Find renewal risk before the QBR
Renewal risk review fails when account teams discover trouble after the customer has already disengaged. Usage changes, unresolved tickets, stakeholder turnover, QBR notes, contract terms, and salesperson judgment often sit in different systems, so the workflow has to connect signals before the renewal meeting.
RSM's middle-market AI survey provides the adoption backdrop, but retention teams need a specific operating question: should AI help account owners prepare, or should it score risk, trigger review queues, and route save-plan actions through CRM and customer-success systems?
Use Copilot for account prep, custom AI for risk orchestration
Copilot can summarize Teams notes, emails, QBR documents, account plans, and executive updates for a customer success manager. Microsoft's privacy and architecture materials support that account-prep role because access follows user permissions and Microsoft 365 context.
Custom AI is justified when renewal review needs usage joins, ticket-history analysis, sponsor-change detection, risk scoring, renewal-calendar triggers, CRM enrichment, and leader review queues. NIST should guide risk scoring oversight and escalation, while CISA-style controls matter because renewal workflows expose customer, commercial, and support data.
Run the test on real renewals
Deloitte's 2026 AI research points to activation as the value gap. For renewal risk, do not test on abstract examples. Use accounts renewing in the next 90-180 days and compare whether the workflow finds risk earlier than the current cadence.
Measure forecast accuracy, renewal-risk lead time, save-plan creation rate, escalations avoided, CSM override rate, and gross or net retention impact. Keep Copilot for prep when the account owner remains the only decision maker. Build custom workflow when risk detection and escalation need to run consistently across the portfolio.
