When I say 'Voice AI,' you might think of a robotic voice asking you to "press 1" if you're calling to block your card. But those days are gone, or at least, they should be. Stellar’s generative AI voice agents speak naturally and guide customers through complex situations with ease. This technology will transform customer service in the next few years. If you're running a contact center, planning for these changes isn't optional—it's essential.

But how do you successfully launch Voice AI in your operations? Our team has years of experience developing and scaling AI at major organizations, including globally recognized banks, insurers, and telecom companies. Here are five crucial lessons we've learned along the way:

1. Be clear on where the value is

Introducing AI for AI's sake won't bring success. Start by identifying your goals and how Voice AI supports them. If cost savings drive your interest, focus on end-to-end automation of calls with the largest average handling time. If enhancing service quality and availability matters more, create a seamless "concierge" experience that identifies customers and routes them appropriately—whether to an AI agent, human advisor, or scheduled callback.

The approach you choose should align with your strategic priorities, not just technical possibilities.

2. Launch early and iterate quickly

This is easier said than done. Once you commit to Voice AI, you'll feel pressure to be "near perfect" before launch. Resist this urge—it robs you of learning opportunities and ultimately leads to a worse product and longer timeline.

In our experience, a voice agent pilot can launch in 1 to 4 months, depending on conversation complexity, your IT platform, and required integrations. Even a limited pilot handling real customer calls provides invaluable learning.

Risk management remains possible with an early launch. At one regulated financial institution, we started with just a handful of calls daily, supervising 100% of interactions during the first three months as we scaled to hundreds of calls per day. Once customers consistently reported good experiences (95%+ satisfaction), the AI agents began operating independently.

3. 'Red team' your solution

You won't encounter many people trying to break your AI agents in normal operations. But if vulnerabilities become known, exploitation attempts multiply quickly. Preparation is essential.

Red teaming—having colleagues deliberately attempt to confuse or manipulate your AI—provides crucial insights no standard testing can match. Teams actually enjoy these exercises; we've organized competitions with prizes for the most revealing attempts.

With Stellar, you get a platform built for compliance and security. We incorporate red teaming outcomes into your AI test harness, ensuring every new deployment undergoes simulated challenges before reaching customers.

4. Bring contact center staff along from day one

Most customer service professionals respond positively to AI when introduced thoughtfully. They see the benefits of automating mundane tasks like identity verification and call logging, freeing them to focus on complex cases where their expertise shines.

This positive reception isn't automatic—it requires involving your team from the project's start, not just during final implementation.

Your existing staff are invaluable assets. They understand customer questions and the nuances of complex requests. Even a few hours listening to their calls reveals crucial knowledge that exists nowhere in your systems or documentation.

We've had remarkable success co-locating development teams directly in contact centers, working alongside experienced advisors. This approach builds mutual respect, shortens feedback cycles, and ensures developers truly understand what works. In one project, this arrangement allowed us to consistently implement improvements within hours of receiving feedback.

5. Plan for rapidly improving AI technology

AI evolves at incredible speed , and this pace shows no signs of slowing down. Your Voice AI roadmap should anticipate these advances. Topics too complex for automation today may be perfectly manageable a year from now. You don't want to complete an AI transformation only to discover you're already two steps behind the state of the art.

Design flexible systems that can incorporate new capabilities as they emerge, and regularly reassess use cases you initially deferred due to technical limitations.

The Learning Mindset

What connects all these best practices is a commitment to continuous learning throughout implementation. This means gathering customer feedback from the earliest stages, welcoming challenges from internal testers, and leveraging the expertise of your experienced phone agents.

Voice AI isn't about replacing the human element in customer service—it's about enhancing it. The most successful implementations create new possibilities for meaningful customer engagement while freeing your team from repetitive tasks.

As you embark on your own Voice AI journey, remember that your implementation approach—how you learn, adapt, and bring people along—determines success more than the technology itself. The future belongs to organizations that master both the technical and human dimensions of this transformation.

Are you ready to take the first step? Contact us, we’re happy to dive into these learnings and demonstrate how Stellar moves you forward.

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