A four-week, fixed-fee diagnostic that maps where AI is in use across sourcing and the supplier base, reconciles it against what your contracts already commit you to, and gives leadership a roadmap they can act on.
Some of it arrives by decision: an intake tool, a contract platform, a sourcing event run with AI assistance. Much of it arrives without one, through feature updates in software the company already licenses and through suppliers using AI on their side of the relationship. Most procurement teams we speak with can describe the first kind in detail. The second kind is usually harder to see, and it is where the questions about data and contract terms tend to sit.
A senior-led sequence with scope agreed up front. The advisor who scopes the work is the advisor who delivers it.
Hive's procurement work draws on leading the strategy behind the sourcing organization at a Fortune 100 insurance company, including developing and implementing its AI strategy and governance framework. That program put a front-end solution in place that sped up the sourcing request process, along with a contract management and RFx platform that provided insights across the portfolio. The team landed on two full solutions after months of evaluation, and the portfolio was consolidated by nearly 32%.
AI in procurement is most often used for intake and request triage, contract analysis, RFx preparation, spend classification and supplier risk monitoring. What we typically find in mid-market companies is a mix of tools the team chose deliberately and AI features that arrived inside software the company already licenses. The second group is often the larger one, and it tends to sit outside any formal review of data use or contract terms.
In our experience, the most useful first step is a clear view of where AI is already in use across sourcing and the supplier base, before new tools are selected. That view shows which requests, contracts and suppliers carry the most exposure and where a tool would help most. Our four-week, fixed-fee diagnostic is built to produce it, together with a roadmap leadership can act on.
AI features added by existing vendors can usually be identified through release notes, admin settings, updated data processing terms and a short set of questions to each vendor's account team. Some of these features appear during routine product updates, so they rarely pass through a purchasing decision. During the diagnostic we review the vendors in scope this way and record what each feature does with company data.
Supplier contracts increasingly need to address whether the supplier uses AI in delivering the service, whether your data can be used to train models, how new AI features are disclosed, and which subprocessors handle your information. Hive is not a law firm, so this work is done alongside your legal team. What we provide is the operating view: where current agreements are silent, and which renewals are the practical moment to revisit the language.
Hive's AI diagnostic for procurement runs four weeks on a fixed fee, with scope agreed at the start. It delivers an AI usage map across sourcing and the supplier base, a reconciliation against supplier agreements and data terms, a view of the suppliers carrying the most exposure, and a prioritized roadmap. The first step is a 30-minute briefing with a senior advisor, with an NDA in place before anything confidential is shared.
A senior Hive advisor will walk you through what the diagnostic would look at in your sourcing organization.
30 minutes · No pitch · Senior advisor · NDA before disclosure