Project Management

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When someone says, “we should use AI,” how do you unpack what’s really being asked?

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Michael Brinn
PMI Team Member
Product Manager, Learning| PMI Denver, Colorado, United States

What signals help you tell different kinds of AI work apart—and what tends to go wrong when everything gets lumped together?

Have you ever been in a conversation where “AI” meant different things to different people? What tipped you off?

Share your experiences navigating what’s really being asked when someone says “we should use AI” in the comments below.

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Israel Radebe South Africa
In a sales and marketing context, when a colleague says “we want to use AI,” it typically signals an underlying business pressure, whether that’s pipeline inefficiency, conversion gaps, or competitive tension. Rather than jumping straight into solutions, the conversation should first anchor on where AI can have the most meaningful impact by asking, “Where in your pipeline would you like to apply AI?” From there, the discussion can be guided across key areas such as lead qualification and scoring, sales administration and automation, customer segmentation and targeting, content and campaign personalisation, and forecasting and pipeline intelligence. Once this focus is established, it becomes far easier to define the core problem, quantify the value opportunity, and map out a practical path forward that aligns with commercial outcomes.
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SAHIL KUMAR Project Management Jamnagar, India
The first thing comes in my mind is "Do we really need AI ?"

lets discuss the problem first and then see whether AI can help us or not. Knowing the problem and better understanding of process and identifying gaps are important.

Curious to listen ideas and understanding them, but not rush with AI if someone else is using it for their work. Others use might didn't solve our problems.
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Othmen Moumni manar, Tunisia
Importance AI in the project management
Artificial Intelligence (AI) plays a transformative role in project management by enhancing decision-making, improving efficiency, and enabling data-driven outcomes across all project phases. It helps organizations analyze large volumes of data to identify opportunities, predict risks, optimize schedules and resources, and monitor performance in real time. AI also automates repetitive tasks such as reporting and tracking, allowing project managers to focus on strategic leadership, stakeholder engagement, and value delivery. By providing predictive insights and intelligent recommendations, AI increases accuracy, reduces uncertainty, and supports proactive management, making projects more agile, cost-effective, and aligned with business objectives.
AI does NOT replace the project manager. Instead, AI acts as a decision support tool, while the project manager remains a leader, strategist, and communicator.
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.
Ai=I is an impressive platform to including it as in analysis tool, but should we align and depend on AI aspects and depend on it.
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Moutasem Mohamed Heliopolis, C, Egypt
First, I ask: what problem are we trying to solve? (cost, time, accuracy, risk).
Then: what does success look like? (KPIs, measurable outcomes).
Next: what data do we have and how clean is it? (AI is only as good as input).
Then: what’s the current process baseline? (so we can justify improvement).
Also: constraints (budget, integration with existing systems, security, timeline).
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Gustavo Mendez Project Manager, BsCE, MScPM, PMP®| Nucleoeléctrica Argentina, S.A La Plata, Buenos Aires, Argentina
The effectiveness of AI depends on our correct understanding of its limitations. We cannot expect AI to do all the work or replace human context interpretation, ethics, or reasoning, but rather to complement it. Once we understand this, we can use AI to help us expedite problem-solving.
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Tiffany Lehn Tempe, AZ, United States
When I hear this statement, my interpretation is, "we should utilize AI tools to manage this workflow more thoroughly, effectively and efficiently."
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Lisa Cantavespre Al, United States
what’s really being asked when someone says “we should use AI” , I follow up with questions to uncover what benefit and value will be created and ensure complex problems are fully understood.
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Anas Abu Yousef National projects and construction abu dhabi, AZ, United Arab Emirates
AI can be used in a ways to save time and increase your productivity.
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