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...
Given the persistent dichotomy between certain government establishments and the private or corporate sector, this shift may gradually emerge over the coming years. However, at present, the gap remains significant, and no strategic decision has yet been made to formally assess the organization’s readiness to leverage GenAI-driven data capabilities. Saving Changes...
Anonymous
Starting to learn more about AI tools in order to better assess what can be appropriately used without violating privacy concerns. The biggest issue is dealing with private data that cannot be shared with the model. Saving Changes...
Makarand KulkarniHead Of Project Management| ITT GOULDSKalyan, Maharashtra, India
GEN AI integration to existing project management approach is unique though the term is few years in the industry. As very preliminary approach - To assess your readiness for working with Generative AI data, firstly we need to have the data sets available and compile with sorting to enable usage. Still, it's premature in typical product tailor made manufacturing set up, but I am curious to learn the basics and new ways to build upon the concept and then apply. Thank you for this thread discussion.
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Mustafa SalehIT Systems & Operations Engineer| Rida GroupAl Riyadh, Saudi Arabia
In the last project I was responsible for, I relied on a clear checklist to make sure the team was truly ready to work with Generative AI in a practical and secure way. The first thing I focused on was making sure employees and trainees understood both the capabilities and the limitations of Gen AI. It is important for people to know that while these tools are powerful, they should not be used blindly or treated as if they can do everything. The second and most critical area was security. I made sure the team understood what kind of data could be entered, what controls or adjustments were needed when using these tools, and that AI-generated outputs should not automatically be treated as final results without review and validation. The final and most important point on my checklist was ensuring they had enough knowledge and ability to build customized GPTs. In my experience, this creates a major shift for both individuals and projects, because a customized GPT can deliver far more relevant value than a general model when it is built around the right context, guidance, and data. Saving Changes...
Mohamed Hassan DakanePlanning, Monitoring and Evaluation Specialist| UNICEFGarissa, Kenya
Nov 30, 2023 10:16 AM
Replying to Claudia Alcelay
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Hello Rami, your approach as a consultant could provide us with great cases to build upon a standardized approach to Gen AI data readiness. Although not into this topic yet, if some ideas come to your mind where you think Gen AI could play a role in your profession, please share. :-)
Sharing any available template that speaks to this topic helps. Saving Changes...
Rahul AgrawalSenior Manager, Project Management| FIS GlobalPune, MH, India
1. Execute pilot projects to gain momentum
2. Build an in-house AI team
3. Provide broad AI training
4. Develop an AI strategy including guardrails with etics and compliance in mind
5. Internal and external communication
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Rahul AgrawalSenior Manager, Project Management| FIS GlobalPune, MH, India
1. Execute pilot projects to gain momentum
2. Build an in-house AI team
3. Provide broad AI training
4. Develop an AI strategy including guardrails with ethics and compliance in mind
Yes, we are using standards such as having a consistent taxonomy Using repeated exports from primary sources Comparing data from multiple tools that overlaps And doing spot checks. Saving Changes...
Kaluthanthrige UpekshaEngineer to Contract| Orel International Holding (Pvt) LtdColombo, Western, Sri Lanka
My views with ChatGTP input/ 1. Establish a GenAI Governance Framework Beyond checklists, organizations should consider creating a GenAI governance structure, which may include:
AI steering committee or governance board
Responsible AI guidelines
Clear accountability for AI decisions and outputs
Defined approval processes for GenAI use cases
2. Introduce Human-in-the-Loop Controls For many applications, especially those affecting customers, operations, or compliance, GenAI outputs should include human validation or oversight to reduce risks associated with hallucinations or inaccurate outputs. 3. Focus on Use-Case Prioritization and Value Realization Before investing heavily in infrastructure, organizations should:
Identify high-value, low-risk GenAI use cases
Evaluate expected business impact (efficiency, cost reduction, innovation)
Align GenAI initiatives with strategic priorities
4. Strengthen Responsible AI and Ethical Safeguards Additional considerations could include:
Bias detection and mitigation mechanisms
Transparency in AI-generated outputs
Clear labeling of AI-generated content
Responsible prompt engineering practices
5. Implement Monitoring and Model Lifecycle Management GenAI systems require continuous monitoring and updating, including:
Output quality monitoring
Model drift detection
Periodic retraining or model updates
Logging and audit trails for AI-generated outputs
6. Develop Organizational Change and AI Literacy Programs Successful adoption depends on people. Organizations should invest in:
AI literacy training for non-technical staff
Clear guidance on appropriate use of GenAI
Change management programs to build trust and adoption
7. Security and Data Leakage Protection GenAI systems can introduce new security risks. Organizations should implement:
Great topic. For successful GenAI integration, I focus on a few core project‑management checkpoints: clear problem definition, data and security readiness, stakeholder alignment, and measurable success criteria. I also find it important to start with small, well‑scoped pilots, establish usage and governance guidelines early, and build feedback loops to continuously refine both the solution and ways of working. Looking forward to learning from others’ checklists and protocols. Saving Changes...
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