Project Context

Google Cloud is preparing a customer-facing launch for a new Vertex AI security feature that lets enterprise admins apply policy controls and audit logging to generative AI workloads. You are the Solutions Architect supporting the launch for one strategic financial-services customer and an internal cross-functional team of 11 people across Product, Engineering, Security, Legal, Sales, and Customer Engineering. The launch date is fixed in 8 weeks because the customer wants the feature included in its annual cloud governance review.

The challenge is not only technical delivery. The customer's CIO and procurement lead are non-technical, but they must approve rollout, budget, and change-management communications. They are concerned that "AI security" sounds risky and expensive, while the customer's security architects want precise details on IAM, Cloud Audit Logs, VPC Service Controls, and data residency.

Key Stakeholders

The Google Cloud Product Manager wants a clean reference launch by quarter-end. The customer's CIO wants a simple explanation of business risk reduction and no disruption to existing Gemini on Vertex AI pilots. The customer's CISO wants technical assurance that controls are enforceable. The account executive wants the deal expansion closed this quarter, even if scope is reduced.

Constraints

• Timeline: 8 weeks to launch
• Budget: $120,000 for enablement, workshops, and limited implementation support
• Team capacity: 11 people; no additional headcount
• Dependencies: Legal approval of customer-facing architecture deck by Week 3; Cloud IAM policy design sign-off by Week 4; customer change-advisory-board approval by Week 6
• Scope limit: only 2 production use cases can go live in the first release

Complications

1. The customer's CIO keeps asking for a "one-page plain English summary," while the security team rejects oversimplified messaging.
2. Engineering has flagged that one desired control may not be GA by launch and may require a workaround using Organization Policy and Cloud Logging.
3. Sales has already implied to the customer that all four AI use cases could launch together.

Deliverables

1. Create an 8-week execution plan with milestones, owners, and dependencies.
2. Propose how you would explain the technical concept to non-technical executives without losing stakeholder trust.
3. Recommend a launch scope for Week 8, including trade-offs and a fallback plan.
4. Define success metrics for executive alignment, customer readiness, and launch quality.
5. Identify the top risks and how you would mitigate and communicate them.