Collect
Gather current, approved renewal signals from defined sources.
01 · Workflow
Start with buyer evidence, not vendor uplift.
The workflow uses only approved contract, usage, service, pricing, stakeholder, and renewal-planning data. It does not invent leverage, predict outcomes, or contact anyone autonomously.
Separate
Distinguish usage facts, vendor claims, internal assumptions, and gaps.
Brief
Create a concise risk, value, leverage, and open-issues narrative with cited support.
Plan
The renewal owner validates context and chooses human negotiation actions.
02 · Prompt example
Evidence before prediction.
A disciplined prompt prevents the model from presenting a plausible renewal story as established fact.
Renewal evidence brief
Organize the renewal information into: verified value received; unused or underused modules; service issues; pricing assumptions; contract constraints; alternative options; missing information. Cite the dated source for each item. Do not assign a renewal probability.
Renewal-owner checklist
- Remove stale or duplicated signals
- Correct missing commercial context
- Confirm usage and service evidence
- Choose negotiation posture using judgment
03 · Example output
A compact action brief.
Designed to prepare a better renewal position, not replace negotiation judgment.
| Signal | Evidence | Human follow-up |
|---|---|---|
| Unused module | Purchased but no active users in current period | Validate removal, credit, or substitution options |
| Open service issue | Support escalations unresolved before renewal | Tie remediation to renewal discussion |
| Benchmark gap unknown | No current comparable pricing in file | Decide whether benchmarking is needed |
04 · What's included
What this playbook includes.
A product-ready structure for an AI renewal risk playbook focused on value, usage, leverage, and renewal preparation.
| Component | Included detail | Purpose |
|---|---|---|
| Use case | AI-assisted renewal risk and leverage review | Prepare before the vendor frames the renewal |
| Intended user | Renewal owner, procurement, customer success, vendor management | Support commercial judgment |
| Required inputs | Contract terms, usage data, service history, pricing notes, alternatives | Ground renewal strategy in facts |
| Output artifacts | Renewal brief, risk log, leverage checklist, action plan | Create an accountable planning packet |
| Review controls | Evidence checks, assumption labels, human negotiation review | Avoid invented leverage |
| Common failure modes | Vendor-led uplift framing, stale usage, missing benchmark context | Prevent weak renewal posture |
| Related playbooks | Vendor evaluation, procurement, contract review, compliance | Connect renewal to the full buying lifecycle |
05 · Guardrails
Renewal judgment stays human.
No hidden scoring
Do not generate pseudo-precise renewal probabilities from incomplete account notes.
Respect permissions
Use only customer, vendor, and contract data approved for the selected AI environment.
No autonomous outreach
A human owner reviews context, tone, timing, leverage, and every communication.
Buyer-controlled renewal practice
Licensing & partners ↗Turn AI capability into disciplined renewal preparation.
Illustrative concept content only. Adapt the workflow to applicable privacy, contractual, security, and organizational requirements.