March 03, 2026
Dialpad Launches New Tools to Get Enterprise AI Out of the Pilot Stage
Dialpad has announced a major update to its agentic AI platform, introducing a set of tools aimed at one of the most persistent problems in enterprise technology: AI projects that never make it past the testing phase.
The new capabilities are set to debut at Enterprise Connect 2026 next week, spanning use case discovery, pre-deployment ROI validation, no-code agent building, and real-time governance. Together, they represent Dialpad’s attempt to give enterprises a clear path from initial AI experimentation to full production deployment.
Why Half of AI Projects Go Nowhere
Dialpad cites figures showing that 79% of companies adopted AI agent technology in 2025, yet roughly half of those projects remain stuck at the pilot stage. Total enterprise spending on AI agents is projected to hit $155 billion by 2030, a number that makes stalled deployments an increasingly costly problem.
Analysts at Gartner have predicted that agentic AI will autonomously resolve 80% of routine customer service issues without human intervention by 2029, cutting operational costs by 30%. Capturing that opportunity, however, requires more than deploying a proof of concept; it requires knowing which use cases to prioritise and being able to demonstrate results before going live.
Dialpad’s new Skill Mining feature addresses the first problem by analysing historical conversation data to identify specific friction points and surface the AI use cases most likely to deliver fast impact. A companion tool called Proving Ground then allows teams to test agent performance and validate projected ROI before any deployment goes live.
The intent is to reduce the number of AI projects that fail not because the technology does not work, but because organisations did not have enough information to make good decisions upfront.
Agents, Humans, and Guardrails
For building agents, Dialpad is releasing Agent Studio, a no-code environment for creating AI agents across voice and digital channels. It includes connectors and custom actions designed to fit into existing enterprise workflows, security policies, and compliance requirements without needing engineering resources.
Research has consistently found that while AI handles routine queries well, it struggles with the emotional complexity of certain customer interactions, which makes human oversight and escalation paths essential. Dialpad says its platform can support both: 97% of its contact centre customers already use AI, and the system assists human agents in real time as well as run autonomous interactions.
On governance, the company introduced Guardian, a real-time supervisor that monitors agentic AI interactions continuously to manage data exposure and maintain compliance. This governance is in the agent lifecycle from the start, rather than added after deployment. That matters in a market where 91% of consumers now expect an explanation for AI-made decisions, and 87% of CX leaders say AI transparency will be a baseline requirement for any customer-facing AI within two years.
Dialpad reports it has delivered over 775 million AI-generated call recaps and 450 million AI CSAT scores to date, drawing on a combination of proprietary speech, intent, and task models alongside third-party large language models.
