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.
Also, to add, Do we see this as a cost saving initiative or a growth investment - how does that influence your budget? Saving Changes...
Akhil NathRisk consultant| KPMGMaharashtra, MH, India
When someone says, “We should use AI,” they are not setting the clear requirements, what is the problem that AI will solve. Saving Changes...
Ahmad El ZaimMartin ProfessionalDubai, DU, United Arab Emirates
when people say let's use AI, it's often seen as a way to solve an underlying problem or resolve a task, when it's truly a way to help analyse data, give more insight about a problem and give a perspective to help individuals navigate through a problem or solve a specific task, automate a process. Saving Changes...
Rich WellerMBA, PMP, Project Certified, Agile Certified, AI Credentials| MIGSO-PCUBEDMilan, Mi, United States
As noted in this course; at this point in time, there is no agreed upon definition of the term AI or Artificial Intelligence. It is being used as an "umbrella" term. I have now completed the course and can say this: This course provides very good guidance on the different "Patterns" of AI and provides insight into whether AI is a good fit for the project and which Pattern(s) would be most relevant. Saving Changes...
In my current role it is usually tied to a request that will go to our design team. For creative writing and graphics I think AI is a good approach for a first draft. The issue I run into is when I am asked by a higher level manager to use it in a project setting where the tool
Does not have access to the Project Management software we use.
Does not have access to our data management system
Does not have the fine tuning to make adjustments to projects without in-depth training of an agent.
It is usually just because they want to find a way to capitalize on AI efficienecies. In creative work, this is easy. For in-depth project management it requires some specific coding in MS Powershell or applying it to work in Microsoft applications via co-pilot. Saving Changes...
Interesante debate. Desde mi experiencia, la inteligencia artificial se integra como una herramienta que potencia nuestros proyectos, pero no sustituye la toma de decisiones, la creatividad ni la experiencia que aportamos como profesionales. Más bien, amplifica nuestras capacidades al permitir transformar ideas y experiencias en instrucciones claras y precisas, generando resultados más rápidos que pueden servir como punto de partida para la discusión en equipo. Al inicio, debo admitir que percibí la IA como una amenaza; incluso llegué a considerarla una forma de “hacer trampa” o de omitir procesos. Sin embargo, con el tiempo he comprendido que se trata de un recurso que complementa nuestro expertise. La IA, por sí sola, no construye proyectos: requiere orientación, contexto e instrucciones bien definidas para generar valor. En la práctica, su uso efectivo implica un proceso iterativo: se plantean indicaciones claras, se analizan los resultados en conjunto con el equipo, se promueven lluvias de ideas, se evalúan alternativas y se identifican variables clave. A partir de ello, se refinan los modelos y las propuestas hasta alinearlas con las expectativas y objetivos del proyecto. Reitero que la IA es una herramienta poderosa para fortalecer el trabajo en equipo y mejorar la calidad de los resultados. Los invito a utilizarla de manera crítica y estratégica, y a compartir sus experiencias sobre los resultados obtenidos. Saving Changes...
Matimba ManuwaTechnical Project Manager| T-MOBILEFrisco, Tx, United States
My approach is usually to ask clarifying questions and understand the goal we are trying to achieve. This will help distinguish the kinds of AI that should be used. Saving Changes...
Anonymous
Where things tend to go wrong is when everything gets lumped under “AI.” That’s when you start seeing mismatched expectations, overcomplicated solutions, or teams talking past each other without realizing it. I’ve been in meetings where someone said “let’s use AI to automate this,” and it turned out one person meant something like ChatGPT, another was thinking of a trained model, and someone else just had a rule-based system in mind 😂 Now whenever I hear that phrase, I always pause and ask: – What exactly are we trying to solve? – What’s the input and expected output? – How do we define success? Getting those aligned usually clears up most of the confusion. Saving Changes...
When we talk about “using AI,” it’s important to clarify what problem we’re aiming to solve and how it aligns with our strategic objectives. From a project management standpoint, we need to define scope, expected outcomes, and success measures before moving forward.
I suggest we start by identifying the specific business case for AI adoption—whether it’s improving efficiency, enhancing decision-making, or reducing costs. Once that’s clear, we can outline requirements (data, tools, skills), assess risks (bias, compliance, change management), and determine how AI integrates into existing workflows.
To keep this structured, we could draft a project charter that captures objectives, stakeholders, deliverables, and KPIs. This will help us evaluate feasibility, prioritize resources, and ensure alignment across teams.
In short, “using AI” should be treated as a formal initiative, not just a technology experiment. Let’s frame it within PMI’s process groups—initiation, planning, execution, monitoring, and closing—so we can manage expectations and realize tangible benefits.
Clarifying the Intent
Problem definition: What challenge are they actually trying to solve? Is it efficiency, creativity, cost reduction, or decision-making?
Scope: Do they mean applying AI to a specific task (like automating customer support) or a broad transformation (like “AI-first” strategy)?
Expectation: Are they imagining a quick plug‑and‑play tool, or a long-term investment in data infrastructure and model training?
Practical Considerations
Data readiness: Do they have the quality and quantity of data needed for AI to be useful?
Integration: How will AI fit into existing workflows, tools, and people’s roles?
Risks: What about bias, transparency, compliance, or security concerns?
Underlying Motivations Often, “use AI” is shorthand for:
Keeping up with competitors (fear of being left behind).
Exploring innovation (curiosity about new possibilities).
Reducing costs or scaling (automation and efficiency).
Enhancing decision-making (insights from data).
So, when someone says it, the real task is to probe: Do they want AI because it’s trendy, or because it’s the right tool for the problem? That distinction changes everything.
While AI reduces workloads by drafting code or test cases, Human Ownership is non-negotiable for validation and accountability. The real hurdle is the high cost and rapid tool sprawl. Navigating the 'AI' hype requires a sharp focus on ROI, ensuring we select sustainable tools that offer genuine efficiency rather than just adding to the daily overhead of keeping pace with the market." Saving Changes...
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