How AI will transform project management

Article originally appeared on the Harvard Business Review website, 2 February 2023

By Antonio Nieto-Rodriguez and Ricardo Viana Vargas

What/Focus

The article opens with a future scenario in which an AI-based smart phone app allows a CEO to monitor the progress of projects, flag potential risks, and prioritise decisions, as well as drawing her attention to adjustments and changes needed, updating plans and informing team members. Thanks to new technologies and ways of working, a strategic project that could have drifted out of control — perhaps even to failure — is now again in line to be successful and deliver the expected results. The possibilities for project management are huge as projects require heavy investment but only a third are considered successful.

How (Details/Methods)

The authors call for innovators and organisations to start investing in project management technology now. Traditional low level technologies such as spread sheets are adequate for measuring project success in terms of deliverables and deadlines but do not support the agile responses needed in an ever changing environment. It is projected that by 2030, 80% of project management tasks will be run by AI that is powered by big data, machine learning (ML), and natural language processing.

As well as arming themselves with the technology, organizations and project managers need to be prepared for disruption and change in six key areas. The first is better selection of projects through ML-driven prioritisation that will bring the most value to the organisation in terms of being projects either being launch ready, having a high chance of success or potential benefits, being part of a balanced project portfolio, and which reduces human bias in decision-making.

The second area concerns the use of intelligent tools to support the project management office with tasks such as monitoring project progress, automated preparation of projects reports and compliance monitoring of processes and policies.

Third is the implementation of new applications that use big data and ML to mitigate risks and facilitate project definition, planning, scheduling and reporting. For example, automated reporting that is produced with less labour, and fewer mistakes and duplications will provide real-time data rather than information that is weeks old.

The fourth aspect is virtual project assistants. These assistants learn from past time entries, planning data and the overall context to tailor interactions, capture critical project information, and estimate how long project tasks will take.

Advanced testing systems and software to allow early detection of defects and self-correcting processes before projects go live is the fifth area of change in project management, as seen for example in the Crossrail project in the UK. Finally, project managers need to accept they will have a new role as these tools free them up to exercise leadership capabilities, and strategic and business acumen. Their focus will be on the delivery of expected benefits and their alignment with strategic goals. They will also need a good understanding of these technologies.

So What

As well as anticipating these areas of change, organisations need to make sure they have their people and data ready for these new tools. This means making an accurate inventory of all projects as well as gathering, cleaning and structuring project data. On the people side, it means changing mindsets to accept and adopt new technology (handing over the reins), investing in training in the new technology, and letting the technology make mistakes as it learns.