Scaling Agentic AI in Voice Platforms the Right Way

Many organizations are eager to implement artificial intelligence (AI) in their voice channels but moving from a successful pilot to a full production rollout requires more than just flipping a switch. It’s a strategic, cross-functional effort that involves more than just technology; all stakeholders need to feel comfortable. Based on insights from recent client work, here’s what it takes to scale Agentic AI in voice with confidence and clarity.

1. Start with a Focused Use Case

Begin with a single, high-volume, low risk call type.  Order status, billing inquiries, rewards and loyalty information, or simple account updates are great examples. These transactional interactions are ideal for proving value without introducing emotional or high-stakes complexity.

For example, in healthcare, scaling may begin with benefit lookups and grow to include claims status updates. In financial services, you might expand from balance inquiries to fraud dispute resolutions. In retail, order status inquiries could lead to AI managing returns or exchanges.

While Agentic AI can express a basic level of empathy through tone, language, and response structure, it does not yet match the nuance and emotional intelligence of a live human agent. That’s why emotionally charged use cases (e.g., complaints, cancellations due to hardship, or life-changing health-related inquiries) are least suited for an initial deployment.  Instead, focus on repetitive, low-complexity interactions that currently take up significant agent time.  Then:

• Prioritize tasks where resolution is clear-cut, with limited need for judgment or deep emotional engagement.
• Determine the portion of the interaction volume that the AI will assist with handling, creating an A/B testing environment.
• Establish pilot success metrics: containment rate, positive deflection, resolution confidence, and customer comfort interacting with AI, and overall experience.

2. Plan for Human-in-the-Loop (HITL) Feedback

Agentic AI is not set-it-and-forget-it. Real-time feedback and supervised learning help refine behavior and responses over time.

• Using your established quality assurance (QA) program, relevant staff should review 100% of all AI interactions as soon as they are complete. Evaluations should flag breakdowns in logic and experience.
• Based on outcomes, build processes for collecting agent and customer feedback to continuously train and improve the model.
• Use dashboards to monitor exceptions, sub intents, and customer sentiment patterns.
• Leverage HITL tools to require Human agent approvals for sensitive changes and or to check the Agentic AI Agents logic.
• Ensure that the handoff between Agentic AI and human agents is seamless. Implement soft handoff mechanisms where AI-generated conversation summaries are passed to the agent, allowing for continuity and reducing customer frustration

3. Build on What Works and Expand Gradually

Once your pilot is delivering consistent results, allow the agentic AI to handle more of the volume.  You can then begin to expand into adjacent use cases. Move from frequently asked questions (FAQs) to action-oriented tasks like processing payments, updating accounts, rescheduling appointments, or developing specialized flows for different customer segments.

Scaling should be iterative not rushed to ensure customer trust, confidence, and acceptance as well as organizational readiness, stability and employee confidence and acceptance.

4. Don’t Forget the Infrastructure

Scaling doesn’t mean starting over. Modernizing your voice platform starts with Next-Generation IVRs.  These are AI-enhanced systems that go beyond traditional touch-tone menus to support natural language, contextual routing, and intelligent automation.

These next-gen interactive voice response (IVRs) systems act as the foundation for layering Agentic AI capabilities, helping you deliver smarter, more efficient customer interactions without a full rip-and-replace of legacy systems.  Consider following this path and understand that these steps can be done in phases regardless of whether your voice platform is on-premises, fully cloud-based, or a hybrid environment.

• Leverage your existing telephony, authentication, and customer relationship management (CRM) infrastructure.
• Use orchestration layers or “wrappers” to introduce AI without disrupting existing operations.
• Enable these modern IVRs to pull in web session data, personalize flows, and adapt to customer behavior in real time
• Next-Gen IVRs are the gateway to a modern voice platform.  They make it possible to deploy Agentic AI sooner while positioning your organization for future scalability.

5. Measure, Monitor, and Optimize

Rollouts should be guided by performance data not instinct or hype. While traditional operational metrics like containment, average handle time (AHT), and escalation rates are essential, measuring both customer and employee experience as well as customer confidence are just as critical to success.

Operational Metrics

• Containment rate
• First Contact Resolution
• AHT and agent deflection
• Escalation and handoff rates

Customer Experience Metrics

• Customer Confidence – What is your customer’s level of confidence with your company’s products or services post interaction?
• Customer Effort Score – How easy was it to get what they needed?
• Resolution Confidence – Was their issue fully addressed?
• Net Promoter Score and or Customer Satisfaction – What is the long-term impact on customer loyalty?

During pilot phases, prioritizing Customer Confidence as a leading indicator of trust and future adoption is crucial. If users don’t feel comfortable with AI, they’ll bypass it regardless of its capabilities.

6. Prepare People, Not Just Platforms

Leveraging Agentic AI is a cultural shift, not Just a technology upgrade.  It is essential to educate business partners and frontline teams on how Agentic AI fits into the service ecosystem.  As you make this shift, the following approach will be critical:

• Shift mindsets from “replacement” to “enablement.”
• Right-skill agents for roles like model tuning, HITL assistant, QA, and knowledge base curation.
• Use AI to empower agents with better tools, insights, and context during live interactions.
• Empower your people; help them to understand that the intent is for AI to support them, not replace them.

Closing

Scaling Agentic AI in voice platforms isn’t just a tech deployment, it’s an operational and cultural transformation. With the right partner, the right use case, and a disciplined rollout strategy, your organization can unlock a more scalable, responsive, and cost-effective customer experience.

At PTP, we specialize in helping organizations modernize their voice platforms, integrate Agentic AI, and implement scalable Next-Generation IVR solutions. Whether you’re just exploring possibilities or ready to accelerate your AI journey, we can help you define the right path forward.

Let’s connect and discuss how PTP can help you bring smarter conversations to life.

[1] https://www.mckinsey.com/capabilities/operations/our-insights/where-is-customer-care-in-2024