Cybersecurity · GenAI Product Rollout
Rolled Out SecurityScorecard's First GenAI Feature to 4,000 Enterprise Customers with Zero Churn
SecurityScorecard is a cybersecurity ratings platform used by enterprise security teams to monitor vendor risk. When it came time to launch their first generative AI feature, an agentic chat interface called ChatSSC, I designed and led a rollout process that treated the launch not as a feature release, but as a buyer-side migration. Over four months, we brought ChatSSC to ~4,000 customers with zero churn, no complaints escalated to leadership, and fewer than 10 customers opting out. A vendor risk manager at a major financial institution later told me that SecurityScorecard was the only vendor who notified her in advance and came prepared with updated policy and governance documentation before the features went live.
01
The Situation
There is a pattern happening across SaaS right now that should worry any product leader: enterprise customers are ripping out vendors for adding AI to their products. Not because the AI is bad, but because vendors are treating a fundamental capability change as a feature flag, flipping it on without considering what it means for the buyer.
Enterprise customers have real data agreements with their own vendors. Many of those agreements explicitly prohibit running data through AI. When a SaaS product suddenly makes AI the default, or the only way to use the tool, it puts their customers in a position where they cannot comply with their own policies. As one executive I spoke with put it, he was removing SaaS vendors not because he was anti-AI, but because they did not leave him a choice.
SecurityScorecard's customers are CISOs, security analysts, and vendor risk managers, people whose entire job is evaluating and managing risk. Launching a GenAI feature to this audience without thinking carefully about data privacy, governance, and customer communication would not just be a missed opportunity. It would break trust with exactly the people who evaluate trust for a living.
02
What I Did
Stopped the feature from shipping before it was ready.
There was momentum to move ChatSSC from private beta to default-on. The thinking was straightforward: the feature worked, so let's ship it. But there were two problems. First, the product had UX issues that would undermine trust: the chat window closed every time a user navigated to another page, which made it feel broken. For a customer's first experience with AI in a product they already trust, that sets the tone for how they will perceive every AI feature that comes after. I insisted we get resources to fix that before launch. Second, most people on the team had not considered that turning on a GenAI capability for a product that never had one is categorically different from launching a regular feature. The data privacy and legal implications change the entire rollout calculus. Once I explained why, there was alignment.
Designed the rollout as a two-phase, months-long customer migration.
Instead of a single launch, I split the customer base into two groups. The first group were customers who had already self-selected as AI-friendly: they had participated in ChatSSC usability testing or had proactively asked their customer success manager about getting early access. The second group was everyone else. We launched with the friendly group first, deliberately, because if we were going to learn anything about the process we would learn it with the people most inclined to be forgiving. By the time we rolled out to the broader base, we already knew what was coming.
Prepared the legal and governance infrastructure before the features landed.
Before any customer saw ChatSSC, we had an updated legal addendum ready, documentation on our models and data handling, clear information about data privacy, and a defined process for customers who needed to opt out. We coordinated directly with Legal and Customer Success to make sure everything was in place. We also sent multiple rounds of email communication per phase, not a single announcement but repeated touchpoints so customers would not feel blindsided because they missed one email. The entire rollout ran from August through November 2025, and that timeline was intentional. We were not slow. We were thorough.
03
The Outcome
- 0churn attributed to the GenAI rollout
- ~4,000enterprise customers migrated over four months
- <10customers opted out of AI features
Zero churn attributed to the GenAI rollout. Out of approximately 4,000 customers, fewer than 10 opted out of AI, and those were handled as straightforward exceptions, not escalations. No complaints reached leadership.
A vendor risk manager at a major financial institution put it this way: "SecurityScorecard was the only company that told me in advance about the features and came prepared with updates in policy and governance documents before the features landed."
In an industry where executives are actively removing vendors for getting this wrong, that distinction matters.
The rollout also established a repeatable process. The phased approach, the legal preparation, the multi-touch communication cadence: all of it became the template for how SecurityScorecard would bring subsequent AI features to market.