Is voice AI right for your service suite?

Today's agentic voice AI technology is capable of working across business systems to resolve everything from simple, single intent queries, to travel itinerary rebookings – and many organizations are exploring how it can be utilized in their customer service suite. 

But not all customers are sold just yet. 

Adobe Express surveyed 1,005 consumers in the US who had recently made an in-store or online purchase. Across all customer service situations, it found human interaction remain the consumers' top preference, at 49 percent. Chatbots followed at 41 percent, but voice assistants were selected by only 11 percent.  

As few as five percent of all respondents said they would want to deal with a voice assistant when contacting an organization with a complaint.

These figures indicate that before deploying a system, practitioners need to take several steps to ensure it is being used for the right journeys and moments and that the technology is capable of completing the tasks customers need help with. 

This article covers: 

• How to decide if voice AI is right for your service suite.
• Three customer journeys that can benefit from voice AI.
• The key capabilities your voice AI needs.
• How to prepare for autonomous self-service and five questions to ask your vendor.

You can find out more about selecting voice AI technology for your organization in this whitepaper from Five9. Meanwhile, this whitepaper explains how to tackle the challenges of voice AI. 

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Is voice AI right for your service suite? 

As the customer stats above indicate, any voice AI deployment must be authentic, localized and capable of natural turn-taking without latency issues – it must also resolve the customer's query or successful hand off to a human who can. 
Only then can an organization avoid unhappy customers. 

Assessing whether voice AI can deliver benefits to your customers requires a deep understanding of: 

• The outcomes the technology should deliver: Do you want it to triage enquiries? Solve contacts end-to-end? Give updates for low-level contacts and hand off for more complex contacts?
• Customer preferences: Do you know your customers' tolerance level around how and when automation and self-service options are presented?
• What automation means for your brand: For example a luxury holiday customer may expect a human advisor to answer every call, whereas a banking customer will have an expectation for some level of automation when they contact the service suite. 

This means applications of AI voice depend heavily on the company's use case, brand identity and audience. 

"Moments like cancellations, complaints, or missed deliveries can be emotionally charged interactions and poorly served by rigid, scripted flows," says Ebrahim Hyder, VP of customer care Michael Kors. 

"Voice based conversational AI is increasingly effective at handling early-stage recovery and retention journeys, where tone, speed, and empathy matter. Modern systems can assess intent and sentiment in real time, adjusting responses or escalating to a human when risk is detected," Hyder continues, adding that such an approach supports proactive intervention, which can prevent frustration escalating. 

How does voice AI improve CX? 3 customer journeys that can benefit 

Traditional voice self-service was built for simple, single-intent automation. But advances in real-time speech recognition AI, latency and multi-agent orchestration are expanding what voice AI can actually solve. Here are three customer journeys that can benefit from voice AI. 

Simple intent self-service

Simple, single-intent use cases are the largest share of voice volume in most contact centers. They are high-frequency and high-volume and include balance inquiries, status updates, password resets, and appointment confirmations. 

The scenario: A bank customer calls to check a balance and confirm a recent transaction.

The old journey: Previously, a bot would match intent to a scripted flow, prompt  the customer for account number entry to authenticate and read the balance from a template response. Any follow-up question outside the script would trigger a clarification loop or a transfer and context reset frequently. 

The agentic voice AI journey: The customer says what they want and provides verification when prompted. The voice AI reads the balance, answers the follow-up question and asks if there's anything else. However, with agentic voice AI, if the customer interrupts to ask about a charge, it shifts context without restarting the call.

Outcome: Higher containment and customer satisfaction on the highest-volume calls.

Multi-intent dynamic conversations

A customer who wants to update a payment method and then ask about a charge has two intents. Unlike earlier technologies, agentic voice AI can handle natural conversations such as these, where a customer may interrupt, clarify or switch direction. The context persists.

The scenario: A customer reaches out to change an order and correct their address. 

The old journey: The order-management flow can swap items but can't change the address. The shipping flow can change addresses, but loses the swap context. The customer gets transferred. 

The agentic voice AI journey: In this scenario, context is carried across the conversation and mixed intent can be interpreted. The AI swaps the item, recalculates the shipping window, updates the delivery address and re-confirms.

Outcome: Order modifications are contained and solved in self-service. Customer effort drops and satisfaction increases. 

Autonomous resolution of complex workflows

Until recently, automation ended when a query required reasoning, multiple system lookups, policy application, and action. A multi-agent architecture can handle this. 

A master orchestrator agent directs the conversation. Specialized sub-agents handle identity verification, knowledge retrieval, policy checks, and system writes in the background. The customer experiences a coherent conversation and the platform handles the work behind it. 

The scenario: A weather event cancels a flight and 1,200 passengers need new itineraries before morning. 

The old journey: Contact center queues exceed 90 minutes. The IVR offers "please hold for the next available agent". Most customers rebook themselves on a competing carrier. 

The agentic voice AI journey: The AI checks passenger name records, surfaces eligible re-routes within policy, books the new itinerary, handles seat selection, and updates the loyalty record. Passengers with complex itineraries or special needs get transferred to an agent who already has full context. 

Outcome: Rebookings get absorbed during surges that used to break the queue. Revenue stays with the airline instead of leaking to a competing carrier. 

What capabilities should your voice AI have?

As outlined above, agentic voice agents that can resolve complex workflows will deliver much higher customer satisfaction. But there are specific capabilities within these systems that service leaders need to understand.

Here are some of the key features of the most human-like systems on the market today:

• Latency reduction for real-time turn taking without silences.
• Interruption detection to allow for natural conversation that works with customer speech patterns.
• Multiple intent detection and context preservation.
• Multi-lingual capabilities and/or versatile voices, such as those that represent different or regional accents where necessary.
• Safety guardrails and controls to set clear boundaries for action and system access.

And here are some of the technical features the technology needs to execute workflows: 

• A master orchestrator agent to direct and delegate to purpose-built sub-agents
• Ability to integrate with business systems in order to work across them.
• Low-code/no-code system editors to reduce demand on IT and engineering teams or keep service updates within the service suite.
• Simulation testing abilities to test common and edge scenarios robustly before deployment in live customer environments.

Five questions to ask your voice AI vendor 

Procurement can be a minefield – particularly when different systems sound distinct but have similar capabilities. 

Here are five questions to help you shortlist a system and collaborate with your chosen vendor:

1. Which simple-intent use cases can be enhanced immediately and what's the volume?
2. Which multi-intent workflows are ready for automation today and which need cleanup first?
3. Which complex journeys could benefit most from agentic orchestration and where's the budget pain?
4. Is your architecture built to support scalable AI collaboration or will you have to replatform in 18 months?
5. How will human agents and AI work together and is that designed in, or bolted on? 

Quick links 

• WATCH: How to build the internal case for voice AI agents
• A framework for measuring AI agent performance in CX
• CX budget insights for 2027: 4 spending tips and 11 questions for your vendors