In today's rapidly evolving technological landscape, integrating 'Agentic AI' into your team can be a game-changer. AI can transform workflows, enhance productivity, and drive innovation. Here are some key strategies for effectively working with an 'Agentic AI' team member:

1. Understand the Capabilities and Limitations

Before integrating an 'Agentic AI' into your team, it's crucial to understand its capabilities and limitations. Agentic AI can perform tasks autonomously, make decisions based on data, and learn from interactions. However, it lacks human intuition and emotional intelligence. Recognizing these boundaries will help you set realistic expectations and leverage the AI's strengths effectively.

2. Define Clear Roles and Responsibilities

Just like any team member, an 'Agentic AI' needs clearly defined roles and responsibilities. Determine which tasks the AI will handle and which will remain under human control. This clarity prevents overlap and ensures that the AI's contributions are maximized without causing confusion or redundancy.

3. Foster Collaboration Between AI and Human Team Members

Successful integration of AI requires seamless collaboration between AI and human team members. Encourage open communication and regular feedback loops. Human team members should feel comfortable interacting with the AI, asking questions, and providing input. This collaborative environment fosters trust and enhances the overall efficiency of the team.

4. Monitor and Evaluate Performance

Regularly monitor the performance of the 'Agentic AI' to ensure it is meeting expectations and contributing effectively to the team's goals. Use key performance indicators (KPIs) to assess its impact on productivity, accuracy, and efficiency. Continuous evaluation allows for adjustments and improvements, ensuring the AI remains a valuable asset.

5. Provide Training and Support

While AI can learn autonomously, it still requires initial training and ongoing support. Ensure that the AI is properly trained on relevant data and processes. Additionally, provide support to human team members to help them understand how to work with the AI effectively. This dual approach ensures both the AI and the team are equipped to succeed.

6. Address Ethical and Security Concerns

Integrating AI into your team comes with ethical and security considerations. Ensure that the AI operates within ethical guidelines and complies with data privacy regulations. Address any concerns related to bias, transparency, and accountability. By proactively managing these issues, you can build a trustworthy and secure AI environment.

7. Embrace Continuous Improvement

AI technology is constantly evolving, and so should your approach to working with it. Stay updated on the latest advancements and be open to incorporating new features and capabilities. Encourage a culture of continuous improvement where both the AI and human team members strive for excellence.

8. Example Demonstrations

The following videos provide a demonstration of Agentic AI:

- Project Manager Agent in Microsoft Planner Demonstration

- Introduction to Operator & Agents

Conclusion

Working with an 'Agentic AI' team member can significantly enhance your project's success. By understanding its capabilities, fostering collaboration, monitoring performance, providing training, addressing ethical concerns, and embracing continuous improvement, you can create a harmonious and productive team environment. As a project manager with decades of experience, leveraging AI effectively will position your team for future success and innovation.

Stop Using Your Favorite Generative AI Tool Like a Google Search

Watch THIS VIDEO

In today's digital age, Generative AI tools have become indispensable in various fields, from content creation to data analysis. However, many users still approach these powerful tools with the same mindset they use for traditional search engines like Google. This approach limits the potential of Generative AI and prevents users from fully leveraging its capabilities. It's time to stop using your favorite Generative AI tool like a Google search and start unlocking its true potential.

Understanding the Difference

Google Search is designed to retrieve information from a vast database of indexed web pages. It excels at providing quick answers to specific queries, such as finding the capital of a country or the latest news on a topic. In contrast, Generative AI tools are designed to create new content, generate insights, and assist with complex tasks. They can write essays, compose music, generate code, and even create art. Treating a Generative AI tool like a search engine underutilizes its creative and analytical capabilities.

Maximizing the Potential of Generative AI

To fully harness the power of Generative AI, users need to shift their mindset and approach. Here are some tips to get started:

1. Provide Context and Details: Unlike search engines, Generative AI tools thrive on context. When asking for assistance, provide as much detail as possible. For example, instead of asking for "tips on writing," specify the type of writing, the audience, and the desired tone.

2. Experiment and Iterate: Generative AI tools are designed to be interactive. Don't be afraid to experiment with different prompts and iterate on the results. If the initial output isn't what you expected, refine your prompt and try again.

3. Leverage Advanced Features: Many Generative AI tools come with advanced features that go beyond simple text generation. Explore options like fine-tuning models, using templates, and integrating with other tools to enhance your workflow.

4. Collaborate with the AI: Think of Generative AI as a collaborator rather than a tool. Engage in a back-and-forth dialogue, provide feedback, and guide the AI to achieve the desired outcome. This collaborative approach can lead to more creative and effective results.

Conclusion

Generative AI tools have the potential to revolutionize the way we work and create. By moving beyond the search engine mindset and embracing the unique capabilities of these tools, users can unlock new levels of creativity and productivity. So, the next time you use your favorite Generative AI tool, remember to provide context, experiment, leverage advanced features, and collaborate with the AI. Stop using it like a Google search and start exploring its full potential.

Watch video HERE

The advent of AI agents is revolutionizing the way businesses operate, and one of the most promising applications is in the realm of project management. AI agents are poised to take over the Project Management Office (PMO), bringing unprecedented efficiency, accuracy, and scalability to project management processes.

AI agents can automate routine tasks such as scheduling, resource allocation, and progress tracking. By embedding human workflows into software, these agents free up project managers to focus on strategic decision-making and problem-solving. This automation leads to significant time savings and allows for more projects to be managed simultaneously.

AI agents can analyze vast amounts of data in real-time, providing project managers with actionable insights. They can predict potential risks, identify bottlenecks, and suggest optimal solutions. This data-driven approach enhances the quality of decisions, leading to better project outcomes.

Multiple AI agents can work together on complementary tasks, ensuring seamless collaboration across different project teams. They can communicate and coordinate with each other, ensuring that all aspects of a project are aligned and progressing smoothly. This level of coordination is difficult to achieve with human teams alone.

AI agents enable the scaling of project management operations without a proportional increase in human resources. They can handle an increasing number of projects and tasks without compromising on quality or efficiency. This scalability is particularly beneficial for growing businesses looking to expand their operations.

By automating routine tasks and improving efficiency, AI agents can significantly reduce the costs associated with project management. Businesses can achieve more with fewer resources, leading to substantial cost savings in the long run.

The integration of AI agents into PMOs is just the beginning. As AI technology continues to evolve, we can expect even more sophisticated capabilities, such as advanced predictive analytics, natural language processing, and autonomous decision-making. These advancements will further enhance the role of AI in project management, making it an indispensable tool for businesses worldwide.

In conclusion, AI agents are set to transform the Project Management Office by enhancing efficiency, improving decision-making, enabling seamless collaboration, providing scalability, and reducing costs. As businesses continue to embrace AI, the future of project management looks brighter than ever.

Concept Sources:

- AI agents could birth the first one-person unicorn — but at what societal cost?

- Chatbots are everywhere and will proliferate

- Copilot Agents Unleashed: Agent Builder, Copilot Studio & SharePoint Agents

Other:

- Join the AI in Project Management LinkedIn Group from HERE

- Sign up for the AI in Project Management Newsletter from HERE

- See other articles, videos and podcasts on AI in Project Management from HERE

Below are the top 5 most visited items from each category within our Research Center for 2024. 

If you missed any previous newsletters, this is a great way to catch up!!

Project Management 

1. How to build MS Forms reports the right way - Video
   
2. 13 Project Management Strategies Every Team Needs to Know
   
3. Current Trends in Project Management - video
   
4. Global Project Management 2024 Lee Lambert's Presentation Video
   
5. Project Budget Tracking Template - Video
   

1. PMConnection Copilot - Your Intelligent Project Management Assistant
   
2. AI in Project Management Books
   
3. AI Use Cases for Business Leaders: Realize Value with AI
   
4. How is ChatGPT & AI Revolutionizing Adaptive Project Portfolio Management - Video
   
5. The AI Driven PMO - Video

Taking the PMP Exam: Testing Center vs. Online

TLDR: Go to a Testing Center!

When it comes to taking the Project Management Professional (PMP) exam, candidates have the option to choose between a traditional testing center or an online proctored exam. Each option has its own set of advantages and disadvantages, and the best choice depends on individual preferences and circumstances. Below, we explore the pros and cons of both options to help you make an informed decision.

In summary, both testing center and online proctored exams have their own unique advantages and disadvantages. Testing centers offer a controlled environment with immediate technical support, but require travel and have fixed schedules. Online exams provide convenience and flexibility, but come with technical requirements and potential distractions. Ultimately, the choice between the two options depends on your personal preferences, comfort level, and logistical considerations.

From my persponal perspective, I have heard from three people within the last year that did NOT go to a testing center and for various reasons got disqualified and had to retake ths exam.  Remove this risk.  Got to a Testing Center!

Additional Resources

- PMP Prep Tips
- PMP Prep Questions
- PMP Exam Day Tips

• 8 Modules
• 34 Lessons (Expand Course Curriculum below)
• 6 Hands-On Assignments
• 6 Quizzes
• Step-by-Step with Screenshots
• Many SHORT videos
• Self-Paced
• Approximately 6 hours
• Course Completion Certificate

• Module 1: Introduction to AI
• Module 2: AI Technologies and Applications
• Module 3: Practical AI Implementation
• Module 4: Generative AI and Prompt Engineering
• Module 5: Intelligent Automation
• Module 6: Custom Chatbots
• Module 7: Data Visualization
• Module 8: Wrap-Up

• 4 Modules
• Over 20 Lessons (Expand Course Curriculum below)
• Many short high-quality "How To" videos
• Module Quizes and Final Exam to reinforce learning
• Approximately 3 hours
• Course Completion Certificate

• Module 1 - Introduction
• Module 2 - Demonstration
• Module 3 - Use Cases
• Module 4 - Wrap Up