What are the implications for management?
But what are the messages for top management? One important point to realise is that however tempting cost savings might be, it’s important to strike a balance between cost reduction and quality reduction. Among other things you need a layer of quality control to challenge the outcomes created by the machine and check the documents it generates. This way you allow the machine to learn and get better and better.
Managers also have to think about how to build and preserve the trust we talked about earlier in this article: trust in machines, and trust in people to make good use of them.
One way of building this trust is to educate and certify project managers to use AI and interpret the predictions it generates. They need to understand the underlying algorithms and data, how these combine to make predictions, and the risks involved. Secondly, you need ethical standards to guide people in the use of AI and set limits on the decisions you’re going to allow it to make. You also need transparency on the methods and algorithms used by AIs to avoid program bias (the assumptions made when the software is written and the way the algorithm is fed, which can result in skewed predictions and decisions). An extra layer of governance can be put in place to make sure no one is able to manipulate the algorithms and data. Third-party assurance completes the process of building trust and taking the whole bias out of the equation. Just as automakers have rules governing the accountability of the manufacturer, programmer or operator of a robot arm in the event that it hurts somebody, but also have an inspector come by periodically to check the equipment, you need independent assurance that you have the right rules and processes in place and that they’re working properly.
An important point to remember is that despite all the hype around AI, few people really understand the true limitations and benefits. To assure that their investment pays off, companies need to understand the prerequisites for the successful application of AI in project management, negotiate the complex environment and social dynamics it involves −and keep a detailed record.