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Ready, Set, Gen AI! Share Your Checklists and Protocols for Successful Integration

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Claudia Alcelay
PMI Team Member
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!
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Antonio Montes Director| Kyndryl Mexico Mexico, D.F., Mexico
Claudia.

In my case, I am taking the first steps, that is, understanding what AI is, how it operates to apply it within the organization, specifically for project management, because of this, I don't think I can contribute.
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Salih Veseli Victor, NY, United States
There are some use cases that they have slowly started to incorporate but the onboarding process in large financial institutions is at a slower pace due to compliance issues with the way how you handle data.
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Ahmad Al-Mardini Head of PMO| Tahaluf United Arab Emirates
Although I had an interest in GenAI, I couldn't contribute much to my company in this area. However, with this new training, I will be able to deliver GenAI solutions more effectively moving forward while building more clear understanding.

Would appreciate if you can recommend the tools that can be used while establishing PMO office so we can monitor projects and enforce governance while using GenAI.
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Holly Hanna Program Owner| Avista contracted through Volt Medical Lake, Wa, United States
Dec 02, 2023 8:50 AM
Replying to Markus Kopko
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Dear Claudia,

Specific checklists and protocols can be beneficial to assess readiness for working with Generative AI (GenAI) data within a project or organizational context. These tools help ensure all necessary factors are considered and addressed before integrating GenAI into your workflows. Here’s a structured approach:

GenAI Readiness Assessment Checklist:
Infrastructure Readiness:

Evaluate existing IT infrastructure for compatibility with GenAI requirements.
Ensure adequate computing power and storage capacity.
Assess network capabilities for handling GenAI data processing.
Data Management:

Inventory available data sources relevant to GenAI applications.
Assess the quality, volume, and variety of data.
Establish data governance policies, including data privacy and security measures.
Skills and Knowledge:

Evaluate the team’s current understanding of GenAI.
Identify skill gaps and plan for training or hiring.
Ensure access to GenAI expertise, either internally or through external partnerships.
Legal and Compliance:

Review data usage and GenAI applications for compliance with laws (e.g., GDPR, CCPA).
Assess ethical considerations related to GenAI use.
Technology and Tools:

Identify and evaluate GenAI tools and platforms suitable for your needs.
Ensure compatibility of these tools with existing systems.
Risk Assessment:

Identify potential risks associated with GenAI implementation.
Develop strategies for risk mitigation.
Stakeholder Engagement:

Engage with key stakeholders to understand their expectations and concerns.
Develop a communication plan for GenAI integration.
Pilot Testing:

Plan for pilot projects to test GenAI integration.
Define success criteria for pilot projects.
Feedback and Improvement Mechanisms:

Establish processes for ongoing feedback on GenAI use.
Plan for regular reviews and updates of GenAI strategies.
Protocols for GenAI Integration:
Project Initiation Protocol:

Define objectives and scope for GenAI application in specific projects.
Conduct initial stakeholder meetings to align goals and expectations.
Data Preparation Protocol:

Standard procedures for data cleaning, labeling, and preprocessing.
Protocols for data security and privacy during GenAI handling.
Training and Development Protocol:

Guidelines for training team members on GenAI tools and concepts.
Schedule for ongoing learning and development.
Quality Assurance Protocol:

Steps for validating and testing GenAI outputs.
Regular audits to ensure quality and accuracy.
Change Management Protocol:

Guidelines for managing the transition to GenAI-enhanced processes.
Support structures for team members adapting to new tools and workflows.

Conclusion:
Implementing these checklists and protocols provides a structured framework to assess and prepare for the integration of GenAI. It’s essential to approach this process methodically, ensuring that infrastructure, data, skills, and compliance are thoroughly addressed. Regular reviews and updates to these protocols are also crucial as GenAI technology and its applications continue to evolve.

BR,

Markus
Great list thank you
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Anonymous
Currently supporting other up and coming health professionals understand GenAI since it's a new area for our organization to explore.
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Abolfazl Yousefi Darestani Manager, Quality and Continuous Improvement| Hörmann-TNR Industrial Doors Newmarket, Ontario, Canada
Again, lots of good and informative replies!
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Brandy Cranford Manager, PMO| SaaS Consulting Group Nj, United States
Nov 29, 2023 8:14 PM
Replying to Rami Kaibni
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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!
In line with Rami, as Consultants most of our toolsets are dependent upon the scope for the customer, and the customer's appetite for AI. We have some tools (note takers, copilot, etc.) however anything that is not in line with our customer's values firms can be asked to refrain from utilizing such tools. I've had first hand experience with this, one of my customers specifically asked that AI note takes not be utilized, or attend their zoom meetings. Interestingly enough they actually started to use the tools themselves near the end of the project, and being able to see the adoption first hand gives hope that one day we can find a balance.
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Carrie Maul Irex Services LLC Pa, United States
Mar 24, 2025 3:35 PM
Replying to Maxine Burton
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Although no specific checklists exist, the AI field is relatively new to me. I find the PMI courses very useful for learning about AI and its application in project management.

Same here, Maxine. I have learned a lot and slowly integrating into my PM activities.
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Sonal Dottor Berlin, CT, United States
Hi Claudia, In addition to the checklists and structured approaches provided I would add couple of perspectives - 1. How do we incorporate learnings from different industries, domains, and academic settings? 2. Determine how best to execute so that the experiment provides further learning and value.
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Marie-Helene Heon Project manager advisor| CIUSSS-MCQ Trois-Rivières, Quebec, Canada
Hi, we have not yet started preparing for using AI in our organization.
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