Conversational AI for customer service is becoming a practical way for enterprises to reduce friction, improve support, and give customers faster answers.
That message came through clearly during Capacity’s interview with CX Today publisher Rob Scott at CCW 2026. Speaking from the Capacity stand, Karaline Venezia, Chief Revenue Officer at Capacity, discussed the company’s growth, customer focus, and $100 million ARR milestone.
She was joined by Tim Harpe, Director of Global Success at DSW, who shared how the retailer uses Capacity to support real customer journeys.
Together, they showed why AI in customer experience is moving beyond hype. A strong virtual agent can support customer self-service, improve speed, and reduce friction. Yet the best strategies still protect the live agent handoff when customers need human help.
For CX leaders, the lesson is clear; Conversational AI for customer service works best when brands start with customer need, not technology for its own sake.
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Why Is Conversational AI For Customer Service Building Momentum?
Capacity arrived at CCW 2026 with major news. The company has reached $100 million in annual recurring revenue, marking a significant growth milestone.
That growth reflects a wider market shift. Enterprises want faster, smarter, and more scalable service models. They also want automation that improves experiences, instead of frustrating customers.
This is where conversational AI for customer service is gaining ground.
Capacity reflected that message. The company used a building-block concept to show how brands can construct better service journeys step by step.
A virtual agent does not need to solve everything on day one. It can start with simple, high-value tasks. Authentication is one example. Order status is another. These moments give customers quick answers and help agents focus on more complex work.
That kind of customer self-service creates value because it gives customers control. It also helps brands build confidence in AI in customer experience before expanding into more advanced use cases.
How Should Brands Think About AI Adoption Challenges?
When Scott asked about customer and retail adoption challenges, Venezia pushed back on the idea that AI adoption is simply about obstacles.
“Well, I wouldn’t say that there have been challenges.. But what I would say is that there are always things that you can possibly do differently, and there are things that you can strategize to.”
That is an important point for enterprise CX leaders. Conversational AI for customer service is not a one-time deployment. It is an ongoing process of learning, testing, and improving.
Venezia said the starting point should always be the customer.
“For us, it comes down to what does the customer at the end of the day truly need from us, and how can we provide that.”
Venezia also stressed that every brand must understand its own audience.
“Not every customer is the same, and not every brand is the same.”
That matters because a virtual agent should never feel generic. It should fit the brand, the customer journey, and the service model.
Why Does Live Agent Handoff Still Matter?
DSW’s experience brought that point to life. Harpe explained that the retailer began with practical AI use cases, including authentication and order status.
These are ideal starting points for conversational AI for customer service. They are clear, common, and easy for customers to understand.
Yet Harpe also made clear that automation has limits. A virtual agent can tell a customer where a package is. But if the answer does not meet the customer’s expectations, the brand needs another path.
“If by chance it’s not doing what the customer needs, how quickly can you get to a live agent? That, to me, is a critical component of the entire process.”
That is why live agent handoff remains essential. The best AI in customer experience does not trap customers inside automation. It gives them fast answers when possible, then connects them to a person when needed.
Strong live agent handoff also builds trust. Customers are more willing to use customer self-service when they know human help is still available.
How Can AI In Customer Experience Improve Costs And Service?
The Capacity interview also explored cost savings. Yet Venezia’s comments showed that the value of AI is not just financial.
She said brands need alignment on how they use the efficiencies created by automation.
Venezia argued that
“The real value of AI is not just in reducing costs. It is in deciding how those efficiencies can be reinvested into better customer experiences.”
She explained that the resources you can redeploy can help teams improve the virtual agent, find friction, and prioritize better customer journeys.
That makes AI in customer experience more strategic. It is not only about reducing contact volume. It is about learning where service breaks down and improving those journeys over time.
Venezia added that businesses can free up people who previously worked directly with customers, then move them into roles that improve the overall system.
“Then it becomes a success across the board… Because it’s not just saving money, it’s saving money, it’s improving the customer experience, and it’s improving the overall friction that happens within the business.”
That is the real opportunity behind conversational AI for customer service. When implemented well, it improves efficiency and experience at the same time.
What Sets Capacity’s Customer Partnership Model Apart?
One of the strongest parts of the interview was the focus on partnership.
Venezia said Capacity works closely with customers to make sure the technology keeps improving after launch.
“I think this is what sets Capacity apart from the rest of the world, in my opinion.”
She described a model where both Capacity and its customers review performance every day. That creates a shared focus on better outcomes.
“I have a team that looks at results every day. They have a team that looks at results every day,” Venezia said. “We work together every day on how do we make it better?”
That approach matters because customer self-service needs constant tuning. Customer expectations change. Products change. Business priorities change. The virtual agent must keep learning with the brand.
Venezia described the relationship as one built around shared goals.
“It is definitely a relationship that is built on two parties working towards the same exact goal,” she said.
For enterprise buyers, that is a key lesson. The best conversational AI for customer service platform is not just software. It is a long-term CX partner.
What Should CX Leaders Learn From Capacity And DSW?
Harpe’s advice to CX leaders was simple.
“Start something”
That does not mean automating everything at once. It means choosing one useful customer need, proving success, and building from there.
“Once you start, you can identify success, and once you realize success, then it’s easier to go to that next step.”
That advice fits Capacity’s building-block theme. Brands can start with authentication. Then they can add order status. Then they can expand into more complex customer self-service journeys.
The goal is not to remove people from the experience. The goal is to use people where they matter most. That means keeping live agent handoff simple, visible, and fast.
For CX leaders evaluating AI in customer experience, the roadmap is clear. Start with customer need. Build the right virtual agent. Measure results. Improve constantly. Keep humans close.
The Final Takeaway
This interview showed why enterprise AI is becoming more practical, measured, and customer-focused.
Venezia highlighted how brands can use AI to improve experiences, reduce friction, and reinvest resources into better journeys. Harpe showed how DSW is applying that thinking in real customer service environments.
Together, their comments point to a clear lesson. Brands should not automate everything first. They should automate carefully, learn quickly, and keep customers in control.
A trusted virtual agent can improve speed. Strong customer self-service can reduce effort. Reliable live agent handoff can protect empathy.
That is how conversational AI for customer service becomes something customers actually trust.
Are you a vendor redefining what’s possible in CX, or an enterprise transforming your customer experience strategy? Explore and apply for the CX Awards!
FAQs
What Is Conversational AI For Customer Service?
Conversational AI for customer service uses AI to answer customer questions through chat, voice, messaging, or digital channels.
What Is A Virtual Agent?
A virtual agent is an AI assistant that helps customers complete tasks without starting with a human agent.
What Is Customer Self-Service?
Customer self-service lets customers solve simple issues themselves, such as checking order status or confirming account details.
Why Is Live Agent Handoff Important?
Live agent handoff matters because some service moments need empathy, context, or human judgment.
How Should Enterprises Use AI In Customer Experience?
Enterprises should use AI in customer experience for focused use cases first, then expand based on results and customer feedback.
