As I begin my mornings these days, I always gravitate toward the filter coffee in the cafeteria—it’s convenient, fresh, and waiting for me as soon as I walk in. It’s hard to resist when it’s right there and ready to go without any extra effort. However, as the day wears on, I inevitably start missing my Turkish coffee. The richness of the flavor is something I crave, and by midday, I usually find myself asking for a cup. Combining both in one day often messes with my sleep, but it’s a small price for enjoying my two favorite coffee styles.
On the teaching front, my classes aren’t too demanding yet, and I’m really enjoying the strategic planning course I’m delivering this week. The course is designed for two senior specialists—one is the head of the engineering department and the other is a geophysicist with over 30 years of experience in the oil and gas industry. Although their expertise isn’t in project management per se, their deep knowledge in their fields makes for some fascinating discussions, bringing practical insights to the table.
As I’ve been exploring more articles on AI in recent weeks, I’ve been specifically looking for generative AI applications in project management. One article that stood out to me is “AI in Project Management: Exploring Theoretical Models for Decision-Making and Risk Management” (2024) by Odejide & Edunjobi. It dives into how machine learning (ML) and deep learning (DL) models can improve decision-making and risk management in project environments.
While the paper provides a solid exploration of traditional AI tools, I’ve been searching for more insight into generative AI applications in project management. With the rise of ChatGPT-4 and the advent of custom GPTs, I’m more interested in seeing how these technologies can automate real-time decision-making and generate project reports on the fly. The article discusses deep learning and machine learning models, but it doesn’t fully delve into the dynamic capabilities of generative AI, which is now rapidly transforming project workflows.
Today, custom GPTs are helping project managers automate communication, scenario analysis, and even risk forecasting with far greater flexibility than traditional AI models. These advancements allow AI to not just assist in decision-making, but also to adapt and personalize workflows in real time—capabilities that would have significantly enriched the article.
As I look through the lens of generative AI, I’m seeing its impact grow at a pace that almost makes articles like this one feel outdated—just a few weeks after publication. Tools like ChatGPT are no longer just aids to project managers, but active participants in strategic planning, report generation, and project monitoring.
Interestingly, the article does emphasize the importance of ethical considerations, particularly when it comes to data bias in AI-driven decision-making. The authors stress that while AI can optimize decisions, human oversight is still crucial to ensure that biases aren’t unintentionally reinforced—a topic that remains highly relevant even as we push forward with generative AI technologies.
This article offers a solid overview of how AI models can enhance decision-making and risk management in project management, but it misses the dynamic, real-time adaptability that generative AI offers. As more articles are published almost weekly, it’s becoming clear that custom GPTs and ChatGPT-4 are leading the way in revolutionizing project management processes. I’m eager to see how generative AI continues to shape the future of project management, especially in areas like scenario planning, resource allocation, and team communication.
In the meantime, I’ll continue balancing my mornings with filter coffee and Turkish coffee, knowing that I need to moderate my caffeine intake if I want to avoid any more sleepless nights.