Google and OpenAI engaged in a price war over voice AI technology, significantly altering the economics of voice automation. This shift, coupled with the emergence of a new "Unified" modular architecture, is redefining how enterprises approach compliance in voice AI, making architectural choices more critical than model quality alone.

In August, OpenAI responded to Google's aggressive pricing of Gemini 2.5 Flash and Gemini 3.0 Flash with a 20% price cut on its Realtime API. While this narrowed the gap, Google's pricing still offered a substantial advantage, positioning itself as a high-volume utility provider. This price reduction made voice automation economically viable for a broader range of workflows, including those previously deemed too inexpensive to automate.

The market impact is substantial. Enterprises are now re-evaluating their voice AI strategies, moving beyond pilot programs to deploy voice agents in regulated, customer-facing workflows. This transition elevates governance and compliance to paramount concerns, overshadowing the previous focus on raw model performance. The architectural decision—whether to adopt a "Native" speech-to-speech (S2S) model or a "Modular" stack—has become a critical determinant of an organization's compliance posture.

Historically, enterprises faced a trade-off: "Native" S2S models offered speed and emotional fidelity, while "Modular" stacks provided greater control and auditability. This binary choice led to distinct market segmentation. However, the emergence of a "Unified" modular architecture, which physically co-locates the disparate components of a voice stack, is blurring these lines. This new architecture promises to offer both the performance of Native models and the control of Modular stacks.

Looking ahead, the trend suggests that architecture will continue to be the primary driver of compliance in voice AI. As regulatory scrutiny intensifies and voice agents handle increasingly sensitive customer interactions, the ability to demonstrate control, auditability, and data security will be crucial. The "Unified" modular architecture is poised to become the dominant paradigm, enabling enterprises to navigate the complex landscape of voice AI compliance while capitalizing on the economic benefits of commoditized "raw intelligence" offered by providers like Google and OpenAI.