AI Automation Vendor Checklist: Privacy, Access, Reliability and Exit Plan
Before connecting an AI vendor to business systems, review data handling, permissions, logging, failure modes, portability and the cost of leaving.
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Before connecting an AI vendor to business systems, review data handling, permissions, logging, failure modes, portability and the cost of leaving.
Read guide ↗Automation is valuable when rules and outcomes are clear. Some processes should remain human-owned because judgment, accountability or empathy matters more.
Read guide ↗A useful AI knowledge base needs controlled source documents, ownership and update rules so the assistant does not invent business policies.
Read guide ↗Before choosing an AI tool, map the repetitive admin process, identify exceptions and decide which steps are deterministic, assisted or human-owned.
Read guide ↗Build CRM follow-up automation that responds quickly without sounding robotic, over-messaging prospects or hiding important replies from humans.
Read guide ↗Prompt injection is a real design risk when AI reads untrusted content or can call tools. Reduce impact with trust boundaries, least…
Read guide ↗Measure automation value with baseline effort, exception rate, correction time and business outcomes instead of optimistic AI savings claims.
Read guide ↗Human review should be placed where a wrong action has meaningful consequences, not added randomly to every step of an AI workflow.
Read guide ↗AI can organize and score lead information, but rigid automation can reject valuable prospects. Build qualification around transparent criteria and human review.
Read guide ↗Use AI to handle repetitive enquiry work without hiding judgment, exceptions or sensitive customer situations behind a bot.
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