Agentic AI is becoming a force multiplier across customer contact operations.
Every year, growth organizations spend heavily to create demand, generate paid leads, and move consumers into the funnel. Yet across both inbound and outbound operations, a stubborn operational limit remains: not every high-intent consumer becomes a real conversation.
Across outbound and inbound use cases, here is what changed, in plain numbers.
The constraint is no longer just media efficiency, creative performance, or lead quality. Increasingly, the constraint is execution capacity at the point of contact.
On the outbound side, AI-powered call screeners are creating a new access bottleneck before a conversation can even begin. On the inbound side, human intake capacity limits how consistently teams can qualify, route, and follow up on every consumer interaction without adding cost and complexity.
Centerfield’s operating data shows that agentic AI is beginning to solve both sides of that problem. Across outbound and inbound use cases, AI is not simply reducing cost. It is expanding the number of commercially useful conversations that can happen, while preserving the quality controls that matter most downstream.
- 01
Outbound access improved.
AI-led outreach more than doubled connect rates vs. legacy dialing in controlled tests across ~188K leads (98% to 189% lift).
- 02
Inbound quality held.
AI handled high-intent inbound calls with transfer and downstream sale/close outcomes on par with human handling.
- 03
Unit economics improved.
Across 72,767 inbound conversations, cost per call was ~83% lower with comparable commercial outcomes.
Bottom line: AI is not only reducing cost; it’s expanding coverage — recovering conversations that would otherwise be missed, blocked, delayed, or too expensive to work with a human-only model.
Paid demand still breaks at the point of contact
The handoff between paid demand and live qualification remains one of the largest leaks in the system.
Lead generation remains one of the largest engines of B2B and high-value B2C growth. Businesses continue to invest heavily in paid search, social, display, affiliate, and marketplace channels to create demand and capture consumer intent. But even when media is working, organizations still face a practical question: can every lead be contacted, qualified, routed, and worked quickly enough to reveal its true value? In many cases, the answer is no.
Outbound teams face a deteriorating access environment as consumers rely more heavily on call screening technology. Inbound teams face a capacity and cost challenge: scaling human intake coverage linearly with call volume is expensive, operationally rigid, and difficult to adapt quickly.
The result is the same in both cases: demand exists, but execution capacity limits how much of that demand becomes a qualified conversation. Agentic AI addresses that bottleneck directly.
Outbound impact: solving the connect problem
AI-powered call screeners have quietly become gatekeepers between brands and consumers.
It is not simply a lack of demand. It is not only a lead quality problem. And it is not just an agent performance problem. It is an access problem. On the surface, this can look like a decline in list quality or a dip in agent productivity. In practice, it is a structural barrier that reduces live connects before any sales conversation can begin.
Centerfield tested whether AI-led calling could navigate this environment more effectively than traditional outbound methods. Across approximately 188,000 leads, the test showed a consistent improvement: agentic AI restored access that legacy dialing methods were losing.
Controlled outbound test results (Jan. 5, 2026 – Feb. 5, 2026):
Across every cohort, AI-led calling beat legacy dialing on connect rate. In several cohorts, connect rates more than doubled. In the strongest cohort, AI delivered a 189% lift. This was not a marginal optimization. It was a structural response to a market-wide constraint.
The point was not that AI made the phone conversation more persuasive. The point was that AI helped more conversations happen in the first place. As AI screeners become more common, the teams that win will not simply be the teams that dial faster.
Inbound impact: matching quality at lower cost
Inbound auto insurance calls are high-intent consumer interactions.
The operational job is not just to answer the phone. The agent must collect intake information, ask qualifying questions, determine routing, and support a warm handoff without degrading the consumer experience or downstream commercial value.
Centerfield analyzed 72,767 inbound auto insurance calls from May 22, 2026 to June 22, 2026, comparing AI-handled and human-handled calls on two quality-control metrics: transfer rate, to determine whether AI is routing calls too conservatively or too liberally, and sold rate, to determine whether AI-handled calls are producing comparable downstream commercial outcomes.
The findings were strong: AI and human agents performed on par for both transfer rate and sold rate. That parity matters — it indicates AI is handling intake, qualification, and routing with commercial effectiveness similar to human agents, without over- or under-screening callers.
At the same time, AI reduced cost per call by approximately 83%.
What the inbound data shows about consumer behavior
Consumers appear willing to provide information to AI agents when the value proposition is clear.
In some cases, consumers may not recognize they are speaking with AI. More importantly, the commercial outcomes do not suggest meaningful negative behavioral change. AI-handled calls are approximately 33% longer, or about 48 seconds longer, than human-handled calls. On its own, longer call duration could raise a concern. But paired with equivalent transfer and sold rates, the additional time appears manageable and commercially acceptable.
Agentic AI improves the operating model, but the consumer benefit is equally important: a faster, more connected path from intent to resolution.
For the potential buyer, the value is not AI itself. The value is less friction. AI can provide immediate coverage, collect information once, apply consistent qualification logic, and carry that context accurately through the handoff so nothing is repeated or lost. That makes the next step more relevant, whether it is an automated route, a warm transfer, or a human conversation.
This does not replace the human role; it makes human engagement more valuable. AI handles the structured parts of intake and routing, while people focus on the moments where empathy, judgment, persuasion, or complex support matter most.
Common consumer pain points, and how agentic AI addresses each one:
This expands the role of agentic AI beyond basic automation. In inbound auto insurance, AI is performing a more nuanced operational function: gathering information, qualifying intent, managing routing, and supporting warm handoffs.
Operational adoption: AI is already a material coverage layer
Over the last 90 days, AI has already become a meaningful part of Centerfield’s call operations.
Across B2B, residential, and insurance, AI now supports 21% of all consumer calls. Adoption is most mature in residential home services, where AI handles 67% of calls, but the insurance opportunity is also beginning to scale.
Insurance is still earlier in its AI adoption curve, with AI agents handling 14% of insurance calls overall. Within that category, auto insurance matters most because it represents approximately 80% of total insurance call volume. AI is already handling 16% of auto insurance calls, giving Centerfield a practical operating base in the largest insurance call category while maintaining parity with human agents on transfer and sold rates.
This matters because AI is no longer confined to a narrow experiment or single workflow. Centerfield is applying it across both outbound access and inbound qualification, using performance controls suited to each environment. In practice, AI is becoming an additional operational coverage layer: mature enough to carry substantial call volume in home services, early but scaling in insurance, and already proving that it can expand capacity without weakening the quality metrics that determine commercial value.
Why this matters for the CMO
Paid demand is only as valuable as the organization’s ability to work it.
CMOs are often asked to increase pipeline by increasing spend, improving targeting, or expanding reach. But if leads are not contacted quickly enough, worked consistently enough, or qualified economically enough, additional media dollars can simply create more leakage. Agentic AI changes that equation by creating a scalable operating layer between demand generation and human sales capacity.
Audit the "unreached" rate first.
Before increasing spend, marketing leaders should understand how many paid leads were contacted fewer than three to five times, delayed in follow-up, routed inefficiently, or never converted into a live conversation. That unreached or underworked group is the immediate AI opportunity.
Redefine the human role.
Humans should not be spending the highest-value time playing phone tag, repeating basic intake questions, or working every low-probability record manually. Agentic AI can cover initial outreach, intake, qualification, and routing so human teams can focus on the conversations most likely to require judgment, persuasion, or complex handling.
Start where the economics are clearest.
The safest AI test beds are often cold, aged, dormant, off-hours, or capacity-constrained cohorts that human teams are already unable to work consistently. Any recovered conversation or incremental pipeline from those pools improves the economics of demand that has already been paid for.
Strategic viewpoint and conclusion
Paid media keeps the funnel full, but execution breakdowns often happen at the initial touchpoint.
On outbound campaigns, AI screeners can prevent legitimate, consent-based outreach from ever becoming a live conversation. On inbound calls, human capacity and cost can limit how efficiently teams qualify and route high-intent consumers. Agentic AI gives Centerfield a way to standardize execution across both environments: restoring access in outbound channels, qualifying and routing consumers in inbound flows, supporting faster script adjustments, reducing training cycles, and expanding coverage without linearly expanding headcount.
The strongest finding across both use cases is not that AI replaces the revenue engine. It is that AI helps the revenue engine capture more of the demand it already created.
In outbound, AI solves an access problem by helping Centerfield reach more consumers in an environment increasingly shaped by AI call screeners. In inbound, AI solves a capacity and cost problem by handling intake and qualification with transfer and sold rates on par with human agents, while reducing cost per call by approximately 83%.
Together, these use cases show why agentic AI matters for modern growth operations. It ensures more paid leads get worked, more consumer intent becomes a real conversation, and more of the funnel is covered without forcing costs to scale at the same rate as volume. AI is not just a support tool. It is becoming an additional operational coverage layer.
For CMOs, the question is no longer whether demand generation works. The question is whether the operating model can qualify, re-engage, and recover the massive pool of leads that would otherwise be left behind.
Methodology
Centerfield Insights publishes one piece of proprietary research each month, drawn from data generated across Centerfield’s network of owned media properties, managed acquisition programs, and AI-driven sales infrastructure.
Our network reaches more than 250 million consumers annually and tracks 10.6 billion monthly intent signals across insurance, home security, telecom, and e-commerce. The research we publish is built on data from operating in these markets — not surveying them from the outside.
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Centerfield is a digital marketing organization specializing in AI visibility, affiliate and owned media, paid media performance, and AI-driven sales conversations for Fortune 100 companies across insurance, home services, telecom, and e-commerce.
We operate the full acquisition stack — from the first intent signal to the closed conversation — and we run owned media properties reaching more than 250 million consumers annually. The data behind Centerfield Insights comes from running real programs at real scale in the markets we write about.