A problem many teams know firsthand: too many prototypes, too few products. Enterprise AI stalls not because the technology fails, but because the gap between a promising experiment and a reliable tool remains stubbornly wide. We agree. The real challenge isn't building a model that works in a notebook, it's turning that model into something people can trust and use every day.
For spreadsheet users, this gap is especially familiar. You've likely built a clever macro, a complex formula, or a dashboard that solves a specific headache. It works perfectly for you. But sharing it with a colleague means explaining the logic, handling edge cases, and watching it break the moment someone enters data differently. That prototype-to-product chasm is where most AI experiments die. The data science community has spent years celebrating prototypes as proof of concept. What it needs is a clearer path to production, tools that don't require a rewrite to become usable by people who aren't data scientists.
This matters because the promise of AI in spreadsheets isn't about flashy demos. It's about making everyday tasks faster and less error-prone. When a prototype stays a prototype, the user never sees the benefit. The organization never recovers the time invested. Enterprise AI stalls when teams focus on the novelty of the experiment rather than the durability of the result. We'd add that the same is true for any tool that promises to transform how people work with data. If it can't survive contact with a real workflow, it's not a product, it's a hobby.
So what does this mean in practice? Look for solutions that prioritize reliability over novelty. A tool that handles one scenario beautifully but breaks on the second is not ready for your team. A prototype that requires constant hand-holding is not a time-saver. The next time you evaluate an AI spreadsheet feature, ask not what it can do in a demo, but what it does when a row of data is missing, or when a formula returns an unexpected result. The teams that turn prototypes into products are the ones that design for the messy, unpredictable reality of daily work. That is the standard worth adopting.