Strategy question
You are a product leader at a large financial Services organization. You have been asked to come up with a governance strategy for the enterprise. What will be your key considerations as you work on developing a point of view?
- Salesforce
- Strategy
- Hard
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
Start a mock interview on this question · Mock interview from a job description
What this question tests
Tests enterprise strategic thinking on governance, a broad and abstract ask: can you narrow it to concrete, prioritized considerations rather than a vague compliance checklist.
How to approach it
- Clarify the scope: governance likely spans data, AI/model, and access/security governance, since financial services carries heavy regulatory obligations across all three.
- Identify the primary constraint: regulatory compliance, privacy, anti-money-laundering, and model risk management, is non-negotiable and should anchor the framework.
- Prioritize a risk-tiered approach: not all data carries equal risk, so controls should scale to risk level rather than a one-size-fits-all burden.
- Address AI-specific governance: AI-driven decisions like credit scoring need explainability, bias auditing, and human-review escalation given regulatory scrutiny.
- Address organizational ownership: define clear accountability, a governance council or steward roles, so policies are enforced consistently, not just on paper.
- Define success as audit-readiness and reduced time-to-approve new data or AI use cases, balancing rigor against speed.
What a strong answer includes
- Explicitly names regulatory concerns unique to financial services, AML and model risk management, rather than a generic governance answer.
- Proposes a risk-tiered model rather than uniform heavy controls, a real best practice balancing compliance and agility.
- Addresses AI-specific governance, explainability and bias auditing, given the real regulatory scrutiny on automated decisions.
- Balances compliance rigor against organizational speed explicitly, showing governance must be workable, not just add controls.
Common mistakes
- Giving a generic corporate governance answer with no connection to the specific regulatory realities of financial services.
- Proposing uniform, maximal controls everywhere without a risk-based prioritization, which would be unrealistic and burdensome in practice.
- No mention of organizational ownership or accountability, leaving the governance framework as policy with no enforcement mechanism.
Likely follow-up questions
- How would you handle a business unit that wants an exception to a governance policy for speed?
- How would you audit whether an AI-driven decision system is actually compliant with your governance framework?
- How would you roll this governance framework out across a large, already-operating enterprise without stalling existing projects?
More strategy questions
- What should Microsoft Teams' product strategy be for the next 3 years?Microsoft · Strategy · Hard
- How do you know if the user story you created is ready for execution?Salesforce · Strategy · Easy
- You have come up with a new product. How would you go about working with your stakeholders on taking it to the market?Salesforce · Strategy · Medium
- You are the PM in charge of product launch of Enterprise SAAS Solution. How would you go about it?Salesforce · Strategy · Hard
- You are a product manager at a large retailer. You are working on the pricing of a new product. What are the factors you would take into account to price this product?Salesforce · Strategy · Hard
- You are working on developing a new product. Doing it right would take 18 months. By then, competitive gaps would be insurmountable. How do you come up with a delivery strategy that would keep your company in the game?Salesforce · Strategy · Hard
More questions from Salesforce
Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop