Although 81 percent of enterprises in the State of International Cloud Voice survey report using AI in the voice channel, many remain concerned about the quality of its output. Poor audio, latency, packet loss, or an unstable connection can prevent AI from interpreting a customer accurately and undermine transcription, sentiment analysis, and real-time agent recommendations. Evaluating AI performance therefore requires visibility into the voice infrastructure supporting each interaction.

Managing Voice as a Strategic Application

The State of International Voice report found that 79 percent of organizations expect their voice environments to change within the next one to two years. For 40 percent, those changing needs will result in a shift to a new preferred provider, while 34 percent plan to select a specialty global voice provider. Greater control and the ability to better leverage AI are among the primary reasons for that shift. Enterprises increasingly view voice as a strategic business application requiring centralized ownership, operational control, and continuous performance management.

Consolidating providers creates a consistent way to connect voice services with contact center and AI applications across markets. It also gives IT teams greater visibility into provisioning, routing, call quality, and phone number usage and spend, while reducing the effort required to coordinate numerous providers.

Visibility becomes critical when an interaction fails. The cause may be a carrier, routing decision, local connection, contact center platform, or AI application. Without end-to-end performance data, teams can spend valuable time determining where the problem occurred. Proactive diagnostics help identify reachability, stability, and call quality problems before customers report them. Monitoring AI- and human-handled calls through the same environment also allows teams to identify patterns across applications, providers and markets.

Effective management requires close collaboration between IT and contact center teams. IT oversees infrastructure, architecture, security and vendor strategy. Contact center leaders understand customer journeys, agent workflows and service outcomes. Together, they must define shared standards for performance, escalation and accountability.

Security and Trust Must Be Built into the Voice Channel

AI increases the potential scale and sophistication of voice-based threats into the contact center. Enterprises must protect the infrastructure and their agents, the identity and data behind each interaction — all while keeping the customer experience accessible. Inbound and outbound calls present different challenges. With inbound calls, companies need to verify the caller and detect attempts to obtain information fraudulently. With outbound calls, the first challenge is getting the customer to answer. Robocalls, spam, and number spoofing have made consumers increasingly reluctant to trust unfamiliar calls.

AI agents may allow an enterprise to initiate a greater number of calls, but volume will accomplish little if customers refuse to answer. Organizations need to manage the numbers and branding displayed, monitor how carriers and devices categorize calls, protect their numbers from misuse, and maintain a consistent identity across markets. These capabilities make trust an operational requirement. Caller identity, number reputation, authentication, and transparency must be managed across the enterprise’s inbound and outbound communications strategy.

A Practical Path to AI-Ready Voice 

While consolidating and streamlining providers can seem daunting, enterprises can move forward in stages, beginning with a clear view of the current voice environment. Leaders should understand which providers support each country and application, how calls are routed, where performance data resides, and who is responsible when an interaction fails.

Understanding that assessment provides the basis for several practical actions, such as moving remaining legacy voice services into a cloud environment that can connect with the broader enterprise technology stack, and consolidating providers where it improves consistency, control and visibility. It also becomes easier to find the right integration points for voice infrastructure with AI, CCaaS and CX applications through open, vendor-agnostic connections.

Having a clear picture of voice infrastructure enables appropriate setting of performance standards for latency, call quality, uptime and reachability across AI and human interactions. Proactive testing and monitoring to identify problems before they affect customers becomes achievable. And a shared ownership between IT and contact center teams optimize the voice environment for performance, security, trust and customer outcomes.

Cloud voice infrastructure is the missing link between AI capability and customer experience. Centralized voice orchestration, flexible integrations, performance visibility and proactive monitoring give enterprises control over how AI-powered calls connect, sound and scale. With that foundation in place, multinational organizations can improve customer experience, simplify global operations, and bring AI into the voice channel without compromising the reliability and trust customers expect.