h1Most of the time when people say "When someone says, “we should use AI,” they want to say that they want it to be done fast and the results should be better. Very less people understand the costs of implementing AI./h1 Saving Changes...
In most cases, the underlying question is not about AI itself, but about which specific tasks or components of the project could benefit from AI support. I would guide the conversation toward identifying areas where AI can add real value, such as:
Automating reporting Supporting risk analysis Helping monitor timelines and project health Streamlining repetitive or data-heavy tasks
From a project management perspective, the goal remains the same: deliver on schedule, within scope, and on budget. AI is a tool(s) to help us get there more efficiently.
I like to think of AI as a highly sophisticated aircraft. As the project manager, I am the pilot. It is my responsibility to understand what each control does, when to use it, and how to operate it effectively.
Without that understanding, adding AI does not improve outcomes; it just adds complexity.
So instead of asking, “Where can we use AI?”, I shift the question to: where can AI improve how we deliver this project? Saving Changes...
let AI handle efficiency, and humans lead with judgment, ethics, and relationships. Saving Changes...
Carlos Andrés Naranjo CallejasIT Project Manager, PMP®, Agile Leader, Digital Transformation, PaymentsBogota, Cundinamarca, Colombia
Probably in many companies heard about AI from large IT companies without understand well about if really needs it. Saving Changes...
Funmilola IyiolaPrincipal Consultant| Trending B&PM ConsultingAbbotsford, British Columbia, Canada
Feb 22, 2026 7:45 AM
Replying to Sergio Luis Conte
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The first thing is to clarify what AI means. Human beings are using AI from more than 50 years ago. We are surrounded of AI entities embeded inside refrigerators, air conditioners, cell phones, etc, etc, Unfortunately in the last time some people and organizations are contributing to the general confusion using generative AI as a synonim of AI.
I quite agree with you. We first need to clarify and establish what AI means in any task or project we are handling to avoid confusion.
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1 reply by anonymous
Jun 02, 2026 5:44 PM
anonymous
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AI enhances the human brain, not replace it. A lot of folks I work with are afraid of using AI and be replaced.
Saving Changes...
Funmilola IyiolaPrincipal Consultant| Trending B&PM ConsultingAbbotsford, British Columbia, Canada
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.
Yes, I agreed with you on this. Saving Changes...
Funmilola IyiolaPrincipal Consultant| Trending B&PM ConsultingAbbotsford, British Columbia, Canada
Yes, AI” meant different things to different people" and it triggers adapting to trending innovative approaches, tools, and ways of handling complex issues, systems, or projects efficiently. Saving Changes...
Inportant to understand what do you want to achieve with AI? Once the outcome is clear, we can define the right approach, tools, and path forward. 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.
"If you have an apple and I have an apple and we exchange apples then you and I will still each have one apple. But if you have an idea and I have an idea and we exchange these ideas, then each of us will have two ideas."
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