Dialpad Support for contact centers brings routing, AI assistance, AI agents, and analytics together, so global teams can manage customer conversations on every channel from one place. Get a demo to see how it fits your operation.
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Jude Tungul
What Dialpad research shows about AI in enterprise contact centers
Dialpad studies how AI performs in real customer conversations through industry surveys, analysis of contact center interactions, and published AI research. Four findings stand out for enterprise contact centers.
AI that answers isn't the same as AI that resolves
In The Next Phase of Customer Service AI, Dialpad's 2026 survey of 150 Director and VP+ customer service leaders, 77% of organizations were already piloting or deploying AI. While 80% had information retrieval enabled, only 25% had autonomous resolution. About one in five AI-to-human handoffs (21%) happened because the AI understood the request but couldn't complete it, and only 33% of organizations had the customer's full cross-channel history available during the interaction. For contact centers, that points to connecting AI agents to the systems they need to act on and keeping context across voice and digital.
Measure outcomes, not just deflection
The same survey found that 54% of organizations can't yet distinguish a truly resolved interaction from a deflected one. Tools like AI CSAT and AI Scorecards help teams judge quality across conversations instead of counting how many calls AI kept away from agents.
"In healthcare, deflection isn't always a good thing. Less call volume doesn't necessarily mean better care. What matters is the outcome."
- Chase Williams, SVP of IT Transformation, Hopper
Much of customer demand goes unanswered
The State of Customer Signals, Dialpad research with Metrigy CX Research, found that 55.9% of inbound contact attempts in Dialpad's analysis were missed or unanswered. About half of the customer calls in its Skill Mining analysis also covered more than one topic. AI agents for after-hours and overflow, plus routing that adapts as a customer's needs change, can help contact centers capture more of that demand.
Research built on real conversations
Dialpad's AI Research Lab publishes research on problems contact centers face every day. A recent benchmark on recognizing customer topics in noisy, real-world contact center transcripts found that lightweight LLMs using natural-language topic descriptions outperformed regex and zero-shot embedding approaches. Other papers cover automated call recommendations for agent coaching and a framework for testing AI agents on voice as well as text, since some gaps appear only when an agent has to understand speech and take action.
Get a tailored walkthrough of how Dialpad's AI-native platform supports large-scale contact center operations, from AI agents and real-time coaching to workforce management and analytics. You can also compare Dialpad Support for contact centers plans.
Look for omnichannel routing, real-time AI assistance, AI agents, quality management, workforce management, analytics, and CRM integrations on one platform. Also evaluate security and compliance controls, multi-site administration, role-based access, and how context carries over when a customer moves from an AI agent to a human agent. The more of these share one set of customer data, the easier it is to see the full customer journey.
Yes. AI contact center solutions can support enterprise scale when AI agents, human agents, routing, and analytics run on the same platform and share customer context. Many enterprises start AI agents on bounded, repeatable requests such as order status, scheduling, or after-hours calls, then expand as results come in.
Clear rules for what AI handles and when people take over matter just as much. In Dialpad's 2026 customer service AI survey, the most common AI-to-human handoff trigger (29%) was a request falling outside the AI's defined decision rules.