Twenty supplier offers: where the change AI brings is hard to reach

Fundamental change that AI brings might sound simple, yet it is hard to reach.

Imagine a company buying glass bottles. Twenty supplier offers arrive as PDFs, spreadsheets and emails. Some omit delivery costs, others use different units, and the contract terms conflict.

Someone in the team has to read each file, reconcile the differences and revisit the comparison whenever a supplier sends a revision.

An AI-assisted workflow could prepare that comparison across the whole set: extract prices and terms, calculate costs using checked formulas, retain links to the sources and flag missing or conflicting information for review. A revised offer would trigger the relevant calculations and checks again.

The same rules can run across every submission and revision. The team defines and improves the method, rather than reconstructing the comparison file by file.

That changes the work itself. People spend more of their attention checking exceptions, challenging assumptions, negotiating and deciding. Their expertise also becomes part of how the workflow operates.

A buyer knows that a price without delivery costs is incomplete. That becomes a check. A review exposes another omission; the correction becomes a tested rule for the next purchase. The method gets better because someone who understands the work keeps improving it.

Leadership provides the tools, data access, time and technical support. The people closest to the job define what a good result requires.

This is how AI can change a team's role: from preparing each analysis to owning a method that can handle a larger, messier workload.

Do you recognize this change happening?