If you’re still running a traditional IVR, you’re not alone. You’re also not winning.

Rigid menus, frustrating wait times, and inflexible routing are all symptoms of an outdated system, and the hidden costs are piling up.

Most contact centers know they need to modernize, but making the case for AI voice agents can feel like a leap. That’s why, in our most recent webinar, we tackled this head on.

Ada’s GM of Voice, Shorit Ghosh, and Voice SME, Brian May, pulled back the curtain on how today’s leading enterprises are rethinking their voice channels—starting small, scaling quickly, and seeing outsized returns with AI voice agents for customer service.

Whether you're part of an IT team, a CX leader, or a C-level exec exploring what comes after IVR, this recap will walk you through the five key takeaways on how to build a business case for AI voice agents. But if you want the full demo, the data, and the deeper discussion, you’ll want to catch the full session on demand .

You don’t need to tear down your IVR to modernize it

The biggest mental hurdle for most teams isn’t whether to upgrade, it’s how.

Legacy voice systems are notoriously embedded. They’re tied to decades-old routing logic, workforce tools, reporting dashboards, and agent workflows that no one wants to unravel, despite not being built to deliver great customer service.

Long hold times, unhelpful menu trees, and robotic tone all contribute to repeat calls, low CSAT, and brand erosion. But the biggest problem with IVRs isn’t just the experience, it’s the cost.

These problems are so ubiquitous that both consumers and companies alike have built these limitations into their expectations.

Poor resolution rates and high agent workloads aren’t just inefficiencies. They’re line items.

Human agents today spend 25-40% of their time answering FAQs and policy questions that IVR cannot answer. If you’re operating with 1,000 agents at about 60 cents per call, you could be spending $20 million per year, when AI customer service agents could resolve at a fraction of the cost.

Yet, 90% of companies are still stuck here. Why? Because ripping and replacing voice systems feels risky.

Here’s the first mental shift every team needs to make: modernizing voice doesn’t mean tearing everything down. You don’t need to replatform your entire contact center. You don’t need to dismantle your current IVR. You don’t need to swap out your CCaaS just to prove a point.

You start by layering AI voice agents on top of your existing stack. That’s it.

Getting started with an AI voice agent

The best way to prove the business case for AI voice agents is to start with something simple and strategic.

At what we call “Level 1: Foundational” teams automate the most common low-complexity call types: FAQs, policy questions, store hours, and appointment logistics. These are the inquiries that drive up handle times, tie up agents, and frustrate customers, especially when the only option is “press 1 to repeat this menu.”

With Ada , deploying a Level 1 is simply deploying foundational AI voice automation —and it only takes 4–6 weeks. There’s no downtime and no disruption to your existing call flows. Just faster, smarter service right out of the gate.

This alone is enough to:

• Achieve 30% resolution
• See 150%+ ROI
• Dramatically improve CSAT with a more human-like, flexible experience

Again, this phase is designed to be low-risk. You set clear rules for escalation. High-risk intents (billing, payments, identity verification) are routed to live agents instantly. And you maintain full observability over the AI agent’s performance.

Integration is easier than you think with an AI voice agent

After proving success with basic inquiries, most organizations quickly move on to “Level 2: Action taking uses cases” and start equipping their AI voice agents to take real action.

This includes tasks like rescheduling appointments, checking order status, updating account information, or processing simple changes that don’t require human intervention.

The leap from answering to acting is a meaningful one, but it doesn’t have to be complicated.

Integrating backend systems may sound like heavy lifting, but with Ada’s developer tools and existing APIs , most customers reach this phase within 2 to 8 weeks of launching. And the results are hard to ignore:

• 45% resolution
• 275% ROI
• More agent bandwidth for complex support
• Higher resolution and lower cost per contact

The results are worth it. AI voice agents become significantly more valuable, and your support operation becomes dramatically more efficient. You’ll reduce repeat calls, increase resolution rates, and start shifting your agent workload away from tasks that automation now owns.

At this stage, teams often start to reorganize their support ops. Agent roles shift from reactive support to quality assurance, coaching , and AI management. Some even hire AI Managers to own performance, training, and optimization.

AI voice agents for customer service can drive loyalty and revenue

“Level 3: Loyalty-driving experience” is where AI voice agents stop reacting and start anticipating. Instead of waiting for a customer to request something, your agent recognizes patterns, understands context, and takes action that adds value.

This might look like surfacing a personalized renewal offer. Notifying a customer that their subscription is about to expire and guiding them through a seamless upgrade. Or suggesting a relevant cross-sell based on previous purchases and eligibility.

This is where voice AI becomes transformational. Results at this level are staggering:

• 75%+ resolution
• 500% ROI
• Revenue-generating cross-sell and upsell flows
• Significantly higher customer lifetime value

These aren’t hypothetical scenarios. They’re real-world outcomes made possible with Ada Playbooks . Playbooks let you design and deploy complex, multi-step experiences using natural language and existing SOPs, no code required.

Your voice channel becomes a tool for growth—not just a line item to manage.

Successful teams treat AI customer service agents like a team member

The most impactful AI voice programs don’t treat automation as a tool—they treat it as a teammate. One that requires training, structure, and continuous improvement.

They invest in:

• AI agent coaching: Reviewing transcripts, refining tone, and optimizing decision paths
• Integration depth: Connecting to key systems for richer personalization
• Knowledge management: Feeding the AI fresh, accurate data
• Performance tracking: Using metrics like automated resolution (AR), CSAT, and containment to measure and improve over time

And they don’t try to do it all at once. They start with one high-impact intent, validate results, and scale methodically. Because building an intelligent voice experience isn’t a sprint, it’s a strategic evolution.

AI voice agents are your next best customer service hire

The voice channel is where your customers turn when they need answers fast or when other channels fall short.

If your phone experience is still stuck in IVR purgatory, you’re not just frustrating customers, you’re leaving ROI, loyalty, and revenue on the table.

AI voice agents for customer service change that. They resolve high-volume inquiries, automate complex workflows, and surface insights that help your business move faster. They’re built to improve over time. And with the right platform, they can become your most efficient, scalable, and brand-consistent employee.

With Ada, the answer is simple: you start small, layer on top, prove value fast, and scale with confidence.