AI Procurement for Business
How to procure AI tools and services. Vendor selection, contracts, deployment.
Standard procurement plus
Data use rights, model training rights, AI ethics commitments, regulatory cooperation, evaluation methodologies.
Common pitfalls
Demo-driven decisions, ignoring integration cost, inadequate POCs, weak contracts on AI-specific terms.
Best practices
POC for production candidates, multi-vendor evaluation, reference checks, ethical AI commitments, exit terms.
Bottom line
AI procurement requires AI-specific expertise. Procurement teams need to evolve.
Frequently asked questions
AI procurement different how?
Data rights, model use, ethics commitments specific to AI. Standard SaaS contracts inadequate. AI-specific terms required.
Should procurement team have AI expertise?
Increasingly yes. AI procurement requires understanding capabilities, evaluating quality, negotiating AI-specific terms.
POCs essential?
Yes for production candidates. Reveals integration issues, quality reality, change management needs. Worth the time.
Reference checks?
Yes — talk to similar customers about real deployment experience. Major signal beyond demos.
Contract terms unique to AI?
Data use, training rights, model ownership, ethics commitments, regulatory cooperation. Standard contracts miss these.
Related guides
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