The spreadsheet industry has it backwards. For months, the conversation around AI in spreadsheets has been dominated by pricing models, subscription tiers, and per-query costs, as if the future of data work will be decided by a billing page. It will not. The only question that matters is whether the AI actually helps you finish your work, understand your data, and stop wrestling with formulas. Everything else is a distraction.
This focus on outcomes over pricing is not naive idealism. It is a practical lesson we have seen play out across the entire AI landscape. Consider the projects that stalled or fell short entirely. As we explored in Learning from AI's missteps: Projects that stalled or fell short, even the most well-funded AI initiatives fail when they lose sight of what users actually need to accomplish. The same principle applies at the spreadsheet level. A tool that costs pennies per query but forces you to restructure your workflow around its limitations is not a bargain. It is a tax on your time. Conversely, a tool priced at a premium that reliably transforms a three-hour reconciliation into a five-minute review is worth every cent. The price tag is a secondary concern. The primary concern is whether the tool closes the gap between where you are and where you need to be.
The challenge for buyers is that pricing models are easy to compare. Outcomes are not. A per-query model might look transparent until you realize that a single complex analysis requires dozens of queries. A flat subscription might seem expensive until you factor in the hours of manual work it eliminates. This is where the industry's obsession with architecture and infrastructure becomes relevant. As our piece on Six architecture patterns to govern enterprise lakehouses with AI made clear, the underlying structure of an AI system determines what it can actually deliver. A spreadsheet AI built on a naive chunk-and-embed approach will produce different outcomes than one built on a governed, context-aware architecture, regardless of what either vendor charges. You cannot evaluate the outcome by looking at the pricing page. You have to look at what the tool produces on your actual data, under your actual constraints.
Here is the concrete takeaway: When evaluating AI for your spreadsheets, run a single real-world test. Take a task that currently takes you thirty minutes and see if the AI can complete it in under five with acceptable accuracy. If it can, the pricing is a negotiation. If it cannot, the pricing is irrelevant. The market will eventually sort itself out, but the only way to avoid wasting money in the meantime is to anchor every decision on the outcome, not the invoice.