AI to drive project management

AI to drive project management

Every year, approximately $48 trillion are invested in projects. Yet according to the Standish Group, only 35% of projects are considered successful. The wasted resources and unrealised benefits of the other 65% are mind-blowing. Gartner’s research indicates that change is coming soon, predicting that by 2030, 80% of project management tasks will be run by Artificial Intelligence (AI), powered by big data, machine learning (ML), and natural language processing.

In PwC’s ‘22nd Annual Global CEO Survey’, 85% of CEOs agreed that AI would significantly change the way they do business in the next five years. With the availability of big data and strong processing power, AI can act as a thinking processor. Even though nascent in its development, AI can be applied to PM to reduce incredibly complex issues and play a significant role in their success.

Automation to free 360 hours every 365 days

Forbes found that AI could save the average Fortune 500 company $4.7 million per year via automation. According to the report, 53% of employees state that they can save up to two work hours a day (240 hours per year) through automation and 78% of business leaders posit that automation can free up to three work hours a day (360 hours per year).

We are living in a time when global mega trends are actively reshaping our world at a rapid pace. These large-scale macroeconomic and geo-strategic forces – which we define as changes in ‘demographics’, the ‘shift in global power’, ‘urbanisation’, ‘climate change’ and ‘technological breakthroughs’ – are raising both profound challenges and opportunities for governments and business alike. In particular, ‘technological breakthroughs’, and the impact of advances such as AI, will have a huge impact on the future of the workforce, including the role of the project manager.

Three waves of job displacement

PwC’s recent analysis of OECD data covering 200,000 jobs in 29 countries breaks AI’s job-displacement effect into three waves: algorithmic (until the early 2020s), augmentation (to the late 2020s) and autonomy (to the mid-2030s). The first wave will impact relatively few jobs – perhaps 3%. By the mid-2030s, however, up to 30% of jobs could be automated – mostly those involving clerical and manual tasks. The need for upskilling the workforce is clear: as technology evolves at an ever-increasing pace, so too will employees’ skill sets in order to adapt and keep pace with such changes – allowing all to thrive in the new era of AI.

AI can be used to analyse disparate and ‘big’ data with greater speed and dexterity to derive actionable, tangible insights. In this way, project managers will be empowered with more and better-quality data and insights to improve the speed, quality and accuracy of decision-making throughout the project life-cycle.

Technology to improve project selection

One reason for this disappointing rate is the low level of maturity of technologies available for project management. This is about to change. Researchers, start-ups, and innovating organisations are beginning to apply AI, machine learning, and other advanced technologies to project management, and by 2030 the field will undergo major shifts.Technology will soon improve project selection and prioritisation, monitor progress, speed up reporting, and facilitate testing. Project managers, aided by virtual project assistants, will find their roles more focused on coaching and stakeholder management than on administration and manual tasks.

If applying AI and other technological innovations to project management could improve the success ratio of projects by just 25%, it would equate to trillions of dollars of value and benefits to organisations, societies, and individuals.Organisations and project leaders that are most prepared for this moment of disruption will stand to reap the most rewards. Nearly every aspect of project management, from planning to processes to people, will be affected.

Risk management is ripe for automation

One of the most developed areas in project management automation is risk management. New applications use big data and ML to help leaders and project managers anticipate risks that might otherwise go unnoticed. These tools can already propose mitigating actions, and soon, they will be able to adjust the plans automatically to avoid certain types of risks.

AI will change how the discipline of project management and the role of project managers will function in the future. By 2030, 80% of the work of today’s project management discipline will be eliminated as AI takes on traditional project management functions such as data collection, tracking and reporting. In this context, the role of the project manager will shift from ‘managers’ to ‘leaders’ who are able to integrate AI capabilities into new practices and procedures, allowing for a greater focus on activities requiring soft skills such as ideation, communication, listening, problem solving and emotional intelligence.

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