Stakeholder management has always been a key element of effective project management. The ability to identify, analyze, and engage individuals or groups influencing a project remains an essential factor without which a project has little chance of success. In an age of widespread access to artificial intelligence, particularly advanced language models known as LLMs (Large Language Models), it’s vital to be aware of new opportunities that can enhance the efficiency of these efforts.
The role of AI in stakeholder identification and needs analysis
Artificial intelligence can significantly support the process of stakeholder identification by:
- data analysis — leveraging various sources of information, such as social media and customer feedback, to gain a deeper understanding of the project context.
- classification and segmentation – algorithms help classify stakeholders based on their influence and engagement levels, facilitating prioritization and strategic decision-making in stakeholder management.
- process automation – streamlining information gathering to save time and enable project managers to focus on key individuals and groups.
Once all individuals and groups affecting the project or influenced by it have been identified, understanding their needs becomes critical. Tools like ChatGPT, Gemini, or Perplexity can assist in this process by:
- efficiently processing large datasets to identify trends and preferences within a short time. Surveys, interviews, and questionnaires for assessing stakeholder satisfaction and expectations become more precise and structured.
- Predicting stakeholders’ reactions to different scenarios, enabling better planning for project actions.
According to PMI, a Project Manager spends approximately 75–90% of their time on formal and informal communication with project stakeholders. With high-quality data (following the principle of “garbage in, garbage out”), a PM can make more accurate and informed decisions. Low-quality data leads to erroneous conclusions, potentially derailing communication optimization and automation efforts within organizations.
Chatbots, a common AI application, highlight this principle. Feeding these models properly prepared data improves query handling efficiency, speeds up responses, and ultimately enhances interaction outcomes. AI also supports personalization by tailoring content to recipient preferences, increasing engagement and strengthening relationships. As with any project, if it isn’t measured, it’s impossible to know whether it’s heading in the right direction.
Real-time monitoring of actions, supported by advanced algorithms, allows for continuous evaluation of communication effectiveness and adaptation of strategies to changing conditions.
Practical insights
Stakeholder analysis is an essential step in project planning, helping to determine how different groups and individuals influence the project and their expectations. A well-conducted analysis enables tailored communication and actions to meet stakeholder needs, significantly increasing the chances of project success.
Tools like ChatGPT can make this process faster and more efficient. To begin identifying and segmenting stakeholders, consider using a sample prompt that helps AI understand the project context and suggest relevant groups:
“You are an experienced PM implementing a new CRM system for a large pharmaceutical organization. Help me identify key external stakeholder groups involved in this project and affected by it. Include typical stakeholder groups for such projects, their potential impact (I) on the project, and their interest level (L), along with brief descriptions of I and L. Provide a short proposal for stakeholder management strategies (use: High I and High L: Engage and actively nurture, High I and Low L: Keep satisfied, Low I and High L: Inform, Low I and Low L: Monitor).”
Here’s an example of a result:
I’m curious about your thoughts. Of course, working with ChatGPT is iterative questions should be refined as necessary, and responses must always be verified for accuracy. Remember, AI is not infallible. However, I’ve often found that using ChatGPT as a foundation can greatly support further analysis and engagement with specific groups.
Challenges in using AI
Despite its numerous benefits, leveraging AI in stakeholder management comes with challenges:
- Adhering to data protection and intellectual property regulations, as well as ensuring transparency in data processing, is crucial. Mismanagement of data through uncontrolled dissemination of stakeholder information online can lead to privacy violations, potentially resulting in a loss of trust in the organization.
- Not every organization has the necessary resources, technological infrastructure, or expertise to effectively implement AI solutions. This requires not only investments in technology but also training for employees, which can be both time-consuming and costly.
- The introduction of new technologies, such as AI, requires not only access to tools but also a change in attitudes and habits among employees and management. In the context of stakeholder management, communication and engagement strategies must adapt to incorporate new technologies. Employees must be open to change and willing to learn to effectively collaborate with new tools.
- AI models can generate incorrect information (so-called hallucinations), which in the context of stakeholder management may lead to misunderstandings or wrong decisions. It is essential for project managers to be aware of the limitations of technology and to critically assess AI-generated results.
- The integration of AI into project management processes alters traditional stakeholder roles. These changes can lead to improved collaboration, but may also raise concerns about losing control over decision-making processes. Building trust through open communication and jointly setting goals will be key.
- The use of AI involves the risk of biases embedded in AI models , which can influence the outcomes of stakeholder analysis. Therefore, regular audits of AI models and ensuring diversity in the data used for training are critical.
I hope this article has shed light on the potential of artificial intelligence in stakeholder management. LLMs can significantly streamline stakeholder needs analysis and communication. However, it is crucial to approach this with an ethical mindset and adequately prepare the organization for working with AI.
Article prepared by
Iwona Cydejko
Change Manager, Project Manager
PMP®, APMG Change Management Practitioner®, Scrum Fundamentals Certified (SFC™)
