- Identifying Project Stakeholders
- The Impact of AI on Stakeholder Expectations
- Stakeholder Analysis with AI
- Engaging Stakeholders through AI-Driven Communication
- AI as a Stakeholder for Project Management?
- Ethical Considerations and Professional Responsibilities
- Key Points to Remember
- Technical Guide
This chapter is from the book
This chapter is from the book
This chapter is from the book
The Impact of AI on Stakeholder Expectations
Stakeholders in the era of AI also have different expectations. With technology advancing at breakneck speeds, stakeholders expect more transparency, faster responses, and personalized interactions—areas where AI can excel.
As a project manager, you can meet and exceed these high expectations using AI, such as ChatGPT. Real-time reporting, for instance, is a task that you can automate with AI. This way, you keep your stakeholders informed and foster transparency. Additionally, ChatGPT can help provide instantaneous responses to stakeholder queries or concerns, improving stakeholder satisfaction.
Consider this example in our case study: Global Health is working on a tight deadline, and your stakeholders are anxious about the progress.
“Could you please generate a progress report for the website project to share with our stakeholders?”
Of course. Here’s a draft of the progress report:
Project Name: Global Health Website Development
Current Phase: Design Stage
Key Accomplishments:
Completed user interface design
Established color scheme and branding
Developed site structure and navigation
Upcoming Milestones:
Begin front-end development (Expected start date: 9/1/2025)
User testing (Expected start date: 11/1/2025)
Risks and Issues:
Potential delay in front-end development due to dependency on external vendors.
Please note that these are projected dates and may be subject to change. We appreciate your understanding and continued support.
Remember to customize this template based on your actual project details.
That was good practice. While ChatGPT provides an initial draft, it’s up to you as the project manager to fine-tune and customize the message to suit your stakeholders. The initial prompt provided was very generic, but if we’d given more project context in the prompt, ChatGPT would have generated more specific and tailored information.
As we push further into the age of AI, not only are stakeholders expecting faster responses and increased transparency, but they are also seeking deeper engagement and more proactive communication. They want to feel like they’re part of the conversation and not just passive recipients of updates. And this is where AI’s predictive and analytical capabilities can be leveraged.
Imagine, for instance, asking ChatGPT to predict your stakeholders’ potential questions after seeing the latest progress report. With its ability to process large volumes of data and predict patterns, ChatGPT can help anticipate and prepare for stakeholder reactions.
Based on the data provided, stakeholders might ask about the following:
What are the specifics of the dependency on the external vendor, and how might it cause a delay?
What steps are we taking to mitigate this risk?
Are there any budgetary implications associated with the potential delay?
By proactively addressing these anticipated concerns in your communications, you’ll be meeting the stakeholders’ need for a deeper level of engagement, thus building their trust and support.
Beyond generating reports and answering queries, AI can also help manage stakeholder expectations regarding project risks. By analyzing project data, AI can identify risk patterns and potential pitfalls, enabling you to proactively communicate these risks to your stakeholders.
Assuming ChatGPT already has access to customized datasets of a company or organization, think about a prompt like this:
“Based on past project data and our current progress, what potential risks should we communicate to our stakeholders?”
Alternatively, you can use this prompt if you need to input some context to ChatGPT to better understand your project.
“Act as an expert in project management, risk analysis, and stakeholder communication. Use your capabilities to analyze the project information provided. Review our current project progress, the resources involved, potential hurdles, and our existing risk mitigation strategies. From this, generate a report that includes a current status update, identified risks, progress made, potential stakeholders who should be informed, and strategic advice on next steps. This report should be in semi-formal language and structured in a way that is easy to comprehend for all stakeholders involved. Information to consider includes:
Project Description: We’re currently developing a new AI model to optimize our recommendation system.
Progress Details: We’re halfway through our timeline with major milestones achieved on time.
Known Risks: Potential data bias and resource allocation.
Current Risk Mitigation Strategies: Regular bias testing and reallocation of resources as needed.
Stakeholder Information: Includes a team of data scientists, business executives, product managers, and end users.”
As we utilize AI in managing stakeholder expectations, another crucial aspect that’s rapidly gaining prominence is AI’s role in stakeholder sentiment analysis. Understanding how stakeholders feel about a project can be instrumental in managing their expectations effectively. AI can analyze stakeholder communication for sentiment, providing valuable insights into their emotional state and overall attitude toward the project.
Let’s consider a scenario. You ask ChatGPT,
“Based on the recent communications, how does the design team feel about the recent changes we’ve implemented?”
Based on recent emails and messages analysis, the design team appears to have positive sentiment toward the changes. Positive language and expressions suggest they are satisfied with the recent implementations.
Armed with this information, you can craft your messages and responses more accurately, keeping the positive sentiment alive and addressing any concerns promptly.
Additionally, as you navigate this new landscape, you’ll notice an increasing demand for AI that doesn’t just respond to commands but that also offers suggestions and recommendations proactively. Stakeholders could expect this level of initiative from AI, further influencing the dynamics of project management.
Imagine a scenario in which ChatGPT notices a pattern of recurring issues during a particular phase of your projects. It might proactively suggest:
In the past few projects, there have been noticeable delays during the testing phase due to unexpected bugs. To mitigate this risk, I recommend incorporating a more robust debugging process in the project plan.
Such proactive insights from AI can significantly improve your preparedness, allowing you to manage stakeholder expectations more effectively.
Moreover, with AI’s data analysis and predictive modeling capabilities, you can now give your stakeholders more realistic project forecasts, reducing the gap between expectations and reality. This level of predictive accuracy can go a long way in maintaining stakeholder confidence and ensuring their continued support.
For example,
“Based on past projects of similar scale, what is the most realistic timeline for the testing phase of our project?”
With a response from ChatGPT, you’d be better equipped to set more accurate timelines and manage stakeholder expectations more effectively.
And as you continue to explore this terrain, you must focus on practical and empathetic communication, stakeholder engagement, and respect for data privacy. In each chapter, we include a section that specifically addresses ethical situations, including transparency about data privacy. It’s clear that as we harness the power of AI in managing stakeholder expectations, we are not just evolving our methodologies but also redefining the boundaries of what is achievable in project management.