United States buyer guide

Local AI procurement and vendor comparison in United States

A buyer-led way to compare product scope, evidence, commercial terms, implementation, and local readiness.

Why read this

Read this before reducing a complex shortlist to a vendor score or signing a pilot statement of work.

Put products in the same category only when they address a comparable job. Record intended use, evidence scope, deployment model, integration burden, support, and the buyer capability required to operate each option.

Evidence: NIST AI Risk Management Framework

Ask for evidence that can be checked

Request current security and privacy material, evaluation results, customer references, accessibility information, service levels, data-processing terms, incident history, model-change notices, and exit commitments. Separate a supplied claim from independently checked evidence.

Evidence: NIST Generative AI Profile, FTC guidance on AI claims

Price the whole operating model

Include implementation, integration, training, review, monitoring, incident response, data preparation, change management, and exit. A low licence price is not low cost if the buyer must build the missing control plane.

Evidence: CISA AI cybersecurity guidance

Questions for the buying team

  • What exact job and outcome are being bought?
  • What evidence is independent, local, dated, and relevant?
  • What is the full cost and responsibility for operating, monitoring, changing, and exiting the system?

Local evidence boundary: this guide organises questions and sources. It is not a legal, security, clinical, financial, procurement, or implementation approval.

Sources and further reading

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