Growth is a crucial component of any business, and sustainable growth is impossible without customer service. More customers inevitably means higher support volume. And without the resources to efficiently handle the rising demand for support, businesses will leave those customers with a poor experience—and a strong desire to take their business elsewhere.
Traditionally, scaling customer service alongside business growth has been a tricky balance to strike. To meet rising demand, the only real option was to add more and more head count to your support team, which was costly, time-consuming, and unsustainable. This has always been a catch-22; you can have speed, provide a great customer experience, or keep costs low—choose two.
AI breaks the linear growth model. Support leaders no longer have to grow their teams at a pace to meet demand. Instead, they can use AI tools to deliver the trifecta of better, faster, and more economical customer service.
What’s the opportunity cost of not adopting AI?
Without AI-first customer service, you won’t get the benefits of breaking the traditional linear growth model. The quality of your customers’ experiences will remain constrained by the size of your support team and the need to recruit, hire, onboard, and train staff to handle any business growth.
Postponing AI-first customer service has significant costs, including limited business growth and scalability, poor customer experiences, and reduced competitiveness. Without AI, your business will get left behind.
From perceived cost center to core value driver
Several strategies can help your organization drive true impact in this new era of AI-first customer service.
1. Reimagine the ROI of customer service.
The true value of AI-first customer service goes beyond cost reduction; it enhances support quality, scalability, and overall business impact. Savvy support teams think about the ROI through two lenses: increased bandwidth and cost efficiency.
But how can you quantify the ROI of AI-first customer service? When you’re shopping for—or calculating the value of—an AI agent, you need to look beyond the sticker price and consider the price per resolution. What moves the bottom line the most—and delivers the greatest ROI—is getting the best resolution and performance rates. Here’s a simple example.
To get the full ROI picture, you also need to factor in the total cost of ownership that comes with adopting any new tool, such as cost of implementation and integration with your existing tech stack.
2. Unlock value-creating opportunities for support teams.
When we think about the new economics of AI, it’s easy to get caught up in how it affects the existing customer service model. But one of the most powerful aspects of AI is how it breaks open and helps you reimagine what that model can look like in the first place, creating new opportunities for your team and your business.
Instead of being stuck answering the same questions over and over, your AI-powered support team will have more time to focus on revenue-generating, value-creating work such as proactive support, customer onboarding, and premium support—all of which drive long-term customer satisfaction and loyalty.
3. Redefine success and how you measure it.
It’s not just how you deliver support that changes with AI-first customer support; you also need to reconsider how you measure success. Traditionally, support costs—and therefore metrics—were tied to agents’ salaries, driving a focus on quantity over quality and minimizing the average handle time.
With AI, focusing on quantity and speed becomes table stakes, so teams can focus instead on solving more valuable, complex issues and keeping customers happy. This shift is positive, reducing cost per transaction, improving first response time, and increasing customer satisfaction. As a result, businesses using AI-first customer service are moving from volume-based metrics like ticket counts to holistic key performance indicators like customer satisfaction, AI resolution rates, and involvement rates.
4. Get started and win executive buy-in.
You don’t have to go all in on day one—start small, and then build from there. AI delivers compounding benefits, so every small change helps. Begin with step one, such as by implementing an AI agent to resolve FAQs for a small segment of loyal customers. Next, gather feedback, test your ideas, and refine your approach before rolling AI out to more customers.
This gradual adoption helps reassure executives that your organization can implement AI without disrupting the business or customers. While AI offers value beyond cost savings, sharing early ROI calculations and real-world impact can help get leadership on board.
Learn more about flipping the perception of the support team from cost center to value driver in Intercom’s in-depth guide The New Economics of Customer Service.
