As enterprises increase investment in artificial intelligence for customer communications and operations, many organizations are struggling to move beyond pilot projects to large scale deployments. Dialpad has introduced new enhancements to its Agentic AI Platform aimed at helping businesses accelerate adoption while validating return on investment before production rollout.
Dialpad, an AI powered business communications and collaboration provider, unveiled the new capabilities at Enterprise Connect 2026. The updates are designed to help organizations identify high impact AI use cases, build intelligent AI agents without coding, and deploy governed AI solutions with built in performance measurement and compliance controls.
The announcement comes as enterprise adoption of agentic AI technologies continues to rise. According to industry estimates cited by Dialpad, 79 percent of companies implemented AI agent technology in 2025, with spending expected to reach 155 billion dollars by 2030. Despite this momentum, roughly half of enterprise AI projects remain stuck in the pilot stage, delaying measurable results and slowing operational transformation.
“Enterprises aren’t struggling with AI ambition; they’re struggling with AI execution,” said Craig Walker, CEO and Co-founder of Dialpad. “Billions have been spent on agentic AI, but too many projects stall before delivering real, measurable results. Our latest platform advancements eliminate the guesswork, helping organizations identify the right use cases, validate ROI before launch, and deploy AI agents that are safe, governed, and ready for production from day one.”
The expanded Agentic AI Platform introduces several capabilities intended to bridge the gap between experimentation and real world deployment. One feature analyzes historical conversation data to identify friction points in customer interactions and determine which automation opportunities will deliver the highest impact. Dialpad refers to this process as Skill Mining, allowing organizations to prioritize the most valuable AI use cases.
Another feature, called Proving Ground, enables businesses to test and evaluate AI agent performance before deployment. By simulating interactions and measuring outcomes such as resolution rates and efficiency improvements, organizations can validate expected ROI prior to launching AI agents in production environments.
The platform also includes enhanced analytics designed to connect AI conversation data with contact center performance metrics. This closed loop analysis allows enterprises to track indicators such as resolution rates, average handling time, and customer satisfaction across both AI driven and human assisted interactions.
Dialpad has integrated these capabilities with its existing AI features used across voice and digital channels. The company reports that 97 percent of its contact center customers currently use AI powered features such as real time transcription, sentiment analysis, coaching prompts, and automated call summaries. To date, the platform has generated more than 775 million AI generated conversation recaps and over 450 million customer satisfaction scores.
Another major component of the release is Agent Studio, a no code environment that enables enterprises to build and deploy custom AI agents aligned with internal workflows and security policies. The system integrates with enterprise data sources and automation tools, enabling teams to design conversational agents tailored to customer service, employee support, and operational use cases.
Dialpad also introduced Guardian, a real time governance layer that monitors AI interactions and helps ensure compliance with privacy and data protection requirements. The feature is intended to reduce operational risk while maintaining transparency and oversight across AI deployments.
“Healthcare organizations don’t have the luxury of trial and error when it comes to patient communications,” said Chris Martinez, Global Chief Information Officer at Healthcare Outcomes Performance Company (HOPCo). “Dialpad’s agentic AI capabilities helped us move from testing to enterprise-wide deployment with confidence by identifying where AI would have the greatest impact. As a result, we reduced resolution times, improved patient satisfaction, and maintained the strict governance our industry requires.”
“The real value for customers right now is moving beyond retrospective analytics to understanding the specific impact and resolution rates ahead of time. This empowers the critical decision-making that delivers real business value,” said Hayley Sutherland, Research Manager, Conversational AI at IDC. “By showing them the quantifiable ROI before deployment, you help them reduce failed AI pilots and maximize ideal business outcomes that are linked strongly to strategic — yet data-based — decisions.”
As enterprises look to operationalize artificial intelligence across customer experience and communication workflows, Dialpad’s expanded Agentic AI Platform reflects a growing industry focus on governance, measurable outcomes, and scalable deployment rather than experimental pilots alone.
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