Learning & Innovation Research Manager| Project Management Institute (PMI)Spain
Are you utilizing any specific checklists or protocols within your projects or company to assess your readiness for working with Generative AI data? I'm curious to know what strategies or tools you've implemented to prepare for integrating Gen AI into your workflows. Please share your approaches in the comments below! Saving Changes...
Claudia, this is a great question. However, given the nature of what we do as consultants, we haven't yet started preparing for this but would be very interested to see what other professionals and organizations are doing!
Hi Claudia, the company I recently worked with is at the beginning stage of using MS Copilot for generating meeting notes and creating ppt summaries. However, they used structured data in Hadoop + Random Forest algorithm for machine learning purposes to look at medicine usage of patients and sending notifications if they fail to use medications as prescribed.
These are great discussions and from the looks of it, a little dated now.
In 2026, use of Gen AI agents to accelerate one's work has already taken root, not only in PM roles but almost every role out there. Saving Changes...
Luz EnriquezPacificWest Inc.Whittier, CA, United States
Hi Claudia,
As a smaller firm, we have not crossed over to utilizing AI. I find it interesting all the new technology and often find myself, like Othelo, to be drawn for more training and knowledge to prepare myself for what is inevitable. Excited to read through and see what practices people have in place for this.
Saving Changes...
Anonymous
In the network performance metrics world, AI could be used to predict failures before they occur by reviewing past events and the concurrent performance metrics. Ultimately, we could reduce outages by "pre-repairing" the network elements and perhaps changing some aspects of our designs.
Saving Changes...
yahya watfaManagement| Built IndustriesRiyadh, 01, Saudi Arabia
Yes — especially in complex projects like data centers and mission-critical facilities, readiness for Generative AI should be treated similarly to any other major technology integration initiative: through governance, quality control, cybersecurity, and process alignment. Using checklists for data quality, version control, confidentiality, and compliance requirements — particularly important in sensitive projects. Integrating AI gradually into planning, reporting, scheduling, and coordination processes rather than relying on full automation from day one. Maintaining human validation for critical outputs such as schedules, technical submittals, risk assessments, and contractual correspondence. successful Gen AI adoption is less about the tool itself and more about the maturity of the underlying processes, data structure, and organizational readiness. Saving Changes...
I retired almost a year ago but my former employer was using GenAI for various applications and rolling it out to various departments to increase efficiency across the organization. They even held routine meetings for interested associates to come together to generate new ideas or share ideas/projects they were currently working on and to learn from experts. It was a great learning experience.
I retired almost a year ago but my former employer was using GenAI for various applications and rolling it out to various departments to increase efficiency across the organization. They even held routine meetings for interested associates to come together to generate new ideas or share ideas/projects they were currently working on and to learn from experts. It was a great learning experience.
Thanks for raising this. Within our projects, we are currently using Pair, a Generative AI tool developed by Open Government Products (OGP) under the Singapore Government. It has been cleared for use with up to Restricted/Sensitive Normal data, which gives us a reasonable level of confidence when integrating it into our workflows.
In terms of readiness, we have been focusing on ensuring that our teams understand the appropriate use cases for Gen AI, as well as the data classification boundaries within which we can operate. This includes guidance on what types of information can and cannot be processed through AI tools.
Saving Changes...
Ketan ShahProject Engineering Manager| Aker SolutionsCamberley, Surrey, United Kingdom
Very Good question Claudia. Actually I am not 100% sure and I need to find out strategies or checklist that has been implemented to use company wide.
PMI Team Member
