In a recent PMI course relating to the adoption of AI, it is clear that as a tool, AI can provide great value to save time in the planning and delivery phases, by automating common tasks, such as capturing meeting minutes, compiling project charters, business cases, project plans and offloading the Project Manager to focus on other strategic activities and reduce the "grunt" work effort. That said, the human supervision is still all encompassing and remains mandatory especially on ensuring accuracy and decision making.
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William SchaalProject Manager| Weston Solutions IncSanta Barbara, CA, United States
Mar 19, 2026 11:15 AM
Replying to Omar Jabbar
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I’ve been asked this many times, and my first response is always: what do you want to achieve with AI? Once the outcome is clear, we can define the right approach, tools, and path forward.
Yes, more than ever it is critical to ask questions that clarify objectives. It's so easy for individual team members to go astray because AI is so new to nearly everyone. Saving Changes...
Desde mi perspectiva, la IA debería evaluarse como cualquier otra alternativa dentro de un proyecto: por su capacidad para contribuir a los objetivos y no por la novedad de la herramienta. Esto implica que el director del proyecto debe mantener una visión crítica, analizar beneficios, riesgos y recursos disponibles, y determinar si realmente su incorporación mejora el resultado esperado. Saving Changes...
When someone says, “We should use AI,” they’re not giving you a requirement; they’re giving you a signal. From a PMI perspective, your role is to translate that into value by first asking what problem we’re actually trying to solve.. If the outcome isn’t clear, the solution shouldn’t be either. From there, identify the real need (automation, augmentation, insights, or user interaction), validate whether the necessary data actually exists and is usable, and define success in measurable terms. Only after assessing feasibility, technical, organizational, and governance constraints, should scope be defined. And in some cases, the right answer is not to use AI at all.
Well, said it’s frustrating when we are asked to do something and someone really doesn’t know why they want it just want it because it’s the latest technology. Saving Changes...
I’ve been asked this many times, and my first response is always: what do you want to achieve with AI? Once the outcome is clear, we can define the right approach, tools, and path forward.
believe the first real bottleneck is not the technology itself, but people’s mindset and their resistance to change. Before choosing the right AI tools, organizations need to create a culture that is open to change, learning, and new ways of working. Saving Changes...
Irfan SakrakProject Manager| NoneIzmir, 35, Türkiye
AI is proving to be a valuable asset in project management. It helps close knowledge gaps, surfaces considerations we might otherwise overlook, and consolidates scattered information into a clear, actionable picture. As a result, we can recall critical details and communicate what we already know faster and more effectively. Saving Changes...
Bopharath SryManager, Project and Partnership| Credit Bureau Cambodia
"We should use AI." should come with a clear definition and framework and expectation, and how AI can serve us within our control. Saving Changes...
Hassan MemonContracts Engineer| Hydrochina International Engineering Co. Ltd.Karachi, Pakistan
The intent behind saying "we should use AI" has three underlying motivations: intelligence, speed and leverage. The later two are closely intertwined and most common; every one is trying to become "effective" and "fast" and showcasing these qualities to gain leverage over others in a common environment or field. While the former one is more thoughtful where people seek AI's help in making decisions and solving problems using available data — tasks they once handled themselves and are now delegating, in whole or in part, to AI.
When someone says “we should use AI,” the conversation is rarely about technology itself. It is usually about pressure for speed, efficiency, innovation, or competitive leverage. The first step is to clarify intent.
Three signals help distinguish what is really being asked.
First, decision proximity. Is AI automating a task, augmenting human judgment, or moving toward managing objectives autonomously? These are fundamentally different categories of work. The closer AI gets to consequential decisions, the stronger the need for governance, traceability, and explicit oversight.
Second, problem clarity. Is there a clearly defined business problem with measurable impact, or is AI being treated as the starting point? When the solution precedes the problem, misalignment and inflated expectations follow.
Third, accountability design. Who owns the outcome if an AI-driven recommendation fails? When responsibility becomes diffuse, risk scales faster than performance.
In many organizations, “AI” simultaneously means efficiency, experimentation, and cost reduction to different stakeholders. Misalignment becomes visible when decision flows and ownership are unclear. A common tipping point is when stakeholders use the same word “AI” but describe different success metrics.
The real shift is not from manual to automated. It is from “man in the loop” to “man in control.” Without deliberate design of responsibility, capability increases while accountability erodes.
Clarity of purpose, category of AI work, and ownership separates disciplined transformation from technological noise.
In my opinion using AI should not be left entirely on the AI, the human aspect is very important in order to streamline the information being sent out Saving Changes...
Anonymous
First, we identify where the use of AI would be meaningful. We consider factors such as whether the task is repetitive, whether the process can proceed even if the result is not necessarily correct, whether the input to the AI needs to be secure, and the extent to which the output can be made public. Saving Changes...
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