Growth is a critical component of any business, and sustainable growth is impossible without customer service. More customers inevitably means higher support volume. Without the resources to efficiently handle the increased demand for support, companies will leave these customers with a poor experience and a strong desire to take their business elsewhere.
Traditionally, expanding customer service alongside business growth has been a difficult balance to strike. To meet growing demand, the only real option was to add more and more employees to your support team, which is expensive, time-consuming, and unsustainable. This has always been a catch 22; You can get speed, deliver a great customer experience, or keep costs low — pick two.
Artificial Intelligence breaks the linear growth model. Support leaders no longer need to grow their teams at a pace to meet demand. Instead, they can use AI tools to provide better, faster, and more economical customer service.
What is 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 customer experiences will continue to be limited by the size of your support team and the need to recruit, hire and train staff to handle any business growth.
Deferring AI-first customer service has significant costs, including limited business growth and scalability, poor customer experiences, and decreased competitiveness. Without AI, your business will fall behind.
From perceived cost center to core value driver
Several strategies can help your organization make a real impact in this new era of AI-driven customer service.
1. Reimagine customer service ROI.
The true value of AI-first customer service goes beyond just cost reduction; It enhances the quality of support, scalability, and overall business impact. Smart support teams think about ROI through two lenses: increased bandwidth and cost efficiency.
But how do you determine the ROI of AI-first customer service? When you’re shopping for an AI agent or calculating its value, you need to look beyond the sticker price and consider the price per accuracy. What drives the bottom line the most – and delivers the greatest return on investment – is having the best accuracy and performance rates. Here’s a simple example.
To get the full picture of ROI, you also need to consider the total cost of ownership that comes with adopting any new tool, such as the cost of implementation and integration with your existing technology stack.
2. Open value creation opportunities for support teams.
When we think about the new economics of AI, it’s easy to get caught up in how it will impact the current customer service model. But one of the most powerful aspects of AI is how it opens up and helps you reimagine what that model could 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 again, your AI-powered support team will have more time to focus on revenue-generating and value-creating businesses like proactive support, customer onboarding, and premium support – all of which are long-term customer satisfaction. And their loyalty.
3. Redefine success and how to measure it.
It’s not just how we deliver support that’s changing with AI-first customer support; You also need to reconsider how you measure success. Traditionally, support costs – and thus metrics – have been tied to agent salaries, resulting in an emphasis on quantity rather than quality and reducing average handle time.
With AI, the emphasis on quantity and speed are off the table, so teams can instead focus on solving more valuable and complex problems and keeping customers happy. This shift is positive, as it reduces transaction cost, improves first response time, and increases customer satisfaction. As a result, companies using AI-first customer service are moving from volume-based metrics like number of tickets to comprehensive KPIs like customer satisfaction, AI accuracy rates, and engagement rates.
4. Get started and get buy-in from executives.
You don’t have to go all out on day one, start small, and build from there. AI offers compounding benefits, so every small change helps. Start with the first step, such as using an AI agent to solve common questions for a small segment of loyal customers. Then, gather feedback, test your ideas, and refine your approach before rolling out AI to more customers.
This gradual adoption helps reassure executives that your organization can implement AI without disrupting the business or customers. While AI provides value beyond cost savings, sharing early ROI calculations and real-world impact can help capture leadership.
Learn more about shifting your support team’s perception from cost center to value driver in Intercom’s in-depth guide The new economy of customer service.