That's so true, it depends a lot of who is talking about AI, there are different kinds of get AI into your daily life, it's that because I wanted to join this course. We need to understand what we want to do with IA, there's a world of options. Saving Changes...
When a general proposition such as “we should use AI” is raised, I do not treat it as a ready-made solution, but rather as an entry point for a more structured and analytical inquiry. This involves first identifying the underlying problem the organization seeks to address, followed by diagnosing inefficiencies or gaps within existing processes. I then focus on defining clear, measurable objectives—whether in terms of reducing time, lowering costs, or improving accuracy. On this basis, the broad idea is translated into a specific, context-driven use case, while also assessing the availability and quality of relevant data, as well as any legal or regulatory considerations. Finally, I advocate for testing the proposed application through a limited pilot to evaluate its practical value before any broader implementation, ensuring that decisions are grounded in evidence rather than general assumptions. Saving Changes...
Andre CassuleFEED and Detailed Engineering, Project management| DEALLuanda, Luanda, Angola
IA é uma ferramenta de busca ou assistente de produtividade para professionais em areas de projectos e engenharia. 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.
There’s no doubt that AI has powerful data processing capabilities and can help us save a significant amount of time on data analysis. Saving Changes...
Angel FelibertyProject Engineer| Austin Bridge and RoadAubrey, Tx, United States
Mar 19, 2026 11:15 AM
Replying to Omar Jabbar
...
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.
Define first the issue and what it wants to achieve, without it the group/department or organization will be on a path to fail on the AI project. Saving Changes...
When someone says “we should use AI,” they’re usually compressing a lot of uncertainty, ambition, and assumptions into a vague statement. Unpacking it means translating that into something concrete, testable, and worth doing Saving Changes...
When someone says “we should use AI,” they’re usually compressing a lot of uncertainty, ambition, and assumptions into a vague statement. Unpacking it means translating that into something concrete, testable, and worth doing Saving Changes...
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.
It's true that we should use AI in project planning even in management of project but not only in that way but also we should use in different activities. Because AI help to simplify certain activities Saving Changes...
Anonymous
AI help to simplify work Saving Changes...
Sahara IbarraTechnip EnergiesMontclair, CA, United States
Mar 19, 2026 7:44 AM
Replying to Kumar Anubhav
...
One of the biggest signals for distinguishing different types of AI work is the expected outcome—whether the goal is automation, prediction, or content generation. For example, if the focus is on insights and forecasting, it’s likely predictive AI; if it’s about creating text, images, or code, it points to generative AI. What often goes wrong is when everything gets labeled simply as “AI” without clarifying the use case. This can lead to unrealistic expectations, poor tool selection, and misalignment with business objectives. I’ve definitely been in conversations where “AI” meant different things to different stakeholders. Usually, I notice it when requirements are vague—like “we should use AI to improve efficiency” without defining how. That’s when I step in to ask clarifying questions about the problem we’re trying to solve, the data available, and the desired outcomes. In my experience, the key is to shift the conversation from “using AI” to “solving a specific business problem with the right AI approach.”
Kumar, I've been in a similar situation. It is crucial to be up to date not only with the latest information, but aware of how AI is evolving. This will help tailor conversations and provide direction to the team. Saving Changes...
PMI Team Member
