Our New Year’s Resolutions: Where AI Meets the Real Economy

Everyone’s talking about AI. Very few are talking about economics.

Wall Street is euphoric. A handful of stocks are carrying the market. Meanwhile, the real economy is grappling with housing shortages, labor constraints, and the rising cost of capital.

That gap matters. When markets and lived experience drift too far apart, capital starts chasing narratives instead of fundamentals, and that’s usually when risk quietly piles up.

So heading into 2026, we’re setting three clear resolutions for how we think about AI in construction, and where it can drive real impact in housing and construction fundamentals.

1. Avoid AI monoculture — invest where real economics still exist

Housing is a powerful example of where real economic value is being created and where capital is increasingly mispriced. While markets fixate on AI narratives, housing continues to face structural shortages, rising demand, and constrained supply.

What makes this moment different is that modern construction methods and new financing structures have made scalable housing development both executable and investable. Returns are grounded in real demand, real assets, and real cash flow, with the flexibility to return capital quickly, hold long-term, or do both.

Housing investments also avoid the very risk many associate with AI: the bubble. You’re backing provable demand against a 5–10 million unit housing deficit across North America, not betting on adoption curves or hoping competition doesn’t materialize. Housing creates new entry points for buyers without destabilizing existing homeowners, supports local economies, and enables steady (not speculative) growth.

So the opportunity isn’t AI or the real economy. It’s AI applied to the real economy.

2. Back AI that strengthens fundamentals

AI doesn’t fix broken business models, it accelerates them. We’ve seen this play out repeatedly: tools that promise efficiency layered onto businesses with weak unit economics, fragile cash flow, or unclear demand. The result isn’t transformation, it’s faster failure with better charts.

At the same time, AI is changing what strong fundamentals look like in construction and housing, for example, by automating site execution, speeding up permitting reviews, and helping small teams manage complex schedules at scale. By automating execution, compressing decision cycles, and enabling small teams to operate at enterprise scale, AI is breaking the traditional link between headcount, cost, and output. Old benchmarks are becoming less reliable, and tomorrow’s winners won’t look like slightly better versions of today’s contractors — they’ll operate on entirely new models.

3. Invest in adaptability, not static efficiency

The biggest risk in 2026 isn’t inefficiency, it’s rigidity.

Markets are shifting too quickly for static operating models to survive. The companies that win won’t be those optimized for a single forecast, but those built to adapt as conditions change. That means flexible cost structures, variable operating models, and the ability to redeploy capital as realities shift.

In an AI-enabled world, resilience comes from optionality: the ability to scale up or down quickly, handle volatile material costs, adapt to labor shortages or permitting delays, and compress execution risk on real projects without blowing budgets or timelines. We prioritize teams and platforms designed for change.

The Takeaway Heading into 2026

So, as we head into the new year, the takeaway is simple: the most compelling opportunities won’t come from choosing between AI and the real economy, but from unlocking AI to tackle real economic constraints like housing shortages and construction inefficiencies, within an operating environment evolving faster than anything we’ve seen before.