apply artificial intelligence to project management failed? and How do you surmount the obstacles to implementing AI in PM?, we analysed the obstacles hindering the widespread adoption of artificial intelligence (AI) in the project management domain. We then described success factors that can guide you if you want to implement AI successfully in your project management (PM) practice. In this, the last of our three posts on the subject, we describe some useful approaches to laying a foundation.

Formulate impact and value

A good first step is to formulate the impact and value a project AI can bring to your organisation. Then it’s worth defining what you mean by success – in other words, the goals the project AI has to achieve. Then you can create your first use cases based on the impact of AI.

Be realistic

There’s been a lot of hype around AI. People often have inflated ideas about what it can achieve. Remember that a fully autonomous project manager AI isn’t going to happen just yet – even if your organisation were ready for it. So it pays to be realistic about how narrower AI applications might fit into your project management set-up. A helpful start is to think about things AI can do better than humans and vice versa. We’ve come up with a short overview:

Easy for AI & hard for project managers	Easy for project managers & hard for AI
General predictions	Diplomacy
Complex rule-based decisionmaking	Influence without authority
Recognising patterns	Feeling/empathy
Filing taxes	Stakeholder management
Repetitive paperwork	Communication management
Fraud detection	Strategy design & execution
Tasks where data is easily accessible and readable for a machine	Tasks where data is hard to get in a structured and easily readable way

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.

Download the publication

Create value cases

Now that you have a realistic idea of what’s possible with AI in your business context, you can start to create value cases for your organisation. You may see AI as a good way of motivating people by giving them feedback on their performance and optimising workflows. You may envisage a case for AI in decisionmaking, facilitating more accurate project decisions based on the collective subjective judgment of experienced individuals. You may see value in harnessing AI’s ability to reduce the cost of coordination within and between projects, vendors and organisations.

You yourself are convinced of the value of AI in project management. Now you have to convince the people who matter within your organisation that it’s worth the investment. Equipped with realistic value cases and a sound understanding of the success factors in implementation, you’ll be in a much stronger position to do so.