When someone says, “we should use AI,” my first reaction is usually skepticism, because the motivation is rarely clear upfront. Often, what’s really driving the suggestion isn’t curiosity about technology, but a fear of being left behind, missing efficiency gains, or losing competitive ground. That signal alone tells me to pause and unpack the conversation carefully before jumping to solutions.
I start by exploring what’s actually being asked: Are we trying to automate a repetitive task, augment human judgment, generate insights, or experiment with something entirely new? Often, different stakeholders mean very different things when they say “AI,” and conflating all use cases under one label leads to misalignment, inflated expectations, and blurred accountability. The human-centered approach I lean on is to clarify intent first, not technology. I ask questions like: What problem are we trying to solve? What would success look like? Who owns the outcome if things go sideways? Only after understanding the underlying motivation and the real business problem do I start discussing which AI approach, or whether AI at all, is appropriate.
In short, I treat “we should use AI” as a cue to explore why, not as an instruction to deploy. Most often, once the motivation is surfaced and fears or pressures are acknowledged, the conversation moves from hype to actionable clarity.
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SHARON TANUIProject Management| MAJID AL FUTTAIMNAIROBI, 30, Kenya
Mar 25, 2026 6:17 PM
Replying to Maloy Manna
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Can't agree more with Luis Branco. In fact "we should use AI" is a great opportunity to learn more about the issues, constraints and bottlenecks perceived.
Stakeholders don't always feel right complaining outright, and this could be: either : genuine suggestions to use AI technology to improve outcomes and/or : couching their frustrations about constraints and roadblocks like slow processes, poor quality
Steer the conversation to find out their motivations, the Why behind the ask: - is it fear of missing out (FOMO)? With the current hype around AI, maybe they think AI is the silver bullet - is it strategic signaling ? To look innovative or good in front of their audience? - is it genuine intent about overcoming some constraint, or improving something further ?
AI is a tool, it's not the job. Find out what's the "job to be done".
But wait! You've already discovered something which you didn't plan for. AI capabilities and hype have been increasing over the last couple of years and directly affect business. The first step was to build awareness and consensus to get everyone on the same page about AI.
If you don't "get" what your stakeholder means, you need to get your act together to build a shared understanding and vocabulary of what AI means in your context (project/program/organization).
I totally agree with your sentiments on AI adoption in the construction field. There's a buzz about AI being the new kid on the block but as people in the construction filed it is important to identify where and how to incorporate AI, may be just as a guide on how to navigate building projects but the human interface is still very much a necessity that may not be negated by AI. Saving Changes...
As AI is trending now, everyone is coming with this idea of implementing AI and making things look cool with their suggestion. The underlying fact is, do they really know what are they solving with implementing AI? I guess only a few understands the use case properly. 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.
We have seen this happen many times, not just for AI, also for (chat)bots, based on no experience and without a problem they are trying to solve. Some companies want bots and AI because every other company is using it and we cannot "stay behind". Eventually the actual problem is not solved by implementing AI or bots because the requirements for this kind of solution cannot be met with the existing data.
Vendors often show you great demos that are set in a controlled environment, using perfectly formatted and clean data. In real live situations this demo would never have worked. Saving Changes...
When someone says “we should use AI,” they are usually expressing a desire for improvement—but not a clear requirement for sure. Job on hand is to turn that statement into specific, measurable, feasible objectives by exploring: • The problem • The goal • The data • The users • The workflow • The risks • The expected outcome / value Saving Changes...
I'd unpack what is being asked by trying to fully grasp the problem to be solved, talking to the main stakeholders and the sponsor to figure out their expectations and pains going on, and complement them with some vendors opinions and with AI suggestions, like Gemini. With all this info. I'd develop a project proposal presentation to gain their feedback and move on. Saving Changes...
When someone says “we should use AI,” it’s important to clarify the real need behind the statement.
I would start by asking what problem we are trying to solve, what outcomes are expected, and how success will be measured. It’s also key to understand the available data, constraints, and whether AI is truly the best solution compared to simpler alternatives.
This helps turn a vague idea into a clear, value driven initiative aligned with project goals. Saving Changes...
If that someone is a key stakeholder, yes we are talking more on that topic. I would advice to treat AI as a helper and try to understand what would they expect the AI to do. Without judgement, listen and document and see if I can create a customer journey map along with AI. As most of you all know, from there the next steps are business analysis, feasibility checks and stakeholder management. Saving Changes...
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