Overview

In 2022, Project Managers (PMs) controlled $46TN in project spend. Yet only half of these projects met their original goals and business case.^[1] One way to reverse this low success rate is PM adoption of AI. While many variables drive project success, studies have shown that Project Management AI (PM-AI) can boost project success rates by 15-25%.^[2]  

PM-AI is a disruptive, forcing function brought on by Generative AI. A 2023 research study predicts that one-third of daily PM activities will be replaced by Generative AI.^[3] Automating 30% of what a PM does with AI may feel threatening, but many PMs will cross the chasm. To stay relevant, PMs will need to practice at the top of their license. Even enterprise Project Management Organizations (PMOs) are not immune. PMOs failing to adopt PM-AI will struggle to get budget approvals and witness departures of talented staff.  

PM careers now hinge on PM-AI adoption in team workflows, business processes, decision-making, issue resolution and risk management. 70% of PMs believe PM-AI helps them be more effective.^[4]  

PM job reinvention and higher project success rates will drive widespread PM-AI adoption. By year end, we expect to see 60% of the 16M PMs worldwide using PM-AI in their work and project tools.^[5] At the same time, caution is necessary when using PM-AI. PMs still need to curate PM-AI results for bias, consistency and accuracy.

According to McKinsey and Gartner, organizations that carefully implement PM-AI can improve the success ratio of their projects by 25% or more.^[6] This translates to trillions of dollars in value and benefits to organizations and individuals.

Our goal is to help PMs thrive and increase project success likelihood by making PM-AI your ally.  

Introduction

In this document, we touch on the underlying AI that drives PM-AI, explore the impact of PM-AI on Project Manager roles, review current use cases for PM-AI, benefits realization, some of the challenges that come with change management, adoption and implementation and cautions in using PM-AI, using risk management as an example.  

Project Management AI (“PM-AI”)

The rise of generative AI is nothing short of revolutionary for project managers (PMs) worldwide. By automating tasks, generating insights and optimizing processes and feedback loops with greater accuracy and efficiency, AI is a game changer for PMs.

While there are many evolving types of generative AI, ChatGPT and AutoGPT are two of the most popular ones. ChatGPT took the world by storm in early 2023. ChatGPT is a chatbot that uses large language models (LLMs) to generate text based on human prompts. LLMs can detect patterns that can’t be discerned by other means and can vastly exceed human accuracy in making predictions.

Generative AI results can be wrong, inconsistent or too generalized to be useful. However, with the right prompting and content, it can augment human decision-making.

Unlike ChatGPT, AutoGPT generates content based on tasks without human prompts.  AutoGPT has emerged as a tool that can impact workflow automation and business process management (BPM).  Expect AutoGPT to disrupt CRMs, Project tools and collaboration chat this year.

Meanwhile, Conversation Intelligence (CI), another AI technology based on Natural Language Processing (NLP) is converging with generative AI. Conversation Intelligence uses NLP to transcribe speech to text for multi-party project meetings. Advanced CI applies machine learning to analyze human voice interactions to extract valuable insights and generate speech analytics. We refer to these three AI technologies as “PM-AI.”  

How does PM-AI increase the likelihood of project success?

PM-AI has shown the greatest impact in meetings, follow-up, communications and forecasting.  PMs spend 55% of their time in meetings^[7] and another 20% of their time in follow-up to keep others in the loop.^[8] Meetings can be a major drain on productivity;^[9] one-third may be entirely unnecessary.

Most PMs welcome fewer meetings, less time spent in meetings and reduced administrative work that results from conversation intelligence AI.

PM-AI boosts project success by 15-25%^[10] by:

∙ generating insights that improve project benefits realization by 15%^[11]

∙ reducing meeting duration and number by 34%

∙ cutting PM administrative work by 35-45%^[12]

∙ increasing project velocity by 20-25%^[13]

∙ improving PM and project team productivity by 30%

∙ prioritizing more efficient workload allocations based on schedule, skillsets^[14]

∙ reducing follow-up by clarifying issues to resolve time-consuming back and forth conversations

∙ creating know-how in knowledgebases from sprint reviews

∙ predicting risk with greater certainty^[15]

∙ helping validate investment decisions.^[16]  

Sources

^[1] Nieto-Rodriguez and R. Vargas, “How AI Will Transform Project Management,” Harvard Business Review, February 23, 2023.The Standish Group's 2020 CHAOS Report and the Project Management Institute's (PMI) Pulse of the Profession, 2021 report both present different success rates for projects. The Standish Group's report indicates that only 35% of projects are delivered successfully, while the PMI's study suggests that 69% of projects are successful in meeting their original goals and business intent.

‍^[2] AI benefits realization increases the likelihood of project success by 15-25%. Sources include:

1. Nieto-Rodriguez and R. Vargas, “How AI Will Transform Project Management,” Harvard Business Review, February 23, 2023.
2. Costa, R., Dias, Á., Gonçalves, R., Pereira, L., & Abreu, S. (2022). Artificial Intelligence in Project Management: Systematic Literature Review. International Journal of Technology Intelligence and Planning, 13(2), 1. DOI: 10.1504/IJTIP.2022.10050400.
3. Klun, M., Heričko, M., & Rozman, I. (2021). Artificial Intelligence in Project Management: Systematic Literature Review. Procedia Computer Science, 180, 534-541. doi: 10.1016/j.procs.2021.01.063. In a 2021 systematic literature review conducted by researchers at the University of Ljubljana, it was found that the use of artificial intelligence (AI) in project management can result in significant improvements in project performance. The review analyzed 37 studies on AI in project management and found that AI can be used for various tasks, including risk management, decision-making, resource allocation, and scheduling. The studies also indicated that the use of AI in project management can lead to improved project delivery time, cost savings, and better decision-making.
4. According to a Deloitte report (2021) sing AI in project management can lead to an average cost savings of 20% and can increase project success rates by up to 50%¹. In fact, organizations using AI in project management reported an average 21% increase in project success rates, as well as improvements in speed to market, quality of deliverables, and overall project outcomes².
5. Accenture. (2022). Maximizing Enterprise AI Investments. This report found that the use of AI in project management led to an average 8% increase in project success rates, as well as improvements in project efficiency and risk management.
6. McKinsey & Company. "AI and Project Management: A Catalyst for Better Results." 1 Mar. 2018, McKinsey & Company found that organizations using AI in project management achieved an average 20-30% improvement in project delivery time and cost savings.
7. A 2020 study published in the International Journal of Project Management found that the use of AI in project management was positively associated with project success, and that the benefits of AI varied depending on the specific context of the project.

^[3] Eloundou, T., Manning, S., Mishkin, P., & Rock, D. (2023). GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models. arXiv preprint arXiv:2303.10130 [econ.GN].

Generative AI or LLMs (Large Language Models) automate or replace up to 30% of tasks in Job Zone 4 in which PMs are classified. Job Zone 4 requires higher levels of technical expertise and experience. Job Zones are based on job skilling classifications from hundreds of occupations tracked in the U.S. Department of Labor’s O*Net database.

O*NET OnLine. (n.d.). Job Analysis. U.S. Department of Labor, Employment & Training Administration. Retrieved from https://www.onetonline.org/

^[4] The 2020 PMI survey "AI Innovators: Cracking the Code on Project Performance"

^[5] In 2021, 37% of PMs used AI in their projects, AI Innovators: Cracking the Code on Project Performance.

1. A study by IDC in 2020, found 25% of PMs were AI in their project tools and workflow.

^[6] Harvard Business Review. (2021). How AI Will Transform Project Management. Additional primary source references cited in article:

1. Gartner. (2021). The State of AI and Project Management, 2021.
2. Gartner. (2020). AI in Project Management: Beyond Task Automation.
3. Gartner. (2020). Innovation Insight: Artificial Intelligence for Project and Portfolio Management.
4. McKinsey & Company. (2020). AI and the future of project management.
5. Gartner. (2019). Prepare for the Impact of AI on Project Management.
6. McKinsey Global Institute. (2018). Notes from the AI frontier: Modelling the impact of AI on the world economy.

^[7] Three studies suggest that project managers spend a significant portion of their working hours in meetings, ranging from 50% to 55%:  

1. According to the Wrike Workplace Productivity Report 2021, project managers spend around 55% of their working hours in meetings. The study analyzed data from 1,464 respondents, including project managers and their team members, from various industries.
2. Similarly, the 2019 The Atlassian State of Work Report, Atlassian, found that project managers spend an average of 50% of their time in meetings. The survey included responses from 1,100 professionals, including project managers, team members, and executives.
3. Another study by Harvard Business Review. (2017). How to Take Charge of Your Development as a Leader found that managers, in general, spend an average of 23 hours per week in meetings. The study surveyed 182 senior managers from various industries.

^[8] Three studies suggest that project managers spend 20% of their time on follow-up activities and communications.

1. Project Management Institute (PMI) study: "The High Cost of Low Performance: The Essential Role of Communications" (2013)
2. Wrike study: "2019 State of Project Management" (2019)
3. LiquidPlanner survey: "2016 Project Management Predictions"  

^[9] The Boss Wants to Make You More Efficient - WSJ (April 29, 2023).

1. One Company’s Trick to Getting 95,000 Hours Back? Canceling Meetings - WSJ (February 1, 2023)
2. Make Time for the Work That Matters. Harvard Business Review. (2013, September 18).
3. Stop the Meeting Madness. Harvard Business Review. (2017, July).

^[10] AI benefits realization increases the likelihood of project success by 15-25%. Sources include:  

8. Nieto-Rodriguez and R. Vargas, “How AI Will Transform Project Management,” Harvard Business Review, February 23, 2023.
9. Costa, R., Dias, Á., Gonçalves, R., Pereira, L., & Abreu, S. (2022). Artificial Intelligence in Project Management: Systematic Literature Review. International Journal of Technology Intelligence and Planning, 13(2), 1. DOI: 10.1504/IJTIP.2022.10050400.
10. Klun, M., Heričko, M., & Rozman, I. (2021). Artificial Intelligence in Project Management: Systematic Literature Review. Procedia Computer Science, 180, 534-541. doi: 10.1016/j.procs.2021.01.063. In a 2021 systematic literature review conducted by researchers at the University of Ljubljana, it was found that the use of artificial intelligence (AI) in project management can result in significant improvements in project performance. The review analyzed 37 studies on AI in project management and found that AI can be used for various tasks, including risk management, decision-making, resource allocation, and scheduling. The studies also indicated that the use of AI in project management can lead to improved project delivery time, cost savings, and better decision-making.
11. According to a Deloitte report (2021) sing AI in project management can lead to an average cost savings of 20% and can increase project success rates by up to 50%¹. In fact, organizations using AI in project management reported an average 21% increase in project success rates, as well as improvements in speed to market, quality of deliverables, and overall project outcomes².
12. Accenture. (2022). Maximizing Enterprise AI Investments. This report found that the use of AI in project management led to an average 8% increase in project success rates, as well as improvements in project efficiency and risk management.
13. McKinsey & Company. "AI and Project Management: A Catalyst for Better Results." 1 Mar. 2018, McKinsey & Company found that organizations using AI in project management achieved an average 20-30% improvement in project delivery time and cost savings.
14. A 2020 study published in the International Journal of Project Management found that the use of AI in project management was positively associated with project success, and that the benefits of AI varied depending on the specific context of the project.

^[11] A case study published by the Project Management Institute (PMI), titled "Using Artificial Intelligence to Improve Project Outcomes," explores the use of AI to analyze project data and identify areas for improvement, leading to a 15% increase in project benefits realization (source: https://www.pmi.org/learning/library/using-ai-improve-project-outcomes-12408).

^[12] A study by McKinsey & Company found that AI can automate up to 45% of the tasks currently performed by project managers, freeing them up to focus on more strategic activities (source: https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/how-artificial-intelligence-can-deliver-real-value-to-companies).

^[13] A study by the Boston Consulting Group found that AI can help accelerate project delivery by up to 25%, through automated scheduling, resource allocation, and task prioritization (source: https://www.bcg.com/en-us/publications/2021/how-artificial-intelligence-can-accelerate-project-delivery).

^[14] Asana, a project management tool uses AI to analyze user data and provide personalized recommendations for task prioritization and workload management (source: https://blog.asana.com/2020/06/how-ai-helps-asana-customers-focus-on-their-most-impactful-work/).

^[15] A research paper published in the Project Management Journal, titled "Applying Artificial Intelligence to Project Risk Management," explores the use of AI algorithms to analyze project risk data and provide more accurate risk predictions (source: https://journals.sagepub.com/doi/abs/10.1177/8756972819884802).

^[16] A research paper published in the Journal of Intelligent Manufacturing, titled "The Application of Artificial Intelligence in Project Investment Decision-Making," explores the use of AI to analyze project investment data and provide more accurate investment recommendations (source: https://link.springer.com/article/10.1007/s10845-021-01769-w).

‍

To know how Versational® can help you leverage PM-AI, watch this 2-min video. Sign up on the banner for an invitation to the Free AI Project Management Beta Program.

‍