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...
Selvam SankaralingamSenior Manager - Delivery| Cognizant Technology SolutionsMiami, Fl, 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!
Hi, We tried implementing a preventative maintenance in one of our projects, using machine learning. During this exercise we learnt the need for data quality and data diversity. This helped us to arrive at a better strategy for data collection and retention across the projects. Hopefully in near future we will implement a full-fledged AI solution. Saving Changes...
Anonymous
Great Ideas Saving Changes...
Thomas HopwoodProject Manager, level 2| ConectaSan Mateo, Costa Rica, Costa Rica
These tools have not yet been adopted by my current company. However, I am hoping to use my insight from this course to build a business case for considering these tools to enhance effectiveness in areas such as lessons learned and bid selection analyses. Saving Changes...
As the PMO responsible for overseeing projects and preparing the company for the integration of Generative AI (Gen AI) into our workflows, it’s essential to approach this transformation systematically. Given that we’re working within the Microsoft ecosystem and aiming to integrate Gen AI, the goal is to ensure the transition is smooth, manageable, and aligned with the company’s needs.
Here’s how I would approach readiness assessment, checklists, and protocols to integrate Generative AI into project management workflows:
1. Readiness Assessment Checklist for Integrating Generative AI
Before implementing AI, it’s important to assess the company's current infrastructure, data maturity, and understanding of AI's capabilities. The following checklist would help ensure that we’re ready for Generative AI:
A. Data Quality and Infrastructure Assessment
Data Availability:
Are the necessary project data (task lists, project milestones, project schedules) easily accessible in Microsoft Project Server or Power BI?
Do we have consistent data storage and backup systems (using OneDrive or SharePoint) that will integrate with AI tools?
Data Quality:
Are the project data sets well-structured (e.g., task statuses, completion dates, dependencies)?
Are our project documents (e.g., reports, meeting notes) stored in standardized formats for easy parsing by AI (e.g., Word, Excel, PDF)?
Data Security:
Have we ensured compliance with GDPR or other relevant data protection regulations?
Are our data sharing and storage protocols secure enough to handle sensitive AI interactions (e.g., AI-generated project documents or status updates)?
B. Tool Integration and Compatibility
Microsoft Ecosystem:
Have we identified all the relevant tools (e.g., Microsoft Teams, Microsoft Project Server, Power BI, Power Automate) that we will be using for AI integrations?
Do we have Power Automate or Power Apps set up to connect various systems (Microsoft tools, external AI services)?
AI Tool Selection:
Have we identified the appropriate AI tools (e.g., Microsoft Copilot, ChatGPT, Azure AI, Otter.ai) for automating specific tasks, such as generating reports, creating agendas, and summarizing meetings?
Automation Potential:
Can existing manual tasks (e.g., drafting status reports, MOM, agendas) be fully automated using these tools?
Do we need third-party tools (e.g., Zapier, Trello, or Google Docs) for further integration?
C. Team and Skills Assessment
Team Readiness:
Have we assessed the team’s level of familiarity with AI tools and Microsoft 365 automation (e.g., Power Automate)?
Do we need to invest in AI-related training for project managers, team members, or key stakeholders?
Internal Support:
Is there an internal champion or project owner for AI integration?
Do we have a cross-functional team (IT, project management, data specialists) that can support the implementation and maintenance of AI tools?
D. Use Case Identification and Prioritization
Key Tasks for AI Automation:
Have we identified the specific project management tasks (e.g., task assignments, meeting note creation, report generation, agenda management) that could benefit most from AI?
Are we clear on which tasks are most time-consuming and error-prone that could be automated with Generative AI?
Pilot Use Cases:
Have we prioritized specific use cases (e.g., meeting summaries, status reports) for initial AI testing and integration?
E. Change Management and Communication Plan
Stakeholder Buy-in:
Have we communicated the goals of integrating AI to key stakeholders and obtained their support?
Is there a clear change management strategy in place to guide the transition, including setting realistic expectations around AI’s capabilities and limitations?
Feedback Loop:
Do we have a feedback mechanism (e.g., through Teams or SharePoint) in place to assess the success of AI adoption and gather insights for continuous improvement?
2. Protocols for Integrating Generative AI Into Project Workflows
Once readiness is assessed, the next step is to set up protocols for integrating AI into project management workflows. These protocols ensure the adoption of AI tools and practices is structured, effective, and scalable across all projects.
A. Protocol for Task Automation & Assignment
Use of Microsoft Project Server:
Automation with Power Automate: Automate task assignments and reminders using Power Automate. This includes triggering task assignments when a milestone is completed, sending notifications to the responsible person, and updating the status in Project Server.
AI-Assisted Task Prioritization: Implement AI-powered suggestions within Microsoft Project Server or through third-party tools like Trello (via Power Automate) to suggest task re-prioritization based on historical data or delays.
B. Protocol for Generating Meeting Agendas and MOM (Minutes of Meeting)
AI for MOM Generation:
Transcription and Summarization: Use Teams and integrate with Otter.ai or Microsoft Copilot to transcribe meeting recordings. Automatically generate MOM with action items and summaries using AI.
Power Automate Workflow: Set up a workflow where Teams meeting notes in OneNote are automatically converted into a formatted MOM document in Word or SharePoint.
Meeting Agenda Generation:
Automated Agendas: Use Power Automate to pull upcoming tasks and project milestones from Project Server and automatically generate an agenda document for the project’s weekly meeting.
AI-Powered Insights: If Microsoft Copilot is available, it can help suggest agenda items based on historical data from past meetings or project timelines.
C. Protocol for Reporting and Status Updates
Power BI Integration:
AI-Generated Reports: Use Power BI dashboards to pull real-time data from Microsoft Project Server and automatically generate reports. Use AI-powered insights (e.g., anomaly detection or predictive analysis) to flag potential project risks or delays.
Automated Status Reporting: Set up Power Automate to send weekly or monthly status updates automatically to stakeholders. These reports could include project progress, milestone completion, task assignments, and more.
D. Protocol for Document Management and Knowledge Sharing
Document Collaboration:
Use SharePoint or OneDrive to store project documents, ensuring AI tools can pull information from these repositories as needed.
Implement AI-powered document categorization within OneDrive/SharePoint (via Microsoft AI Builder) to auto-tag and organize project-related documents.
E. Protocol for Team Communication and Collaboration
AI-Assisted Collaboration:
Use Microsoft Teams as the hub for all team communications. Leverage AI to provide real-time task updates or reminders during conversations (using bots like Microsoft Teams bots or Power Virtual Agents).
Implement chatbots for task tracking, answering project-related questions, and even assigning new tasks based on project status or changes.
3. Strategies for Implementation
A. Pilot Project for AI Integration
Select a Low-Risk Project: Choose a smaller or less complex project (e.g., a smaller construction project or a logistics optimization task) to test the integration of Generative AI tools.
Iterate and Improve: Use the feedback from the pilot project to iterate and refine the AI integration process, adjusting workflows as needed before scaling up.
B. Continuous Monitoring and Feedback
Regular Reviews: Set up regular review meetings (e.g., quarterly or bi-annually) to assess the effectiveness of the AI tools, and update the system accordingly based on feedback.
Data-Driven Decision Making: Use Power BI to monitor KPIs related to AI integration, such as time saved on report generation, task completion accuracy, or meeting note quality.
C. Training and Support
Provide Training: Offer initial and ongoing training sessions to ensure all team members understand how to leverage AI tools (e.g., Teams bots, Power Automate, Microsoft Copilot).
Create a Knowledge Base: Develop a central knowledge base (e.g., on SharePoint) to house documentation, FAQs, and best practices for using AI in project management workflows.
Final Thoughts
By creating clear readiness assessment checklists, establishing well-defined protocols for integrating Generative AI, and adopting a strategic implementation plan, your company can successfully integrate AI into project management workflows. This will automate repetitive tasks like report generation, meeting summaries, and task assignments, helping the project management team focus on higher-value activities and enabling data-driven decision-making.
As the PMO, it is crucial to ensure the adoption process is gradual, ensuring everyone is comfortable with AI tools, the technology works well with existing systems, and the organization benefits from enhanced productivity and project visibility.
Disclaimer: Content generated with ChatGPT4, using a Prompt that considered a real-life company.
The use of GenAI tools for PM is in early stages in our company. All employees must comply with the Gen AI policy when using any of the tools available in the market. When doing prompt engineering ensure that no sensitive data is been used in the models. We are nudged to use ChatGPT enterprise license vs. personal. I use PMI Infinity for specific project related questions and templates. Taking baby steps towards creating a workflow after finishing up the PMI Gen AI courses :) Saving Changes...
We are at the leading edge of starting to incorporate checklists and protocols for working with GenAI in our projects. For our organization, we believe that getting the vision right is the first step. Namely, what is the problem(s) AI will solve and/or the opportunities it can help us seize. The second part is getting the organization's data strategy put in place before we begin to try and solve the problem/ leverage the opportunity. Saving Changes...
Ahmed AhmedPerformance and Follow-up Manager| Shibh al Jazira ContractingRiyadh, 01, Saudi Arabia
Hi Claudia
As acontracting company we are using now oracle ERP fusion with all modules (PPM, HCM, SCM, ...).
We have held many meeting and workshops with oracle to apply and integrate AI with existing system to get the benefits of the huge volume of data especially with the nature of our work, which needs to be made important decisions that AI for sure can help with.
Excited and hopeful to reach this phase soon.
Best Regards Saving Changes...
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