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Three reports, written separately, reached the same conclusion

I spent more than twenty years in this industry before I built anything, and I did not need a report to tell me it was broken. I had lived it. This summer, three arrived anyway. In July, McKinsey published its analysis of AI in engineering and construction. Around the same time, Batimatech, the Montreal non-profit that gathers this sector to talk about its future, published a white paper of its own, built on Canadian data. In September, MIT and Suffolk, the Boston-based builder, released a joint study on construction in the age of AI. The three teams worked separately. One looked at the global picture, one at Canada, one at the United States. They reached the same conclusions.

The most expensive mistakes in infrastructure happen before anyone breaks ground

When a major infrastructure project overruns, the news covers the cranes and the concrete. The real mistake was often made months earlier, in a room full of documents, before anyone broke ground. I spent eleven years as the group Chief Risk Officer of one of the world’s largest infrastructure firms, reviewing our biggest and most exposed projects across the globe. Before that I worked on the client side, ran an engineering group, and led bids on projects worth billions.

I was the customer before I built the product

Most construction software targets the build: estimating, scheduling, safety. The pre-construction stage, where bids are won and lost, is underserved, and truly AI-native platforms barely exist because incumbents retrofit AI onto old systems rather than building from scratch. EllisDon CIO Brandon Milner explains where the real opportunity in construction technology sits and why it is hard for incumbents to seize.