How Contact Center Leaders Can Use AI To Drive Business Growth

Forbes

4 days ago

Vasudeva Akula, VOZIQ AI cofounder and head of data science. Helps recurring revenue businesses improve customer retention using ML.
Customer lifetime value (CLV) is a North Star metric for many subscription businesses, and it supports several use cases, as illustrated by researchers.
However, contact center leaders are constantly challenged to lower their costs. In this context, AI can help. What many leaders don't know is that AI can do more than lower costs; it can drive CLV growth.
This opportunity can be unlocked by scoring every customer for risk and revenue potential using AI, which can identify who is likely to cancel and common drivers of cancellations. Once this scoring has been done, contact centers can uncover hidden opportunities that directly impact revenue.
While cost optimization is a tempting starting point, in my experience, focusing on revenue optimization delivers significantly higher value for contact center leaders—often with similar effort.
Starting AI Adoption In The Contact Center
In my career, I've found that AI initiatives take around two to four years to reach production. This delay usually stems from a lack of clarity about the use case at hand and the right channel to kickstart AI. I recommend that subscription leaders begin AI projects in their contact centers. Here's why.
A contact center is a goldmine of unstructured data—conversations, chat logs, sentiment and agent notes. These hold the crucial details about customer desires, emotions and gaps in customer experience.
By integrating AI here, you can turn this data into real-time actionable intelligence—not just to proactively retain at-risk customers, but also to deliver value-enhanced services like validating purchase decisions, educating customers on product usage, anticipating needs and helping them achieve their goals.
Perhaps most importantly, the contact center offers a clear path to proving ROI early, through measurable improvements in first-call resolution, agent performance and CSAT. These early wins can build internal confidence and lay the groundwork for scaling AI across other customer touchpoints.
AI-Enabled Chatbots
A common starting point for AI adoption in the contact center is automating low-value customer interactions like billing inquiries, password resets and basic troubleshooting using AI chatbots. These are typically repetitive tasks that don't require human empathy or complex decision-making.
By automating them, contact centers free up human agents to focus on high-value, high-impact conversations that drive customer retention and revenue growth.
Value-Based Call Routing
Customer scoring enables high-value customers to be prioritized through value-based IVR routing. Customers with higher lifetime value or revenue potential can be quickly connected to the most skilled or specialized agents.
By routing calls based on customer value, contact centers can deliver faster, more personalized service to their most important customers, increasing the chances of retention and long-term growth.
Customer-Level Scoring
AI-powered scoring offers real-time insight into which customers are happy, at risk of churning, ready for an upgrade or likely to refer others. These insights open up new opportunities for revenue growth through the contact center.
When fed directly into both chatbots and human agent systems, this information enables personalized interactions tailored to each customer's risk or potential. Chatbots can respond more intelligently, while agents can address churn signals, offer custom solutions and surface upsell or cross-sell opportunities.
Proactive Retention And Renewals
Customer-level scoring segments at-risk customers based on cancellation risks, usage patterns, purchase history and perceived value. You can then route high-value, at-risk customers to dedicated retention specialists who offer personalized renewal strategies before it's too late.
With this value-focused transformation, the contact center shifts from being a cost center to standing alongside the sales team as a true profit center.
Vetting AI-Readiness
While the ultimate goal is transforming the contact center into a growth engine, a great starting point is focusing on a single AI use case powered by customer-level scoring and turning that into a success story.
This approach supports cross-functional alignment across sales, marketing, finance and tech teams. It also ensures success by focusing not just on technology, but on organizational alignment throughout the process.
Once initial results are delivered, your team can improve and scale your AI efforts—adding new use cases or involving additional teams. This simplifies the full process from data gathering to modeling to activation and directly improves your growth KPIs.
Once you've completed a first pass, repeating the process becomes easier and gains wider buy-in. Ask these three questions to get started:
Final Thoughts
When contact centers shift their focus from cost optimization to revenue generation, they can unlock untapped growth, strengthen customer relationships and elevate their role within the organization. With AI as a co-pilot and customer-level intelligence guiding every interaction, contact centers can move beyond support and truly drive sustainable business growth.
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