Have attempts to apply artificial intelligence to project management failed?

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

Around four years ago we wrote our first article on artificial intelligence (AI) in project management.

Since then, the use of AI in certain areas of business has skyrocketed. But not in project management. Admittedly, simpler forms such as automation/integration and chatbots are making inroads. But advanced AI, for example predictive insights and autonomous project managers? Not really much to report.

Why the lack of progress?

Research into AI has been going on at a fairly steady pace for nearly 60 years. But it’s applications like Siri and Alexa that have caught the imagination of the public and the media. The resulting hype has spilled over into other areas, with AI predicted to have far-reaching consequences for many professions, including project management (PM). Scenarios have ranged from a new golden age for companies to massive unemployment.

This hype, combined with global empirical data showing that companies expect AI to lead to major changes in the nature of work has given much of the project management profession the jitters. Some of the widespread debate that’s ensued around AI for PM has bordered on hostility.

Does this mean AI for PM is dead in the water?

Despite the current gap between hype and reality, we believe that artificial intelligence will bring about huge changes in project management. On balance, these changes will be empowering. They’ll relieve project managers of much of the mundane work and free them up for tasks that humans still do better than machines. More about that in another blog post.

Given the relative lack of progress, however, we figured it was time to look more closely at the factors limiting the application of AI in PM. We came up with three broad categories:

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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Technology & data readiness

To train a neural network to decide quicker and better than humans, you need plentiful, structured data. But most organisations don’t have this. They don’t have a nice, well-kept, orderly repository of past projects, and they don’t have robust project controlling and monitoring in place. Companies serious about adopting AI will have to address this lack as a matter of priority.

People & capabilities

The talent to develop, implement and work with AI is in short supply. One solution would be for organisations to train their existing workforce to operate in AI-enabled environments. Most, however, still tend to hire graduates from prestigious universities or poach from big name competitors rather than spending the money on internal upskilling initiatives.

Market demand & readiness

With all the hype, potential buyers and would-be adopters are desperately seeking AI solutions. But often, these don’t yet exist. The way out would be investment in AI development. Problem is, leaders often lack a business case for AI. If the AI is itself the product or directly increases revenues, the benefits are clear. The allure of project management AI, however, isn’t always as obvious.