AI in call centers has come a long way. We’re no longer talking about basic chatbots that can only answer a few scripted questions or voice systems that trap callers in endless menus.

What’s emerging now is something much more practical: agentic AI. AI that can actually think through a task, move between systems, and help customers get things done—without replacing the human element entirely.

Dialpad’s new AI agent is a good example of how this technology is starting to show real value for businesses. This article breaks down what the AI agent does, how it works in both chat and voice, and why the way it’s set up matters just as much as the technology itself.

What Makes Dialpad’s AI Agent Stand Out

One of the first things that makes Dialpad’s AI agent different is that it works across both chat and voice using the same underlying technology. Instead of building separate bots for chat and phone calls, businesses can create one AI agent that handles both.

Another big plus is that it’s designed to be low-code or no-code. You don’t need to be a developer to set it up or make changes. That’s important because most businesses want flexibility without relying on engineers every time something needs updating.

Rather than following rigid “if this, then that” rules, the AI agent works off instructions. That means it can handle conversations more naturally, understand incomplete or informal input, and still stay within the boundaries you define.

Why So Many AI Projects Go Wrong

A lot of AI projects fail—not because the technology is bad, but because of how it’s deployed.

The most common problems are:

• Messy or unorganized data
• Trying to automate too much, too fast
• Vague instructions
• Missing guardrails

AI can only work with what you give it. If the data isn’t clean or the instructions aren’t clear, the results won’t be either. That’s why a “start small” approach works best. Solve one or two meaningful problems first, then expand once the AI proves itself.

Chat AI That Feels Natural, Not Robotic

In a chat-based demo, Dialpad’s AI agent showed how far things have come compared to traditional chatbots.

Instead of forcing users to follow a strict step-by-step flow, the AI was able to:

• Handle information provided out of order
• Understand abbreviations, misspellings, and casual language
• Recognize phrases like “this Sunday” and interpret them correctly
• Catch scheduling conflicts and suggest alternatives
• Offer helpful suggestions based on past user behavior
• Send confirmations via email or text
• Automatically sync appointments with a calendar

The key takeaway here is flexibility. People don’t communicate perfectly, and this AI is built with that reality in mind.

Learning Over Time—Without Losing Control

One impressive feature is the AI’s ability to learn patterns over time. If many users consistently request the same preference, the AI can start suggesting it proactively.

That said, learning doesn’t mean loss of control. Businesses can decide whether learning is enabled and what the AI is allowed to suggest. This keeps the experience helpful without letting the AI go off course.

Voice AI That Knows When to Hand Off to a Human

Voice AI often gets a bad reputation because people worry they’ll never reach a real person. Dialpad’s approach is different.

The voice AI is designed to handle common tasks—like gathering information, scheduling, or basic negotiations—but it knows when to escalate to a human.

In a car rental demo, the AI:

• Collected booking details conversationally
• Checked availability and pricing
• Negotiated within preset limits
• Stopped and transferred to a human when boundaries were reached
• Provided vehicle details when asked

The result is a smoother experience where AI helps—but doesn’t trap—the customer.

Why Guardrails Matter More Than Anything Else

Guardrails are one of the most important parts of any AI deployment.

They define what the AI should never do. For example:

• Reveal internal pricing or profit margins
• Share confidential documents
• Expose sensitive customer data

Without proper guardrails, businesses can run into serious problems, including being forced to honor incorrect pricing or exposing internal information.

Dialpad allows guardrails to be set using plain language, not code. If the AI hits a boundary, it redirects the conversation or hands it off to a human. This protects the business while keeping the experience smooth for the customer.

Designed for Non-Technical Teams

Not every business deploying AI has technical expertise in-house—and Dialpad recognizes that.

Businesses are supported by a dedicated team that helps:

• Identify what problems the AI should solve
• Structure data correctly
• Set up guardrails
• Train teams after deployment

There’s also a built-in recommendation system that warns users if changes might introduce risk, such as exposing sensitive data.

Why Dialpad Is a Strong Option

Dialpad’s AI agent is backed by a broader communications platform that includes calling, messaging, and meetings in one place. Businesses can use the AI within Dialpad’s ecosystem now, and future versions will allow even more flexibility across providers.

That makes it a practical option for businesses that want to adopt AI without locking themselves into a rigid setup.

Final Thoughts

Dialpad’s new AI agent shows what agentic AI should look like in the real world. It’s flexible, practical, and designed to help—not replace—human teams.

When implemented thoughtfully, this kind of AI can reduce repetitive work, improve customer experiences, and help teams focus on what actually matters.

Make the right choice today and set your business up for success in 2025!