Everyone’s talking about AI. Every week there’s a new “intelligent” tool promising to automate the toughest parts of construction workflows. But there’s one inconvenient truth the tech industry seems to forget: construction still runs on spreadsheets.

Across the job trailers, estimating departments, and field offices of the world, Excel is alive and well. It’s not because people don’t want to change, it’s because Excel works. It’s flexible. It’s familiar. It bends to fit the messy, nuanced, and ever-changing nature of construction projects.

Why Excel Still Rules the Job

Construction is complex. It's filled with exceptions, revisions, and judgment calls that rarely fit into rigid systems. And nowhere does that complexity show up more clearly than in estimating, where every assumption, rate, and scope line can shape the success or failure of a project.

Estimating isn’t just math. It’s judgment, experience, and logic layered into a structure that must flex with each project. Contractors tweak cost structures, add unique conditions, code in a way that matches both owner requirements and internal reporting.

Excel allows that freedom. It lets estimators think the way they think. Every row can mean something different to a different estimator. Every formula can adapt. And that freedom, however chaotic, is what makes it so powerful.

The trade-off, of course, is fragility. Links break, formulas get corrupted, and collaboration is clunky. But despite decades of software claiming to “replace Excel,” most of those systems failed to understand why Excel worked in the first place. They tried to control the estimator, not empower them.

The Real Risk in Tech Today

The biggest risk isn’t that construction firms are “behind” on technology — it’s that many technology teams approach the industry from the outside-in. Too often, solutions are built on assumptions of perfectly structured data, standardized workflows, and decision-making that can be fully automated.

But construction isn’t a tidy industry. Every project is different, every scope evolves, and every company structures its data a little differently. The result? Tools that look great in demos but fall apart in day-to-day use.

No workflow makes this more visible than estimating—one of the most data-rich, logic-heavy, and business-critical workflows in construction. Estimating is where every decision begins, and where risk and profitability are set in motion. If we can’t get estimating right, the rest of the project tech stack doesn’t stand a chance.

Where AI Actually Adds Value

For serious estimating—the kind that determines whether you win or lose a multi-million-dollar bid—AI can’t do an estimator’s job. Not yet, and not without context.

The opportunity isn’t in replacing estimators, it’s in empowering them. AI shines when it’s embedded into the estimator’s natural workflow: importing bid forms, matching historical items, analyzing quotes, or flagging inconsistencies. But it must live within a system that feels familiar and flexible enough that an estimator trusts it.

If we don’t solve for Excel—the flexibility, the structure, the ability to nest and organize costs in flexible ways—we’ll keep building tools around the problem instead of through it. And that’s what’s holding back the future of estimating.

The Future: Flexibility, Without the Fragility

That’s exactly what we’ve built at BidBow.

BidBow was designed from the ground up to mirror the freedom and flexibility of spreadsheets, while eliminating their chaos. It lets estimators structure and nest costs however they think best, while still capturing data in a consistent way that supports reporting, benchmarking, and yes—AI.

By embedding AI modules that power importing bid schedules and bill of quantities, importing and matching vendor quotes, and auto-estimating from historical data, BidBow combines human expertise with machine intelligence—without breaking the estimator’s flow.

We believe technology in construction should adapt to people, not the other way around. Because if we lose touch with the realities of how estimators actually work, we risk building beautiful systems that no one uses.

And the truth is simple: solving for Excel isn’t about replacing the old way—it’s about unlocking what comes next.