AI Calls Connect 32% of the Time. Dialers: 13%
AI call screening can block consenting customers. In a test of 188,000 consumers, agentic AI connected far more often than traditional dialling.
Your company probably invests heavily in customer acquisition. But once a consumer signals interest, are you ready to engage them at precisely the right moment?
Generating demand is essential to growth. But generating more demand isn’t always the answer. In many cases, there’s another opportunity hiding further down the funnel: improving how effectively businesses engage and convert the demand they’ve already created.
Companies can lose opportunities for many reasons. They may respond too slowly, struggle to answer customers’ questions directly, or simply fail to connect with an interested consumer. When conversion rates stall, it can be tempting to focus primarily on generating more demand or improving its quality. But execution deserves just as much scrutiny.
At Centerfield, we’ve found that agentic AI can help address some of these execution gaps by reducing technology and capacity constraints that can prevent businesses from turning customer intent into successful outcomes.
Customer intent has limited value if you can’t connect
Generating high-intent customer opportunities matters, but businesses also need to act on that intent.
That is becoming more challenging as AI-powered call screening, designed to protect consumers from spam callers, can block calls even when customers have opted in or requested a callback.
My team at Centerfield, a technology-powered customer acquisition company serving Fortune 100 brands, tested whether a different approach to calling could improve connect rates. In our controlled test of roughly 188,000 consumers who had consented to communications, calls initiated with agentic AI produced a 32% connect rate, compared with 13% for traditional dialling. AI-led calling achieved a higher connect rate across all seven cohorts we tested, with lifts ranging from 98% to 189%.
In our test, AI-led calling reached more consumers who had requested contact. When conversions decline, leaders should examine whether interested customers are being reached, as well as lead quality and quantity.
For some organisations, agentic AI could provide another tool to improve conversion rates and get more value from existing customer demand.
Turn customer intent into timely action
Businesses also need enough capacity to engage interested consumers when they signal intent or ask a question. Customers want quick answers, but interest can spike or arrive after hours, leaving call centres without enough capacity. Agentic AI may help teams respond during those gaps.
How do we know AI can handle inbound calls accurately? My team analysed 72,767 high-intent inbound auto insurance calls handled by AI and human agents. The sold-call rate was the same for both groups, at 22.3%, while AI agents had a slightly lower connect-to-transfer rate: 32.8% compared with 36.3% for human agents.
Taken together, these two data points indicate that the AI agents weren’t screening out qualified consumers in a way that cost sales, nor were they over-transferring lower-quality calls.
AI calls averaged 3.2 minutes, 48 seconds longer than human-handled calls. Duration alone doesn’t show satisfaction, but the longer calls coincided with the same sold-call rate in this analysis. The longer duration suggests AI may take more time to gather caller information and move customers to the next appropriate step without negatively affecting the ultimate sales outcome.
Finally, our data revealed that the cost per call was about 83% lower for AI-led calls.
These results don’t mean AI should handle every interaction. They do suggest that, in the right use cases, AI can give businesses another way to expand capacity and service hours, particularly when customer demand outpaces what a human team can respond to.
Orchestrate AI and humans around the customer
The goal of using AI in customer acquisition shouldn’t be to replace humans. It should be to determine where AI can improve the customer journey and where people add the most value.
Some parts of that journey may be well-suited for an AI agent to engage a consumer, understand intent, gather information, and move them forward. Other moments may benefit from a person stepping in.
Instead of applying a blanket rule or relying on assumptions about AI’s capabilities, businesses should use data to make these decisions. Our learnings from more than a quarter million real calls suggest AI can manage tasks such as initial engagement, qualification, and routing in certain customer acquisition environments. This can create more capacity for people to focus on complex conversations that require greater judgment or empathy.
A well-designed handoff should also carry the customer’s context forward, so they don’t have to repeat themselves when a human takes over.
From the customer’s perspective, the goal should be one seamless journey, regardless of how many people, systems, or AI agents support it behind the scenes.
Diagnose the bottleneck before adding AI or more demand
Adding AI to a broken customer acquisition process won’t solve underlying problems. Neither will simply pouring more demand into a process that isn’t converting efficiently. Businesses should understand where the greatest opportunity exists before deciding where to invest next.
Are you reaching enough prospective customers? Are interested customers waiting too long for a response after requesting a callback? Are sales teams overwhelmed during periods of high demand? Are legitimate calls being blocked by carriers or devices? Are employees spending too much time on repetitive qualification work that could be automated?
Once you identify the bottleneck, you can run focused tests to determine whether AI, additional demand generation, more human capacity or some combination of the three can improve the outcome.
The next phase of AI in customer acquisition isn’t necessarily about choosing between generating more demand and converting existing demand. It’s about understanding where technology can create the most leverage across the entire customer journey.
For many businesses, there may be a significant untapped opportunity in simply doing a better job with the customer intent they already have.
My advice to leaders is simple: Don’t start with AI. It’s not a strategy. Start with the business outcome you’re trying to improve, identify what’s standing in the way, and determine whether AI is the right tool to help solve it.
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