I've definitely been in rooms where "AI" was used to mean different things to all people in the room. Lack of clarity on the problem that needs to be solved, what needs to be achieved or what success looks like is usually the main contributor to the confusion.
Discussions of the use of AI are usually including individuals that view AI differently, and or who know only a certain level of what AI can do, and all individuals have a different view of how it can be incorporated into project work, yet all think they are having the same discussion. Saving Changes...
In my experience, when someone says “we should use AI,” they are often not talking about AI itself. They are usually talking about a business pain point: too much manual work, slow decision-making, lack of visibility, reporting overload, or pressure to deliver faster. The first thing I try to clarify is:
What problem are we actually trying to solve?
Which process is inefficient today?
What outcome do we expect from AI?
I also think it’s important to distinguish between:
automation,
predictive analytics,
generative AI,
and decision-support tools.
Many projects fail because “AI” becomes a buzzword before the operational need is clearly defined. In project and contract environments, I’ve seen the best results when AI is used to support existing workflows (reporting, document review, KPI tracking, risk identification) rather than replacing human judgment. The real discussion should start with business value, not technology. Saving Changes...
Have you ever been in a conversation where “AI” meant different things to different people? What tipped you off? Yeap, frequently I'm observing that the AI concept in some case is being wrong intrepeted, moving to the unprodutive way. The base concepts and pratical skills must'be more polished. Saving Changes...
Dephney MabuelaCEO| KMSD Engineering ConsultantsCenturion, GT, South Africa
Mar 25, 2026 9:08 AM
Replying to Dwight Clarke
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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.
Very profound, sometimes the use of AI can be misinterpreted as a substitution for human intellectual capability, when its aimed at enhancing workflow efficiency when applied appropriately. Saving Changes...
Payel RakshitJunior Project Manager| Syngene International LimitedIndia
I agree to the submission Saving Changes...
Htar Htar EiProject Manager| Anzer IT Healthcare MyanmarYangon, Myanmar
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.
I completely agree. AI is just a tool — the real starting point is understanding the goal. Once the desired outcome is clear, it becomes much easier to identify the right approach, choose the appropriate tools, and define a practical path forward. Saving Changes...
AI is generally to understand a challenge or issue at its core by effectively & efficiently collecting and analyzing all relevant data points for a solutions or real-time scenarios to address any challenging issues. Saving Changes...
The level of autonomy under which the tool can practice varies greatly. Many expect full autonomy, while that is not usually the case. It also seems to be true that the initial lift in setting up a tool inversely relates to the amount of work a human will need to put in for daily operation. Saving Changes...
Having a conversation about AI today is akin to describing crypto currency to your colleagues a decade ago. Often the concept is conflated with the technology or even the use case. Saving Changes...
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