As businesses increasingly adopt Voice AI technology to enhance customer service, the infrastructure supporting these innovations is becoming a focal point of discussion among industry experts. Alexey Aylarov, CEO and co-founder of Voximplant, emphasizes that outdated telephony systems pose significant challenges to deploying effective AI agents capable of handling real-world phone interactions.
In a recent interview, Aylarov countered common misconceptions about Voice AI, stating, “Many people believe that a Voice AI Agent is simply a ChatGPT with a voice. In reality, production-ready agents are way more complex.” He explained that such agents require a comprehensive infrastructure that extends beyond just advanced language models.
To function effectively, a Voice AI Agent needs essential components, including a real phone number, a large language model (LLM) that can interpret intent and generate responses, and a Speech-to-Text (STT) engine to convert caller audio into text. Additionally, it requires a Text-to-Speech (TTS) engine to turn the agent’s responses into natural speech, as well as a telephony gateway to ensure smooth interaction with the global phone network. Aylarov highlighted the importance of “orchestration,” a term he uses to describe the management of multiple, real-time components working together to deliver a seamless customer experience.
Voice AI technology is increasingly being deployed in business-to-consumer (B2C) sectors. According to Aylarov, despite the convenience of text-based communication, 80 percent of inbound customer interactions occur via voice calls. Voice AI can manage tasks such as scheduling appointments, handling sales inquiries, and even replacing antiquated Interactive Voice Response (IVR) systems that often frustrate customers. “It can triage calls, answer FAQs, and finally route calls to a human agent when necessary,” Aylarov noted.
The adoption of AI in voice workflows is being driven by its ability to operate 24/7, allowing companies to provide instant support without the need for physical call centers. This capability enables businesses to significantly reduce both customer wait times and operational costs. Aylarov stated that the economic advantages are clear: “AI voice agents respond faster, reduce abandonment, and repeat calls.” He added that consumer expectations for immediate multi-channel accessibility are reshaping the customer service landscape.
However, Aylarov cautioned that traditional call centers and legacy customer relationship management (CRM) systems struggle to meet the demands of this evolving market. These older systems often rely on outdated workflows lacking context and speed. “Enterprises need infrastructure that unifies AI models, telephony, and real-time voice systems under a single programmable layer,” he explained.
As Voice AI technology continues to evolve, Aylarov pointed out the growing importance of orchestration platforms. Such platforms facilitate the coordination of various components, including telephony, speech engines, and compliance measures, particularly as regulations can vary widely across different countries. “Just a single vendor can’t solve everything end-to-end,” he added, emphasizing that enterprises must be able to integrate and switch between different service providers as needed.
Developers and businesses adopting AI for voice calls are advised to implement safeguards throughout their systems. Aylarov suggested that organizations should design their pipelines with flexibility in mind, allowing for easy transitions between LLMs and speech vendors as advancements occur. He warned against over-reliance on any single vendor’s performance, as the reliability and capabilities of voice infrastructure can vary significantly by region.
Looking ahead, Aylarov expressed optimism about the future capabilities of AI voice technology, predicting that advancements will make AI sound increasingly natural and indistinguishable from human voices. He anticipates that legacy IVR systems will be phased out in favor of more sophisticated conversational AI, which will enhance customer interactions and expand the scope of automated services.
As Voice AI systems improve, Aylarov believes they will enable proactive customer service solutions, such as logistics coordination and dispute resolution, without requiring human intervention. “Real-time automation will expand outbound capabilities,” he concluded, indicating a transformative shift in how businesses will handle customer interactions in the near future.
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