Top 10 causes of stalled AI/ML projects


and some suggestions



By Yogi Schulz

Calgary, Alberta, Canada

Experienced project managers observe that too many AI/ML projects are stalling and eventually being cancelled. This article discusses the ten most common causes of this unfortunate situation and what project managers can do to correct the problem. Project teams need to evaluate their AI/ML project work in light of these ten causes and formulate a plan to accelerate AI/ML project progress. The ten most common causes are:

  1. Deteriorating business case
  2. Underestimating model training
  3. Lacking data quality
  4. Addressing data integration
  5. Managing data volumes
  6. Incorporating iterative development
  7. Responding to data shift
  8. Underspecifying the model
  9. Validating results
  10. Complicating the algorithm

Deteriorating business case

Organizations approve an AI/ML project based on an appealing business case. As the project proceeds, some events, such as the following, can undermine the business case:

  • Discovery of additional complexity in the solution leading to a significant increase in the cost-to-complete forecast and the annual operating cost estimate.
  • Recognition that the solution requires data the organization does not own.
  • Changes in customer expectations or preferences.
  • Actions by competitors.

The best practice response is to update the business case and determine if continuing the project is still appealing. Allowing projects that are unlikely to produce a net benefit to drag on wastes the organization’s resources.

Underestimating model training

Organizations underestimate the work that goes into training AI/ML models sufficiently. AI/ML project teams tend to underestimate the following:


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How to cite this article: Schulz, Y. (2024).  Top 10 causes of stalled AI/ML projects and some suggestions, PM World Journal, Vol. XIII, Issue V, May. Available online at https://pmworldlibrary.net/wp-content/uploads/2024/05/pmwj141-May2024-Schulz-Top-10-causes-of-stalled-AI-ML-projects.pdf

About the Author

Yogi Schulz

Calgary, Alberta, Canada


Yogi Schulz has over 40 years of Information Technology experience in various industries. Yogi works extensively in the petroleum industry to select and implement financial, production revenue accounting, land & contracts and geotechnical systems. He manages projects that arise from changes in business requirements, from the need to leverage technology opportunities and from mergers. His specialties include IT strategy, web strategy and systems project management.

Mr. Schulz regularly speaks to industry groups and writes a regular column for IT World Canada and for Engineering.com. He has written for Microsoft.com and the Calgary Herald. His writing focuses on project management and IT developments of interest to management. Mr. Schulz served as a member of the Board of Directors of the PPDM Association for twenty years until 2015. Learn more at https://www.corvelle.com/. He can be contacted at yogischulz@corvelle.com

His new book, co-authored by Jocelyn Schulz Lapointe, is “A Project Sponsor’s Warp-Speed Guide: Improving Project Performance.”

To view other works by Yogi Schulz, visit his author showcase in the PM World Library at https://pmworldlibrary.net/authors/yogi-schulz/