Transitioning Processes to AI and Between AI Platforms
Explore how to safely transition business processes to generative AI or between AI platforms while maintaining service continuity. Learn to evaluate continuity, cost, data readiness, and performance, implement phased pilots, and prepare fallback options. Understand how these factors guide build, buy, or partner decisions and influence prioritization, ensuring AI adoption minimizes disruption and supports strategic goals.
Moving the complaint backlog case from the legacy rules engine to generative AI is a business transition, not just a technology choice. The company must keep complaint handling running while it introduces GenAI drafting and retrieval of current policy material. It must also plan for a future vendor change that could alter cost, data handling, or response quality.
A low-risk transition evaluates four connected considerations before any broad rollout. Business continuity means keeping the complaint service available and retaining a workable fallback when the new AI-supported process cannot meet its agreed conditions.
Continuity, cost, data, and performance
For complaint handling, continuity requires clear ownership of exceptions. Staff must be able to return to the rule-based routing and manual drafting process if the GenAI output is unavailable, unreliable, or outside approved policy. The fallback is not a ...