Avoiding Common Pitfalls Using AI

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In a recent survey, AI in project management was my readers’ top topic to explore further. AI’s benefits are often highlighted, so let’s look at potential pitfalls using AI in project management. For an ironic twist, I asked an AI tool to identify the five most significant traps. 

Beyond best practice — required practice! Any output from an AI tool needs human review for clarity, context verification, and refinement. To show this, you’ll see the AI tool’s answers along with my human interpretation and insights. The My insight entries either clarify what wasn’t clear in the AI response or expand what AI identified to other scenarios. Overall, the AI response identified the high-level concerns I had thought of. However, I didn’t consider it complete. Of course, I could have asked AI to provide more detail on each high-level topic to see if it provided some of the insights I identified.

  • AI-identified pitfall: Overreliance on AI. Project managers may become too reliant on AI tools and overlook the importance of human decision-making. It’s important to remember that AI tools are only as good as the data they are trained on and the algorithms they use. They can’t replace human intuition and experience.
  • My insight: AI also can’t “read a room.” Sure, there are great tools to take notes during meetings, track and assign action items and check calendars. What they can’t do is tell whether a person is happy with an assignment. They also can’t tell if people are content with the meeting. They aren’t detecting body language (yet!). So, they only tell part of the story.
  • AI-identified pitfall: Data quality issues. AI tools require high-quality data to function effectively. If the data is incomplete, inaccurate, or biased, the AI tool’s output will be flawed. (My aside: Yep, garbage-in, garbage-out is still true.) Project managers need to ensure the data they’re using is high-quality and free from bias.
  • My insight: In addition, you need to review the sources the AI tool uses to produce its responses. One way to minimize data-quality issues is to include mandatory experience levels in your AI prompts. For example, “As a project manager with over 20 years of experience in delivering projects in the information technology sector…” then ask for the information you’re looking for. This approach helps improve response relevance and accuracy, but you still need to review the output.
  • AI-identified pitfall: Lack of transparency. Some AI tools are “black boxes” that don’t offer any insight into how they arrived at their output. This lack of transparency can make it difficult for project managers to understand how the AI tool is making decisions and to identify potential issues.
  • My insight: A simple rule – don’t use AI output without understanding the sources the tool referenced. Most AI tools are now providing specific (and actual) references as part of their response. Check those references to ensure their context is suitable for what you are trying to do.
  • AI-identified pitfall: Inadequate training. AI tools require significant training to function effectively. Project managers need to ensure that they and their team members are adequately trained in the use of the AI tool and that they understand its limitations.
  • My insight: Using AI to produce something you don’t fully understand is another version of inadequate training. I heard a story where a web developer used an AI tool to produce code in a language that he had not learned. While initially it appeared to work, errors arose. The developer didn’t have any idea how to debug the code, and refined AI queries to correct the code were unsuccessful. His reputation with his client was tarnished because he didn’t appreciate the need for proper training.
  • AI-identified pitfall: Ethical concerns. AI tools can raise ethical concerns, particularly around issues of privacy and bias. Project managers need to ensure that they are using AI tools in an ethical manner and that they are not inadvertently perpetuating biases or violating privacy laws.
  • My insight: Do your homework! Understand your local laws. They are changing quickly around the world. The safest thing is to analyze the output from AI tools, verify its accuracy and how much it has “spit out” the work of others. Make changes or don’t use the output without seeking permission from the referenced author. Another approach is to apply the output to your own stories and experiences. For example, if AI output recommends that you need to beef up project requirements, document that need by conveying your own stories where requirements were inadequate. That way, you use your intellectual property, not someone else’s who didn’t provide permission to do so.

Do you see other pitfalls to using AI in project management? Rules for how to make AI work effectively in your work? Share with us in the comments section.

For more about AI, check out Dave Birss’ How to Research and Write Using Generative AI Tools course. Or search LinkedIn Learning for his name to find all his courses.

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This article belongs to the Bonnie’s Project Pointers newsletter series, which has more than 62,000 subscribers. This newsletter is 100% written by a human (no aliens or AIs involved). If you like this article, you can subscribe to receive notifications when a new article posts.

Want to learn more about the topics I talk about in these newsletters? Watch my courses in the LinkedIn Learning Library and tune into my LinkedIn Office Hours live broadcasts.

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Using Personality Traits to Assign Project Tasks

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Project team members come with diverse personalities. Let’s look at how to take advantage of different personalities and their work preferences throughout your project.

Important! As project managers, we might assume a person’s personality limits their abilities. For example, extroverts like to talk, but they‘re still able to actively listen to stakeholders. Be careful not to confuse preferences with capability.

Here are some examples of putting personalities to use: 

  • Introversion versus Extroversion. If possible, I assign introverted team members to support senior leaders who appreciate thoughtful consideration. These leaders appreciate team members who carefully digest information before responding. On the other hand, extroverted team members are better for leaders who engage in rapid-fire discussions. These leaders expect quick answers across a range of topics and thrive in dynamic settings.
  • Big picture versus detail-oriented thinkers. When constructing work breakdown structures (WBS), I like a mix of big-picture and detail-oriented thinkers in the room. Big picture thinkers excel at creating the high-level work breakdown structure–listing and combining overarching topics into high-order categories that make sense to the team. From there, the detail-oriented thinkers shine at identifying specific tasks needed to complete the work. Next, the entire team creates the mid-level breakdown and assigns the tasks. Big-picture and detail-oriented are both needed when you’re building a WBS from the top down and the bottom up! When it comes to testing, detail-oriented team members work thoroughly to confirm products to satisfy business needs.
  • Leader versus follower. Team members often need a degree of guidance and leadership to carry out tasks. Assigning a person to lead an effort might seem straightforward…pick the best leader. Maybe not! Sometimes you might need a person who will strictly follow your directions or who will make sure there is alignment with one of your business’ specific and rigid processes. In that case, a person who readily embraces and follows rules and processes might be the best leader.
  • Sensing versus intuitive individuals. By definition, a sensing person looks at the details of a situation and uses their senses to examine what’s in front of them. An intuitive person thinks more abstractly. They focus on future possibilities and patterns as opposed to what is currently present. Intuitives also typically pick up the feelings or disposition of other stakeholders. Sensing individuals are better for collecting and analyzing information.  Intuitive folks are better at collaborating with stakeholders who you suspect aren’t disclosing all of what’s on their mind.

Do you see yourself in any of these categories? Do the activities and roles sound like you? After examining yourself and the tasks you like to do, spend some time doing the same analysis for your team members.

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This article belongs to the Bonnie’s Project Pointers newsletter series, which has more than 61,000 subscribers. This newsletter is 100% written by a human (no aliens or AIs involved). If you like this article, you can subscribe to receive notifications when a new article posts.

Want to learn more about the topics I talk about in these newsletters? Watch my courses in the LinkedIn Learning Library and tune into my LinkedIn Office Hours live broadcasts.

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How to Deal with People Who Ask for Estimates

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How to Deal with People Who Ask for EstimatesA big challenge in project estimating is dealing with the requestor! Leaders often have a number in mind. They might want you to deliver an unachievable objective or expect an unreasonable level of accuracy. Here are a few techniques to handle a challenging estimate requestor.   

  • Point out unknowns. Because projects are unique, they include things that haven’t been done before. That’s where risk and uncertainty make estimating so challenging. When you discuss the development of an estimate with the requestor, talk about the unknowns. Point out what’s different or unique. This can help the requestor understand how difficult estimating can be. Then, ask the requestor questions about any insights they have about project unknowns. This can spark meaningful dialogue and produce a reasonable expectation for the estimate.
  • Uncover and discuss assumptions. Requestors often have unspoken assumptions about the project concept, which can be related to their beliefs about technical complexity. Or they may remember a project they think is like the one they want estimated. Ask the requestor about their assumptions for the project and then talk about whether those assumptions make sense. This can change the requestor’s understanding of the estimating effort and result in a better initial estimate that will be accepted more readily.
  • Present research possibilities. Doing research is a part of building good estimates. But sharing that with a requestor rarely relieves the pressure.  You have a better chance of convincing them to support research by explaining what you want to research and the resources you will use to conduct it. The requestor might reduce their pressure for fast estimates when they see the details of the research that’s needed. The research helps bring facts and historical trends into your estimating.
  • Use estimation ranges and ways to narrow them. Recommended practice is to associate a range with an estimate. For example, an order of magnitude estimate usually appears like $300,000 plus 75% – minus 25%. This range allows for the unknowns and risks that can affect your estimate. When you talk to the requestor, you need to share more information. A range isn’t enough. Talk about the data points and events that could narrow the estimate. Suppose one of the major unknowns is a vendor’s quote. Once you receive the quote and the cost is known, you can incorporate it into the estimate and narrow the range. Explaining this process helps the estimate requestor accept the variability of the estimate.
  • Present historical data about past projects and the inaccuracies of hasty estimating. Discuss similar projects that can validate an estimate. And show how initial estimates are often off the mark. This can temper the requestor’s expectations. Make sure the referenced projects are truly similar. When you look at a past estimate that wasn’t accurate, identify why it differed from the actual values. That way, you can draw parallels to the current estimation process to get a better idea of the estimate and how it might not be accurate.
  • Try to understand the requestor’s perspective and challenges. The requestor could have a valid business reason to pressure you for an estimate. Understanding their challenges can be helpful — it could uncover alternatives.  For example, breaking a project into smaller phases to achieve the requestor’s objectives more quickly. Or expanding the use of a tool or process already in the business to satisfy a pressing business need.

What else have you done to manage requestors’ expectations and demands for estimates? Or what unsolved challenges do you have related to people asking for project estimates? Share with us in the comments section.

For more about estimating methods, check out my Project Management Foundations: Scheduling course.

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This article belongs to the Bonnie’s Project Pointers newsletter series, which has more than 61,000 subscribers. This newsletter is 100% written by a human (no aliens or AIs involved). If you like this article, you can subscribe to receive notifications when a new article posts.

Want to learn more about the topics I talk about in these newsletters? Watch my courses in the LinkedIn Learning Library and tune into my LinkedIn Office Hours live broadcasts.

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Improve Your Foresight

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Improve Your ForesightProject managers need foresight to anticipate potential issues and handle project curveballs. Developing foresight takes time so here are five tips to help you expand your foresight. 

  • Learn from the past. Most organizations keep project files but few people ever look at them. Take time to study previous projects in your organization, successful and unsuccessful alike. Look for trends and patterns. Find out why things went astray. Figure out whether risks were predicted and how they were dealt with. Lessons learned documents are a gold mine for developing foresight, but only if you read them!  
  • Talk with project stakeholders. Rarely does everyone related to a project have the same perspective. Talk to stakeholders about the goals, benefits, shortcomings, and other stressors that came from the projects they were involved in. Listen carefully and be ready for criticism. Not only will these discussions help build your foresight – you will solidify key relationships that make it easier to share truth and increase your ability to make your project stakeholders happy.
  • Review plans and question assumptions. Be prepared to examine, question, and edit your project plans multiple times. Many projects fail because the initial plans weren’t analyzed and adjusted. Question anything that is new or appears to have come from guesswork or assumptions. Test assumptions for feasibility and add tasks to your plans to confirm those assumptions. These activities help ensure you create achievable plans.
  • Consider alternative scenarios. When asking for estimates from your team members, use the Program Evaluation and Review Technique (PERT). Don’t just ask for a single estimate. Ask for optimistic, most likely, and pessimistic estimates. Talk with your estimators about those three estimates and what thinking when into them. You’ll learn more about the challenges your team members might face. This can significantly increase your foresight and help you predict issues before they occur.
  • Never stop learning.  Sign up for courses. Obtain certifications, follow industry experts online, and attend conferences. The more you deliberately expand your knowledge, the better you can envision the road ahead rather than just reacting as your projects progress.

How good is your foresight? What experiences in your past helped you build your foresight? Share with us in the comments section.

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This article belongs to the Bonnie’s Project Pointers newsletter series, which has more than 60,000 subscribers. This newsletter is 100% written by a human (no aliens or AIs involved). If you like this article, you can subscribe to receive notifications when a new article posts.

Want to learn more about the topics I talk about in these newsletters? Watch my courses in the LinkedIn Learning Library and tune into my LinkedIn Office Hours live broadcasts.

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