Artificial Intelligence

Redesigning the post-sale operating model for the AI era requires leaders to question assumptions that have shaped Customer Success, Support, Professional Services, and other customer-facing teams for years. AI changes what can be automated, personalized, monitored, analyzed, and delivered to customers. I keep a few sticky notes around the edge of my monitor. They’re simple reminders that help me be a better listener, leader, and advisor.

AI transformation in post-sale organizations is starting to raise a much bigger question than how teams can use AI to work faster. Leaders are being asked to rethink how their organizations create and deliver customer value now that AI has changed what is possible.

Customer Success in an AI-native company looks different from the traditional post-sale models most organizations have built. Recently, I joined a thoughtful discussion at Cursor’s San Francisco office about what Customer Success looks like when AI is central to the company, product, and customer experience. The panel featured Priya Bhatia, Emily Liu, Seema Amble, and Ziv Peled. Their perspectives reinforced something I have been hearing from post-sale leaders across the industry.

The AI-powered customer experience is moving from a future concept into the platforms customers and post-sale teams use every day. Salesforce’s agreement to acquire Fin for approximately $3.6 billion makes the growing importance of the AI-powered customer experience difficult for customer executives to ignore. That is a significant amount of money behind a relatively simple idea: The way customers get help, find answers, and move forward is changing quickly.

An AI Agent Registry gives post-sale leaders a centralized view of the agents, assistants, automations, and AI-enabled workflows operating across their organization. Most companies deploying AI in Customer Success do not have an AI Agent Registry today, which means they cannot confidently explain what is running, who owns it, what it costs, or whether it is creating value.

AgentOps for Customer Success is quickly becoming a priority as post-sale organizations move beyond experimenting with AI and begin deploying agents across everyday operations. A year ago, many leaders were still asking whether their teams should use AI. Today, they face a more complicated question: How do we manage, govern, and budget for all the AI agents our teams have created?

An effective AI framework for Customer Success is becoming essential as post-sale leaders move beyond experimenting with AI and begin embedding it into everyday work. Over the past year, I’ve spoken with hundreds of Customer Success leaders, delivered AI workshops, and worked with teams that are all trying to answer the same question.

When leaders ask, “What impact is AI having?” The honest answer is often: “I know it’s helping, but I can’t fully quantify it yet.”

Customer Success trends are evolving faster than ever, and the conversations happening across the industry all point in the same direction. While every conference introduces new ideas, the themes that continue to surface reveal something much more important: how the role of Customer Success is fundamentally changing.