Is It Ethical to Let AI Write the Project Scope?
| At a recent presentation, a participant suggested that having AI write an entire project document, such as the project scope, raises an ethical issue. It is a fair concern. But is using AI to create the document actually unethical? Of course, there needs to be transparency. If someone presents an AI-generated document as their own work, that presents an ethical issue. But if the use of AI is disclosed, I don’t believe using AI itself is unethical. My preferred approach is collaboration. A project team member develops the scope with input from others and then uses AI to check its accuracy, consistency, and completeness. AI becomes another contributor to the process rather than a substitute for human responsibility. However, we might be missing the larger point. Is the objective to ensure that people write project documents or to produce accurate, comprehensive documents that help us deliver successful projects? Suppose you had two choices. The first is a scope document written by people, perhaps with AI help, but containing errors, omissions, and ambiguities. The second is generated completely by AI but is accurate, complete, and clearly reflects the intended scope. Which would you choose? I would choose the better document regardless of how it was created. Having AI create a project document is not unethical if disclosed. The important point is for project managers to ensure accurate and complete project documents regardless of how they are created and a person must remain accountable for the result. AI may change how documents are generated, but people still need to be accountable. |
Posted on: October 20, 2026 01:27 PM
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Help! Everyone on My Project is Using AI.
| Imagine a project where the sponsor uses AI to find gaps in the business case, the project team uses it to forecast costs and completion dates, the contractor uses another AI to assess schedule performance, and the customer uses AI to interpret progress reports and contracts. The problem is that their AI systems may not agree. For the completion date, one predicts a six-week delay, and another predicts three weeks. One team member uses AI to conclude that a requested change is within scope, but your AI doesn't agree. Also, the customer interprets AI-forecast deliverables differently than the reports you produced. The focus is no longer how to use AI, but how to manage a project when everyone is using it. Project leaders can prepare for this by establishing a simple AI information protocol: o Identify the project data considered authoritative. o Require important AI-generated conclusions to state their data sources and assumptions. o Compare conflicting AI outputs rather than automatically choosing one. o Clarify who has authority to make the final decision. o Record significant decisions and the information used to make them. o Keep accountability with the person responsible for the decision, not the AI that produced the recommendation. As AI becomes easier to use, generating analysis becomes easier too. The challenge is determining which information to trust and how to resolve competing conclusions. Welcome to a new project leadership responsibility: managing an environment in which almost everyone can bring their own AI-generated analysis to the table. |
Posted on: October 12, 2026 08:00 AM
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Use AI to Improve Stakeholder Communication
| Over the years and many projects, I learned that stakeholders do not all need the same information. An executive may want a concise view of progress, risk, and decisions. A technical stakeholder may need detailed information about an issue. A customer may be primarily concerned about impacts and outcomes. Yet project communication is often created once and distributed to everyone. AI provides an opportunity to change that. Section 3.1.3 of PMI’s Standard for Artificial Intelligence in Portfolio, Program, and Project Management encourages using AI to tailor messages for different stakeholder groups and communication channels. For most project professionals, a chatbot offers a simple way to put this idea into practice. I suggest using the following Stakeholder Communication Prompt Template. Give the chatbot the project information and specify:
An important value of AI is its ability to help us communicate more effectively with each stakeholder. |
Posted on: October 05, 2026 08:00 AM
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AI Makes Data Quality a Project Leadership Issue
| Artificial intelligence is changing the importance of data in project management. For years, project teams have worked with misaligned schedules, inconsistent cost information, incomplete risk registers, and retrospective progress reports. People learned to recognize these weaknesses and compensate for them through experience and judgment. AI changes that relationship. An AI system can analyze thousands of data points and produce a forecast in seconds. However, greater analytical capability does not compensate for poor project data. In fact, it can amplify the problem by producing sophisticated outputs based on incomplete, inconsistent, or inaccurate information. PMI’s Standard for Artificial Intelligence in Portfolio, Program, and Project Management emphasizes that reliable and actionable AI outcomes depend on data quality. For project leaders, this makes data quality more than a technology issue. It becomes a management responsibility. Before relying on an AI-generated forecast or recommendation, project professionals should ask:
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Posted on: September 28, 2026 08:00 AM
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AI Changes How We Manage Project Risk
| Project risk management has traditionally relied on identifying risks, assessing probability and impact, developing responses, and reviewing the risk register periodically. Artificial intelligence creates an opportunity to make that process more continuous. AI can analyze changing project data, detect patterns, identify anomalies, and reassess risks as conditions change. A risk that appeared relatively insignificant last week may become important when schedule performance, resource availability, cost trends, or external conditions begin moving in the wrong direction. PMI’s Standard for Artificial Intelligence in Portfolio, Program, and Project Management recognizes this shift by emphasizing continuous monitoring and reassessment of AI-related risks as new data, technologies, and internal or external conditions emerge. The same thinking can be extended to how AI supports project risk management. Instead of asking only “What are our current risks?”, project professionals can increasingly ask “How is our risk exposure changing?” That is an important development. AI makes it possible to move risk management closer to the project's actual pace. Emerging patterns can be identified earlier, assumptions can be continually tested, and potential responses can be evaluated before a risk becomes an issue. The future of project risk management is not simply a better risk register. It is a continuously updated view of where the project may be heading. |
Posted on: September 21, 2026 08:00 AM
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