You can’t engage in the business world today without hearing about AI. Organizations across industries, sizes, and scopes are talking about how to leverage AI to improve everything. One such area is project management.
In short, yes, AI can automate many project management tasks—up to 80%, in fact.
But how? Many businesses and project managers are still trying to navigate the new AI landscape and figure out how to incorporate it into daily tasks and operations. Although it’s still a challenge, and many organizations remain change- and risk-averse, there is light at the end of the tunnel.
As a professional project manager, I’ve had similar questions. However, rather than let the fear of change and AI possibly taking over my job bring me down, I took three courses from the Project Management Institute (PMI) to learn more about how AI can help project managers, and how to leverage it to streamline tedious and time-consuming project management tasks.
In this article, I will share my experiences with AI and how I have used it in my day-to-day project management activities. I’ll also provide some tips on how you can integrate it into your daily business operations to save time, improve decision-making and efficiency, and reduce and mitigate risks.
The Top 7 Ways AI Can Be Used in Project Management
One of the top project management trends for 2024 is AI. As mentioned in this article, AI can help with many areas, specifically those related to integration management:
- Risk management
- Project artifacts
- Decision-making
- Stakeholder communication
- Data analysis
- Lessons learned
- Acceptance criteria
I know what you might be thinking… but how?
#1. Risk Management
One use case I’ve been experimenting with lately is in the area of risk management. I’ve been experimenting with both PMI Infinity and ChatGPT, both of which are GenAI tools. As a general professional practice, I record nearly every meeting I participate in or facilitate (if appropriate, of course) using the Fathom AI notetaker. Although I still jot down some handwritten notes in my handy-dandy notebook for my own reference, I also have the meeting recording that I can refer back to, if and when needed. I also shared the recording of the meeting with other team members and stakeholders.
Once the meeting recording and transcript become available, I download a copy of the meeting transcript as a Word doc, upload it to ChatGPT, and ask it to identify the risks and provide them to me in a bullet-point format. In many cases, ChatGPT has highlighted risks that I never would have considered or even missed. I am often so focused on facilitating the meeting and taking notes, keeping stakeholders on task and on agenda, that I don’t capture all possible risks. This is where ChatGPT has helped me immensely. ChatGPT has also saved me time from having to go back to re-listen to a meeting, or segments of a meeting, over and over. No, ChatGPT can’t see the “big picture” of the project, and assess its risks, but it can do in minutes what it would have taken me hours.
#2. Creating Project Artifacts
I’ve also used both ChatGPT and PMI Infinity to create numerous project charters. Of course, I have to review its results, verify them, make edits and additions, but ChatGPT can help generate that first draft in seconds. Although I haven’t experimented with it yet, I’m confident that ChatGPT can help analyze EEFs and OPAs and provide summaries, assisting with project integration.
Another artifact that AI can help create is the lessons learned log. Regularly updating the lessons learned log can help aid in decision-making, which brings me to my next point…
#3. Decision-making
ChatGPT and other GenAI tools can analyze data from current and previous projects to provide insights and guidance for project managers in making decisions and addressing risks. No, GenAI tools cannot make decisions for you, of course, but the AI algorithms can support decision-making and act as an assistant to project managers and leaders. GenAI tools can list the potential implications of each decision in a comprehensive and cohesive format to be reviewed by project sponsors and other key stakeholders, helping to speed up and streamline the decision-making process.
#4. Stakeholder communication and conflict management
Have you ever had to send a difficult email to a difficult stakeholder? Or have you ever had to participate in or facilitate a difficult meeting you dreaded? Me too, and on countless occasions. Although ChatGPT can’t facilitate the meeting for you, it can help you prepare for it. ChatGPT can help you draft a difficult email to a project team member or stakeholder. How? Simply open the ChatGPT prompt, describe the situation in a few sentences, and then ask ChatGPT to draft a direct yet professional email response. Then, see what it comes up with!
Will it be perfect? Unlikely. You will need to reread and edit it so that it sounds like you wrote it and not ChatGPT. What might have taken you hours or even several days to think about and draft, ChatGPT can draft it for you in a matter of seconds.
Another way you can leverage AI for stakeholder management is conflict management. Managing conflicts involves employing emotional intelligence, and actively listening to others’ opinions, perspectives, reasons, and conclusions. We must make sure we fully understand a stakeholder’s argument. Sometimes, when a stakeholder is venting their frustrations and concerns, it can be difficult for the listener to identify their reasons and conclusions, especially in a live and/or face-to-face conversation. AI to the rescue again. If possible, you can record a conversation or take notes, and then pass that to ChatGPT, asking it to identify and organize the speaker’s reasons and conclusions.
For complicated arguments, it can be helpful to get the conversation and conflict down in some type of written format so that you can refer back to it as often as needed to make sure you fully understand the root cause of the conflict, which allows you to solve it.
#5. Data analysis
As project managers, although we aren’t expected to be engineers or mathematicians—and most of us aren’t—there are times when we might have to perform basic arithmetic. If you’re like me, and you prefer to avoid doing any kind of math like the plague, then ChatGPT will become your best friend. You can ask ChatGPT to analyze a report or perform basic arithmetic calculations, such as budgets, costs, and even baselines. One caveat that is important to know is that ChatGPT can only perform data analyses by reviewing structured, quantitative data.
#6. Lessons Learned
A lessons learned log is a document that records knowledge gained during a project, phase, or iteration on what went well and where improvements can be made for the future. The goal of a lessons learned document is to aid in decision-making, specifically regarding improving future performance for the project team and/or the organization. It is an important tool for continuous improvement and can help to avoid repeating mistakes.
Most project managers will meet at the end of the project to discuss and document lessons learned. The purpose of these meetings is to listen to all the different opinions and perspectives of project team members and document their insights on what went well and what the team could do better in the future, over the course of the project. Most project managers are great at holding these meetings, taking great notes and documentation, sharing the insights and qualitative data with leadership, and then archiving those learnings properly with the project documentation and artifacts. However, that’s usually where it ends. Most insights and actions that come out of a lessons learned meeting don’t actually get acted upon or executed in the future. This is where AI can step in.
AI can help with lessons learned in the following ways:
- Predict project costs and timelines with greater accuracy based on data from past projects.
- Highlight important lessons learned to help project managers deliver better results.
- Summarize action items for future projects
You can then leverage data gathered from your projects in your “lessons learned” documents, helping you build up your knowledge management and also direct and manage future project work.
#7. Acceptance Criteria
Writing acceptance criteria for specific tasks and features can be an essential piece to your quality management plan. Believe it or not, acceptance criteria apply to more than just software or application development projects. It can also apply to:
- eCommerce platform projects
- Marketing campaigns
- Infrastructure projects
- Product development
- Research and development projects
- Health care and medical device projects
- … and many others
Acceptance criteria are critical for a quality management plan because they define the specific conditions under which a deliverable is considered complete and acceptable. They are the benchmarks against which the quality of project outputs is measured, ensuring that the project meets the agreed-upon standards, quality metrics, and requirements. Acceptance criteria also help to reduce risks.
If writing acceptance criteria feels time-consuming, that’s because it is. This is another area where AI can help. For example, asking ChatGPT to write acceptance criteria for a particular task can generate a bullet-point list of acceptance criteria that you can then add to your quality management plan or in the description of a task in your project management software.
However, one caveat here is ChatGPT or another GenAI tool might not necessarily understand the scope of the task. You will likely still need to thoroughly review and vet the acceptance criteria provided by ChatGPT to make sure they are still within scope. You can also give ChatGPT some context as to the scope of the task so that it generates acceptance criteria that are within scope.
What Are the Risks?
We wouldn’t be good project managers if we didn’t consider the potential risks of using GenAI tools to help us manage projects. Although GenAI and other AI tools can help project managers and PMOs alike, it’s worth noting that the tools themselves carry their own risks, and can introduce risks into your project. It’s important to understand how the particular GenAI tool you use is trained, specifically what datasets were used to train the model, and how that data was organized.
What does that mean? Let’s put it this way: A new team member will only be as successful at his or her job as the quality of the training he or she receives. GenAI tools are similar. They are only as effective as the quality and accuracy of the data it receives.
However, there are some workarounds, and they lie within prompt engineering. There are essentially two formulas you can follow to ensure you get the highest quality output and response from your GenAI tool of choice to help you complete your specific task at hand. Those formulas are as follows:
RTF: Role, Task Formula: Perfect for simple tasks or projects
CREATE Formula: Perfect for more complex tasks or projects, where a specific and highly accurate response or output is needed.
Here are some examples of both types of formulas in use:
[INSERT SCREENSHOTS FROM CHATGPT]
You can also request that your GenAI tool cite its sources. This will allow you to validate the quality of information and output the GenAI tool provided.
How Can Project Managers Remain Relevant?
With all these great use cases for how project managers can leverage AI to assist them in their daily project management activities, how will they remain relevant over time? I asked myself this same question. As project managers, we must focus on the areas where we provide the most value to project teams and organizations. Despite how well ChatGPT and other GenAI tools emerge and advance in the coming decades, they will never be able to replicate human intelligence. Maybe this is the optimist in me speaking, but I believe that human intelligence will always be needed in the world of business. This is why developing “soft skills” or “power skills” as a project manager and a leader is so important.
As we navigate the dynamic landscape of project management, the integration of AI continues to drive efficiency, precision, and innovation. The future of project management is undeniably intertwined with AI, promising to elevate the discipline to new heights. Embracing these advancements enhances project outcomes and positions businesses to remain competitive in an increasingly digital world.