March 3, 2026 • 5 min read
Dialpad Announces Agentic AI Product Advancements
CX Analyst & Thought Leader
March 3, 2026
In advance of Enterprise Connect, Dialpad announced several advancements in the AI-powered business communications and agentic platform. Most notably, the advancements include historical conversation data analytics, no-code voice and digital AI agent creation, and a new layer of AI governance.
The idea behind these features is to help enterprises move their AI projects firmly and securely out of pilot purgatory into the execution phase, rapidly and at scale. These product enhancements will make it easier for enterprises to not only identify realistic, high-impact AI use cases, but also to extensively test them before going live.
Enterprises aren’t struggling with AI ambition – they’re struggling with AI execution. 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.
Craig Walker
Skill Mining
Skill Mining reviews past conversation transcripts to identify scenarios, workflows, or interactions that AI agents could either automate completely or provide significant assistance with. When choosing conversations to mine, end users can select a specific date range, call purpose category, and call source. The skill mining tool then identifies the exact percentages of calls that could be automated, alongside a deeper breakdown of the specific tasks/interactions that could be automated with agentic AI (for example: re-routing delivery, unlocking accounts, resolving payment failures, etc.)
Once these skills are identified, end users can review the specific steps/path the AI agent would take when automating the task. For example, if generating return slips, the AI agent would verify customer details and addresses, ensure eligibility, identify the items for return, generate and send the return slip, give customers the return instructions, then log the interaction.
Users can edit/refine these steps–and set guardrails–in Dialpad Studio, a no-code automation designer interface for voice and digital AI agents.
Proving Ground
Dialpad’s Proving Ground is a testing suite that lets users pressure-test AI agents created via Skill Mining before deployment. Proving Ground follows a two-step process: scenario generation followed by test execution. Each skill goes through 10-15 scenarios per skill, and the tests include simulated voice calls and chat messages.
Each test shows end users an aggregate output (task completion rate) and a summary of the overall test result. Providing Ground also provides per-scenario pass/fail and complexity rates, deeper scenario result breakdowns, and details about the specific skills used. Proving Ground also lets end users review cumulative test results, review and tracing AI agent improvement across multiple iterations. Proving Ground is especially ideal for testing edge cases that are much more likely to be escalated to a live agent.
Guardian
Dialpad’s Guardian is a real-time governance supervisor using three “Analyzers” that track and terminate conversations that pose risks to businesses and customer data. Guardian ensures AI agents stay task-relevant and that complex support issues are escalated to a human agent.
Guardian uses Google Cloud’s Model Armor Analyzer to assign specialized classifiers for harmful content, prompt injection, jailbreak detection, sensitive data protection, and malicious URL detection. Guardian also uses a native Conversation Alignment Analyzer, which maps agent language to the specific messaging criteria to ensure that intent remains in alignment with AI Agent scope. The User Frustration Analyzer uses a general-purpose sentiment model to identify negative sentiment and determine if the frustration is directed at the AI agent.
Guardian will have the biggest impact on highly regulated industries like healthcare, banking, and legal.
Healthcare organizations don’t have the luxury of trial and error when it comes to patient Communications. 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.
Chris Martinez
What This Means For Enterprises
These new advancements build upon Dialpad’s existing AI-powered coaching capabilities, which include live transcription, interaction recaps, and sentiment analysis. As of this writing, 97% of Dialpad contact center customers are currently using AI, resulting in the creation of over 470 million AI CSAT scores, over 10 billion AI-enabled conversations, and over 750 million AI recaps.
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. 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.
Hayley Sutherland
Customer Experience is moving away from reactive, human-dependent support models toward proactive, AI-first support. Vendors aren’t competing on call routing or uptime anymore. Now, they're competing on how deeply and safely their AI can be embedded into enterprise workflows.
Dialpad's announcements target the exact friction point slowing AI adoption at scale: the gap between a successful proof of concept and a production-ready deployment.
Skill Mining aims to end the pilot purgatory problem by grounding AI use case identification in real conversation data rather than assumptions. Proving Ground eliminates the pre-launch by simulating and testing the edge cases most likely to break an AI agent in production.
Guardian, meanwhile, speaks directly to one of the most pressing concerns in enterprise SaaS today: AI governance. As agentic AI takes on more autonomous, customer-facing roles, risk expands dramatically, real-time guardrails become a requirement. Guardian's three-layer approach positions Dialpad as one of the first platforms to treat AI governance as a core product feature rather than an afterthought.