While some may embrace the revolutionary technological change brought about by artificial intelligence, others may fear a robot-ruled dystopia. From a project management perspective, it’s prudent to avoid extremes and take a pragmatic look at how the future of the profession may be impacted. 

Artificial Intelligence (AI) refers to software or machines that mimic human intelligence to perform tasks and can appear to ‘learn’ based on data collected. ‘AI’ is often tossed around as a catch-all term for applications that carry out tasks that generally require human input, such as chatting with customers, scheduling appointments, or making predictions – and it’s already influencing project performance. Over 80% of respondents to a recent PMI “Pulse of the Profession®” survey report that their organizations are seeing an impact from AI. Over the next three years, project professionals expect the proportion of projects they manage using AI to jump from 23% to 37%, according to PMI’s “AI Innovators: Cracking the Code on Project Performance.” 

What might this mean for the future of project management? 

  1. Better insights for better decision-making: PMI panelist on AI Advances and Ethics Wanda Curlee emphasizes that “AI can bring forward important lessons learned to help project managers address risks and deliver better results.” The core capabilities provided by AI –predictive analytics, data-driven recommendations, and risk assessment — provide management teams with greater insights and actionable information to make key strategic decisions. 
  1. Reduced cost with improved efficiency: With the potential of AI to automate repetitive administrative tasks, project managers can spend their time more efficiently 
    working on higher value activities, ultimately leading to increased utility and cost reductions. According to a report from KPMG, “AI Transforming the Enterprise,” organizations who have invested in AI say they’ve seen, on average, a 15% improvement in productivity. According to  PMI’s “AI@Work” report, project managers who implemented AI-based tools report that use of AI has cut the time they spend on activities like monitoring progress, managing documentation, and activity and resource planning. 
  1. Optimized scheduling and budgeting: Estimating project cost and duration is one of the great challenges of project management, and mistakes in this area may lead to project failure. A subset of AI known as deep learning – a system of ‘artificial neural networks’ that can iteratively learn based on large amounts of data — could support the optimization of project schedules to minimize the total cost based on resource constraints. For example, predictive 
    forecasting can be used to identify potential shortages or excesses in resources at certain points during the project lifecycle. The deep learning algorithms can also be used to provide estimates of the duration and resource requirements for project activities based on lessons learned from previous projects. 

Even though a recent Gartner press release estimated that by 2030, 80% of the work of today’s project management (PM) discipline will be eliminated as AI takes on traditional PM functions, there’s one thing we’re certain won’t change anytime soon: 

There will still be a need for creative, flexible, context-driven project managers: While AI might excel at finding patterns and correlations between data sets, the output is only as good as the input, and human intelligence is needed to provide context and interpretation. Projects are complex undertakings involving a high degree of uncertainty and variability beyond the realm of what AI can handle for the foreseeable future. The Project Management Institute predicts that we’ll still need 88 million humans working in project management around the world by 2027, and AI will continue to be a valuable tool serving their needs.