How Can Leaders in Construction Project Management Begin Adopting Machine Learning?
Let’s start with this idea: machine learning is all about identifying patterns in data.
Without structured data, there’s nothing to model—no patterns to detect.
And that is one of the main challenges in the AECO sector. While significant progress has been made in structuring information—especially through the integration of cost estimating, design, BIM models, and reality capture technologies—there is still a gap when it comes to connecting these data streams in a consistent and fluid way. We are generating better information, but turning it into usable and reusable datasets for AI analysis remains difficult.
Those of us in the field are deeply familiar with the constraints, dynamics, and interactions among the different stakeholders. But that also gives us a unique advantage: we can lead change from within. To do that, we face a dual mission—build useful datasets and learn how to extract value from them.
📚 McKinsey suggests three concrete actions to integrate AI in the AECO sector (Artificial Intelligence: Construction Technology’s Next Frontier):
- Identify where AI solutions are already emerging within the industry.
- Study successful cases from other industries and explore how they could be adapted.
- Evaluate which algorithms may apply to our specific problems.
That said, we must stay grounded. Many industries are currently experiencing a collective (and sometimes frantic) excitement about AI. With the rise of Generative AI, new and improved models are released almost weekly. It's easy to fall into the FOMO trap.
That’s why our team at Entrez Ingenieros Civiles attended the Analytics Forum 2025 at Universidad de los Andes—to learn.
We encountered leaders from sectors such as education, logistics, banking, healthcare, and agriculture. As far as we could tell, we were the only attendees representing the construction industry. Here are some key takeaways from the event that sparked reflection:
👨🏫 Ryan Keenan (Deeplearning.ai):
One of the world’s leading AI and ML educators, Keenan highlighted two essential learning tracks for professionals:
- Strengthen foundations in data science, AI, and programming. (Chatbots and vibe coding won’t replace programmers any time soon—but they will raise the bar.)
- Develop soft skills like critical thinking, leadership, and the ability to teach others.
💡 Recommendation: Explore the courses on Deeplearning.com to better understand the mathematical and data requirements behind AI.
💡 Bonus tip: Interact with Andrew Ng’s avatar to create a personalized learning path.
🧠 Alejandro Correa (AI Hype vs AI Reality):
His session was exactly what the audience didn’t know we needed. Correa emphasized the distinction between AI hype and AI reality. While the potential is immense, the predictive power of AI is entirely dependent on the quality of input data. And—human judgment is still irreplaceable. (See this experiment where a company was run entirely by AI agents to explore the implications.) Correa believes AGI is not attainable.
🚛 Julián Pachón (Amazon Last Mile):
As Amazon’s Global Director of Last Mile Technology, Pachón delivered a masterclass on simplifying complex ideas. He explained how Amazon optimizes its global logistics network using data science, ML, and interdisciplinary teams.
It sparked a question: how much could we optimize supply chains in construction projects by applying the same approach? While our sector faces different challenges (on-site execution, prefabrication, advance payments, hundreds of suppliers, limited storage), there are valuable insights we can adapt.
💡 Recommended: Watch his interview with Robbie Frye YouTube
🤖 María Paula Ríos (Alianza Team):
We first learned about Alianza Team through an interview with their CEO, Luis Alberto Botero, and later listened to María Paula Ríos at the forum.
She demonstrated why Alianza Team has successfully tackled both the technical and human challenges of digital transformation. María Paula blends deep business knowledge with scientific expertise and outstanding leadership. Her ability to articulate a vision, connect with people, and execute complex strategies stood out. She also addressed the role of women in technology—a critical topic.
And just like in construction, her industry faces the challenge of transforming real-world operations with real people in unpredictable environments. A valuable parallel.
Two concepts to act on immediately within our organization:
- Data Governance/strong>: Set clear policies, roles, workflows, and metrics to ensure data is usable, accessible, and reliable.
- Cybersecurity: When using third-party models, safeguard operational data and client privacy.
Final thoughts The goal isn’t to jump on the AI bandwagon just because it’s trending—but to do it with intention. That means building structured data, identifying patterns, and above all, staying curious and open to learning from other sectors.
At Entrez Ingenieros Civiles, we will continue exploring new paths to bring value to the AECO sector through data, technology, and—always—collaborative teamwork.