Conversational AI for enterprise

What conversational AI enables for the enterprise

Conversational AI uses machine learning and natural language processing to understand a wider range of customer questions than a traditional, menu-based chatbot, and to respond in a more natural, human-sounding way. For enterprises, that can mean handling higher volumes of customer inquiries, supporting more channels, and keeping hiring and expansion costs down as demand grows.

Where conversational AI creates the most value is in how it's deployed. A tool that can only answer questions still leaves customers waiting on a human agent for anything that requires action. That's the gap agentic AI is designed to close, and it's the focus of the rest of this page.

The enterprise conversational AI journey: from scripted to agentic

Not every enterprise is starting from the same place, and that's fine. Conversational AI capabilities generally fall along a spectrum, and Dialpad can meet teams along it.

Scripted flows and rules-based bots

Many customer service teams start here, and for good reason: an enterprise chatbot built on a defined decision tree can be a fast, low-risk way to automate common, well-understood requests, like sharing store hours or routing a call to the right department. The tradeoff is that these flows can only handle the specific paths they were built for.

Conversational AI

The next step is a system that can understand a wider range of phrasing and intent, hold context across a conversation, and pull answers from structured and unstructured knowledge sources, like help center articles or past customer conversations, rather than a fixed script. This is where enterprises often see a meaningful jump in self-service resolution and customer satisfaction.

Agentic AI

The furthest point on the spectrum, and the area Dialpad is heavily focused on, is agentic AI: systems that don't just generate a response, but understand a goal, make a decision, and take action inside connected business systems. A Dialpad AI Agent can look up an order status, verify a customer's identity, reschedule an appointment, or escalate to a human agent with the full conversation history attached, without needing a human to manually complete each step.

Enterprises don't need to choose one point on this spectrum and stay there. Many run rules-based flows for some use cases while piloting AI Agents for others, and expand as those pilots prove out.

What makes Dialpad's approach different

A full-stack agentic platform

Conversational AI, contact center, and AI Agents run on one platform, so context isn't lost when a conversation moves from an AI Agent to a human agent. Teams can also see performance across all three in a single set of analytics rather than piecing it together across separate tools.

Hybrid by design

Human intervention is treated as a feature of the system, not a fallback. Dialpad AI Agents can handle what they're configured to handle, then hand off to a human agent when a conversation calls for it, along with the context that agent needs to pick up where the AI left off.

Data-driven and no-code by default

Setting up an AI Agent doesn't require a data science team. Skills are configured through guided settings and natural-language instructions, and admins can test an agent before publishing it. This can shorten time to value and make it easier to see where an agent is working well and where it may need adjustment.

Built for enterprise governance and trust

Enterprise deployments of conversational and agentic AI typically come with real governance requirements, and Dialpad's platform is built with those in mind.

• Data isolation: Customer data is segregated within Dialpad's multi-tenant architecture.

• PII redaction: Sensitive information can be automatically masked in logs and transcripts.

• Guardian: An AI safety layer is designed to monitor for and help prevent abuse, hallucinations, and security vulnerabilities within agentic workflows.

• Compliance: Dialpad's platform is built to align with standards including SOC 2, HIPAA, and GDPR. For the most current details on certifications and compliance scope, visit the Dialpad Trust Center.

Skills, integrations, and vertical templates

Dialpad AI Agents connect to the systems enterprises already use for customer-facing work, including Salesforce, Calendly, ServiceNow, Google Calendar, Zendesk, Microsoft Outlook, HubSpot, and AthenaHealth. Common skills include knowledge retrieval, scheduling, order status lookup, identity verification, and feedback collection, and teams can configure custom integrations for systems specific to their business.

Vertical templates are available for industries with common, well-defined support and service workflows, including healthcare, legal, sports, and insurance, giving teams a starting point they can adapt rather than building from a blank canvas.

Seamless handoff between AI and human agents

When a conversation needs a human, whether a customer explicitly asks for one or the situation calls for it, Dialpad AI Agents can escalate directly into Dialpad Support for contact centers with context carried forward: reason for the interaction, what's already been attempted, sentiment, and any information the customer has already provided. The human agent isn't starting over, and the customer isn't repeating themselves.