AI vendor due diligence must follow the workflow, not the brochure
Enterprise AI risk depends on what a product can access, infer and change in the actual workflow, not only on the vendor model card.
Sourcing, vendor management, contracts, spend visibility and software buying. Practical guidance for evaluation, implementation, governance and day-to-day operation.
Enterprise AI risk depends on what a product can access, infer and change in the actual workflow, not only on the vendor model card.
Read the lead insightEnterprise AI risk depends on what a product can access, infer and change in the actual workflow, not only on the vendor model card.
Agent marketplaces can accelerate adoption while creating new questions about provenance, permissions, support, pricing and accountability.
AI-enabled software contracts need clearer language on model changes, data use, actions, auditability, performance and exit.
Procurement is balancing agentic features, SaaS consolidation, data sovereignty, flexible models and growing third-party dependencies.
A practical checklist for reviewing an AI supplier before pilot, contract and production access.
A qualitative model for assessing intake, due diligence, contracting, access approval, monitoring and renewal decisions.
Decisions about strategic sourcing platforms improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about strategic sourcing platforms improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about strategic sourcing platforms improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about procurement analytics improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about spend analytics improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about contract lifecycle management improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about software procurement improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about software procurement improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
A useful scorecard records evidence, trade-offs and operating effort. It should not reward the vendor that checks the most boxes.
Decisions about category management improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about category management improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about category management improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about category management improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about category management improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about renewal management improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about procurement analytics improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about contract lifecycle management improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Decisions about spend analytics improve when procurement leaders define the work, ownership, evidence and exceptions before selecting or expanding technology.
Try “AI governance”, “buyer guide”, “finance” or “CRM”.