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.
Salesforce announced in June 2026 that it had signed a definitive agreement to acquire Fin, formerly Intercom. Fin’s AI customer agent is designed to resolve customer questions across channels including live chat, email, messaging, phone, and Slack.
The transaction is important, but the more useful question for Customer Success and post-sale leaders is not whether the price was justified. The useful question is what this shift could mean for the customer experiences we are responsible for creating.
What an AI-Powered Customer Experience Could Look Like
Think about a customer who is trying to complete an implementation step, understand a product feature, prepare for a renewal conversation, or resolve a problem late at night. Today, that experience may require the customer to:
- Search a knowledge base
- Submit a support ticket
- Email a Customer Success manager
- Explain the problem more than once
- Wait for the right person to become available
- Search online for an answer from another customer
Each step creates friction. AI creates more options for how that moment could work. The customer might receive an answer based on their account configuration, product usage, goals, subscription level, and support history. The system might guide them through the next step rather than simply sending them a help article. A CSM might enter the conversation with the relevant context already assembled. An emerging issue might be identified early enough for the team to offer assistance before the customer has to ask.
Those are not simply faster versions of the same experience. They are different experiences, and they can produce different business results.
Customers Will Expect Answers That Reflect Their Context
Most traditional self-service experiences require the customer to find the right answer.
The customer searches, compares several articles, decides which instructions apply to their situation, and fills in the gaps when the documentation does not match their configuration. An AI-powered experience has the potential to reverse that burden.
Instead of asking the customer to interpret a library of information, the system can assemble a response based on the customer’s question and context.
That shift is already changing how customers learn. In How Customers Use AI to Learn About Your Product, I explored why customers will not always begin with your website, support portal, or knowledge base. They may ask ChatGPT, Copilot, Gemini, Claude, or another AI platform for help first.
This creates two responsibilities for post-sale leaders. First, we need to think about how customers receive accurate answers inside the experiences we control. Second, we need to think about whether external AI platforms can find and understand reliable information about our products. Both affect the customer’s ability to achieve value.
AI Can Prepare Employees, Not Just Respond to Customers
The AI-powered customer experience is not limited to autonomous customer service. Some of the most valuable uses of AI may happen behind the scenes. Before a CSM joins a customer call, an agent could assemble:
- Current product usage
- Open support issues
- Recent customer communications
- Progress against the customer’s goals
- Relevant stakeholder changes
- Renewal timing
- Recommended discussion topics
Before an implementation manager contacts a customer, an agent could identify incomplete milestones, common obstacles, and the next actions most likely to keep the project moving, and before a support specialist responds, AI could summarize the customer’s history and surface similar resolved cases.
The employee still brings judgment, empathy, experience, and accountability. AI reduces the time required to gather context and makes it easier for the employee to enter the conversation prepared. This is an important distinction.
The opportunity is not only to replace a human interaction with an automated one. It is to improve the timing and quality of the human interaction when a person is needed. That idea is central to the AI POWER framework for customer success. AI can create value across personal productivity, operational workflows, customer experiences, and revenue outcomes. Leaders should resist reducing the entire opportunity to one support chatbot.
The Customer Journey Should Determine Where AI Is Used
When a major technology company makes an acquisition like this, leaders may feel pressure to respond with a large AI initiative. That is rarely the best starting point. Begin with the customer journey. Identify the moments where customers experience avoidable delay, confusion, repetition, or effort. For example:
- Customers repeatedly get stuck during the same onboarding step.
- CSMs spend hours gathering information before business reviews.
- Support teams receive predictable questions that require similar research.
- Customers do not realize they are underusing a valuable feature.
- Renewal conversations begin without a shared view of value achieved.
- Escalations move slowly because context is spread across several systems.
These moments are more useful than a generic mandate to “use more AI.” Once the moment is clear, leaders can ask:
- What does the customer need to accomplish?
- What information is required?
- Which parts could AI complete?
- Where does a person add essential judgment or reassurance?
- What result should improve?
- How will we know whether the new experience is better?
This approach supports the shift toward adaptive customer success. The goal is not simply to automate the existing operating model. It is to use better signals and faster decisions to respond to what each customer needs.
Customer Leaders Must Help Shape the Design
AI strategy cannot belong only to Technology, Product, or IT. Customer leaders understand where customers struggle. We see which questions appear repeatedly, where handoffs break down, which signals predict risk, and what customers are ultimately trying to achieve. That perspective is essential when a company decides where AI should be applied. Without customer leadership, an organization may optimize for the easiest task to automate rather than the most important experience to improve. It may reduce response time while creating less trust, increase self-service while making it harder for customers to reach a person, and automate a workflow that should have been redesigned first.
Customer leaders can help the organization ask a better question: Does this use of AI make it easier for the customer to achieve the outcome they purchased our product to achieve?
That question creates a stronger standard than efficiency alone.
Measure the Result, Not Just the Automation
AI metrics often focus on activity:
- Number of conversations handled
- Number of summaries generated
- Number of tasks completed
- Number of hours estimated to be saved
- Percentage of cases deflected
Those measures can be useful, but they are incomplete. A customer experience should be evaluated through customer and business outcomes. Depending on the use case, leaders might measure:
- Time to first value
- Onboarding completion
- Customer effort
- Resolution quality
- Product adoption
- Escalation frequency
- Renewal readiness
- Retention
- Expansion
- Customer confidence
The challenge is that the business impact of AI in Customer Success may take time to become visible. Early improvements often appear through speed, consistency, and reduced cognitive load before they show up in retention or expansion metrics.
That should not prevent measurement. It should encourage leaders to define a clear chain between the AI-enabled action, the customer behaviour it should change, and the business result that should eventually improve.
Redesign One Customer Moment
This is one of the central ideas in my upcoming book, The Chief Customer Officer Playbook for the AI Era.
The book asks customer leaders to look beyond individual tools and consider a larger question: If you were designing how your organization creates and delivers customer value today, knowing what AI makes possible, what would you build?
Salesforce’s planned acquisition of Fin makes that question more immediate. AI is becoming part of the platforms, workflows, and customer interactions post-sale organizations rely on every day. Customer leaders have an important role to play in shaping what comes next. You do not have to redesign the entire customer journey at once.
Choose one customer moment that matters. Ask how it could become more responsive, more personal, or easier for the customer using the capabilities AI enables. Then define the result that should improve. That is where an AI-powered customer experience stops being an abstract vision and becomes practical operating work.
