Bandar BahlulManagement| Logistics ManagementRiyadh, 1, Saudi Arabia
Thank you for your thoughtful question.
Yes, we’ve experienced several exciting and sometimes unexpected successes using Generative AI in our projects. One of the most impactful outcomes was the automation of project documentation and reporting, which significantly reduced manual effort and improved accuracy.
Data played a key role in these successes. By ensuring our datasets were clean, structured, and relevant, we were able to guide the AI to produce meaningful and actionable outputs. We also used prompt engineering techniques to refine the responses.
Challenges we faced included:
Ensuring data privacy and compliance with internal policies.
Managing occasional inaccuracies or hallucinations in AI outputs.
Training team members to use Gen AI effectively and responsibly.
Benefits realized:
Increased productivity and faster decision-making.
Enhanced collaboration and communication across teams.
More time for strategic and creative tasks.
We’re excited to continue exploring Gen AI and would be happy to exchange insights with others on similar journeys.
Saving Changes...
Piet HuibertsChief Systems Engineer| LeidosFrederick, Md, United States
Overall, GenAI offers significant benefits, but it is important to be aware of its limitations. When using GenAI, it's best to start with clear expectations, and if the results do not meet them, analyze whether the AI misunderstood the task or whether the expectations need adjustment. Persistence is crucial, as the initial output is seldom ready for use and often requires iterative refinement. GenAI also shifts the necessary skill set toward comprehension, enabling users to better evaluate and improve the generated results. Saving Changes...
Tim CurtisTechnology Services Manager| Nike, Inc.Phoenix, Az, United States
I am trying to understand the benefits of AI in project management. I am having trouble grasping how all the data gets integrated so it can be analyzed. Our org uses various tools for after action reviews as one example. I have actually used a couple different tools as time has passed. If you have all these disparate data sources, it seems difficult to integrate all of these into a cohesive singular source that can then be analyzed.
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1 reply by Thomas Turan
Sep 06, 2025 4:23 PM
Thomas Turan
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I recently gained access to Copilot which has secure access to our internal storage systems, and it has helped me greatly with unstructured data: I have used it to search and summarize large numbers of documents, generate new drafts of documents drawing from other internal documentation, and summarizing meetings with action items just seconds after the meeting ended.
Challenges remain the same from long time ago (Gen AI is outside there from long time ago): AI entities have a grade of confidence associated to them that must be published with the results. So, the final decision still remains in human being hands. The same for the outcomes: helps me to search patterns in a hugh amount of data to create the information I need adding that today I can find data public and outside my organization.
As a Project Manager at an educational institution, I recognize the significant potential of AI in enhancing project management practices, particularly in analyzing lessons learned and streamlining other key processes. While I fully support its integration, our institution has not yet reached the stage where such technologies are actively adopted. Saving Changes...
Challenges remain the same from long time ago (Gen AI is outside there from long time ago): AI entities have a grade of confidence associated to them that must be published with the results. So, the final decision still remains in human being hands. The same for the outcomes: helps me to search patterns in a hugh amount of data to create the information I need adding that today I can find data public and outside my organization.
As a Project Manager at an educational institution, I recognize the significant potential of AI in enhancing project management practices, particularly in analyzing lessons learned and streamlining other key processes. While I fully support its integration, our institution has not yet reached the stage where such technologies are actively adopted. Saving Changes...
Stephen VolzAssistant Dean, Colleges and Curriculum - Project Management| DeVry UniversityLeeds, Al, United States
Hello Claudia and all,
At this time, we do not have successes using Generative AI in projects but we are moving in that direction. A few of our projects are in the beginning stages of adding GenAI to various areas and will hope to have successful outcomes in the near future. Saving Changes...
Thomas TuranProduct Owner, Investments Data Quality| Thrivent FinancialMn, United States
Sep 02, 2025 5:15 PM
Replying to Tim Curtis
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I am trying to understand the benefits of AI in project management. I am having trouble grasping how all the data gets integrated so it can be analyzed. Our org uses various tools for after action reviews as one example. I have actually used a couple different tools as time has passed. If you have all these disparate data sources, it seems difficult to integrate all of these into a cohesive singular source that can then be analyzed.
I recently gained access to Copilot which has secure access to our internal storage systems, and it has helped me greatly with unstructured data: I have used it to search and summarize large numbers of documents, generate new drafts of documents drawing from other internal documentation, and summarizing meetings with action items just seconds after the meeting ended. Saving Changes...
Yes, we’ve seen some unexpected successes with GenAI, especially in areas like automating data profiling, accelerating documentation, and enhancing customer insights. What stood out was how quickly GenAI could turn raw data into actionable narratives and prototypes, reducing cycle times dramatically.
I've found generative AI transformative for creating first drafts of project documentation and communication emails, significantly accelerating my writing process.
Organizationally, AI excels in requirements analysis by synthesizing stakeholder feedback and translating technical specifications for business audiences. We've also used it for resource planning to optimize team assignments.
Main challenges include ensuring accuracy and maintaining data quality, as AI outputs depend on input information quality.
Benefits include 40-50% reduction in documentation time and improved consistency across materials, freeing up time for strategic thinking and stakeholder management. AI has become an invaluable project companion, handling routine tasks while human expertise remains essential for strategic decisions.
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