Project management plays a vital part in the UK's economy, with c2m working in the PM profession contributing £156bn of UK annual GVA, writes Lloyd J Skinner MBCS, CEO of

High rates of project failure have tremendous financial cost – APM reports up to 80% of projects fail to meet their outcomes. Indeed, project delivery is a complex problem with many variables which are impossible to know upfront. Complexity is compounded by people; with soft skills required to deal with the conflicting needs of stakeholders, team members, vendors, and customers.

The benefits of incorporating AI into project management (PM) are many, but to implement requires new operating models and capabilities. But just how is AI impacting PM and shaping the future of work?

Can AI improve project management?

AI tools and techniques can handle complexities during different stages of projects to increase the likelihood of achieving desired results.

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. Dmytro Bogdanov, a professional project management author, stated that 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.

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).

Think about those numbers – they’re staggering. If you consider that the conventional work week is 40 hours, the data reveals that automation will save employees six weeks per year; nine weeks for business leaders – all of it time that professionals could reinvest into career development and personal growth opportunities.

Furthermore, Christian Mendieta, discusses the AI 'virtual assistant'. An AI-based assistant to transform time-consuming tasks, by requesting updates from team members, filling pre-formed weekly reports, and organising meetings and booking rooms. This allows project managers to focus on value-add items such as portfolio management, project prioritisation, coaching, conflict management and leadership.

Cost saving and efficiency through AI automation

In addition to automation, the most likely impact for PM includes project scheduling and risk management. Taking the most efficient route to your goal can also ensure that you meet your schedule. This is a huge benefit – especially given how often projects overrun.

For instance, in a McKinsey study of 1800 software projects, only 30% finished on time. Predictive analytics can ensure this doesn’t happen, by ensuring your schedules are accurate to begin with. By drawing on data about team productivity, available budget and other factors, AI can provide an accurate estimate of when a project will be completed.

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Najjar and Sarraj (2019) explain how AI could transform PM by providing actionable insights and strategies in A virtual partnership? How Artificial Intelligence will disrupt project management and change the role of project managers ( This includes PM tools providing insight into the possible outcomes of a project which will enhance the quality and agility of decision-making.

Machine learning algorithms can be used to provide estimates of the duration and resource requirements for a project based on expert knowledge and lessons learned from previous projects. Optimising schedules is a way to minimise total project cost.

The future of PM work: a marriage made in cyber heaven?

By 2030, 80% of the work of today's PM discipline will be eliminated as AI takes on traditional PM functions, such as data collection, tracking and reporting (Gartner, 2019). Digital skills are important to PMs of the future. PMI’s Pulse of the Profession report highlights the need for data science skills, innovative mindset, security and privacy knowledge, legal & regulatory compliance knowledge, ability to make data-driven decisions and collaborative leadership skills.

Furthermore, AI-based solutions currently focus on predicting the more likely outcomes of your project schedule, however they are now starting to tackle what happens when scenarios change and the impact on the underlying schedule. This, indeed, will require human intervention to fully understand implications and gather consensus on fundamental project direction decisions.

AI is a futuristic tool – available now

Despite all the hype and fascination around AI, ultimately, it is a tool to facilitate productivity. The sooner we learn to engage with it, the easier all our jobs will become. Roles are therefore likely to change as tools increasingly augment our project management capability.

The project manager will need to integrate these capabilities into how they deliver projects and this should allow focus to be far more on the softer skills such as decision making, influencing, change management and conflict resolution.

Project managers must ensure they have the skills to use these systems; in the short term this will differentiate them until this capability is seen as the norm. Therefore, project success (as ever) is just as much about people.


Human-machine collaboration will have a profound effect on how we deliver projects. Rather than resist the change, we should embrace it. We are in an embryonic stage of development for AI in PM, which will accelerate as companies strive for efficiency gains and RoI. Investing in AI increases immediate costs; however, it reduces costs in the long run. In a period of 12 to 18 months, McKinsey observed that businesses found a 15-20% cost reduction using AI and related technologies.

While many businesses are starting to realise that implementing AI helps PM success, it’s important to remember the need for solid foundations. It requires standardised, efficient processes and high data maturity or risk project capability with bad decisions and inefficiency. By spending the time building foundations, AI can get off to an exceptional start.

About the author

Lloyd Skinner is Chief Executive Officer at He is a project professional with 25+ years of experience working in multiple sectors and projects in both delivery and support roles. He has managed full lifecycle, multi-million pound transformation programmes with infrastructure at their heart. For over three years, as CEO of, he has been investigating and developing products that use AI in project management to increase the likelihood of project success – including an Intelligent Project Prediction platform that is a strategic portfolio tool using AI to predict project outcomes.