Summarize risk before the renewal meeting
Renewal risk review is a good first customer-service AI use case because most teams already have the evidence: support history, unresolved escalations, product usage, commitments from the sale, and customer-success notes. Salesforce State of Service 2025 is relevant because service teams are moving into more complex, AI-assisted responsibilities; the immediate value is better context for human teams.
Salesforce State of Sales also matters because renewal work crosses sales and service. The AI system should reconcile account promises and service experience before a human decides whether to escalate, save, expand, or let the account reset.
Keep the recommendation explainable
The workflow should cite the ticket, transcript, usage note, or commercial commitment behind every risk flag. NIST AI Risk Management Framework is a useful frame because renewal recommendations affect customer treatment and revenue prioritization, so the system needs mapping, measurement, control, and governance.
McKinsey State of AI 2025 is relevant because scaled AI value comes from workflow redesign, not isolated pilots. A renewal-risk workflow only works if the summary leads to a consistent account-review cadence.
Measure action quality, not just summary speed
Track source completeness, false-positive risk flags, save-plan acceptance, escalation quality, and renewal-team time spent preparing for review. The target is a better human decision before the renewal window, not an automated account verdict.
Use customer-service AI workflow design for the operating model and the AI Opportunity Score to prioritize whether renewal risk belongs ahead of ticket triage or reporting.
