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...
I personally use a few simple checks before I bring Gen Ai into a project. The first thing I look at is whether the data is in good shape. If the information is messy or unclear, the result won't help anyone, so I make sure that part is solid first. I also take a moment to decide if the use case is even worth it. I look at the impact, the effort involved, and any risk. It keeps me focused on the areas where AI will actually make a difference instead of adding tools just because they are new. From here, I keep track of what's working. I save different versions of prompts or workflows and review them so I know what gives them the best results. I'm also careful about what data goes in, making sure it fits our security and privacy rules. And before I roll anything out widely, I test it on a small scale. That gives me a good feel for how reliable it is and whether it fits naturally into the team's day-to-day work. This approach has helped me use Gen AI in a way that feels practical, safe, and genuinely useful to the work. Saving Changes...
Anonymous
This is still a new concept for us. It still ha to be fully embraced in the industry. However it will be interesting to see how it would impact the industry here.
Saving Changes...
Anonymous
This is still a new concept for us. It still ha to be fully embraced in the industry. However it will be interesting to see how it would impact the industry here.
Kevin FernandezPorts Customs and Freezone CorporationDubai, United Arab Emirates
This is a very timely and relevant topic. From a project management perspective, successful GenAI integration starts with the same fundamentals we apply to any initiative: clear objectives, defined boundaries, and governance. In my experience, a practical GenAI checklist should include use-case prioritization (where AI adds measurable value), data readiness and quality checks, risk and ethics assessment, and clear ownership for outputs and decisions. Equally important is change management—setting expectations with stakeholders that AI is an enabler, not a replacement for accountability or professional judgment. When GenAI is integrated within existing PM frameworks (scope control, risk management, and benefits realization), it becomes a powerful accelerator rather than a source of unmanaged risk. Looking forward to learning from others’ checklists and lessons learned. Saving Changes...
Anonymous
For big organization it will need to get PMO involved, not sure how to apply this on a particular project unless PMO gets involved?
At this stage, I only use Chat GPT to analyze my data. If I were a project manager for a company I would choose the purpose-specific SAAS enterprise solution because it would tailor to my organizations needs and it has better integration capabilities. Moving forward, I would make sure I prioritize tools that can be aligned with my company's workflow, data security, and can be tailored to specific operational needs rather than relying specifically on general-purpose models. Saving Changes...
I am using the PMI classes to learn more about this. I once took an MIT course but that was before GenAI exploded onto the landscape
Saving Changes...
Jacqueline Elaine DennisProfessional Development Training Consultant| Just Expertise DeliveredMansfield, OH, United States
PMI's Gen AI Overview and the AI-related courses that follow are an essential first step in my understanding the fundamentals of AI. Specifically, how the triple As (automation, assistance, augmentation) relate to increased complexity and need for human intervention, which are fundamental to planning for Gen AI's incorporation into practice.
Saving Changes...
Hilda SotoFounder & CEO| Peaceful AI Solutions, LLCSan Diego, Ca, United States
I have seriously considered many possibilities for how to effectively integrate compliance and risk mitigation within the product development lifecycle. I find that documentation and checklists work very well for me.
I have created the following:
AI Ethics Impact Assessment
Model Card Template
AI Risk Register
Datasheet for Datasets
AI Governance Policy Framework
Bias Testing Checklist
AI Vendor Due Diligence Questionnaire
Explainability Requirements Template
AI Incident Response Plan
NIST AI RMF Mapping Worksheet
Human-in-the-Loop Decision Matrix
AI Training Data Audit Log
I analyze each project to determine which templates / checklists are appropriate and incorporate them in to my workflow. Saving Changes...
PMI Team Member
