The App of the Future Is Voice — Not a Screen. Mitel's CTO Luiz Domingos Explains Why. — AI Summary

Summary

Luiz Domingos explains how enterprises must evolve legacy infrastructure by adopting API-first, modular AI services to achieve measurable ROI. The focus has shifted from speculative AI pilots to operational, agentic workflows that integrate directly with enterprise communication tools to drive efficiency.

Key Topics

• Agentic AI: Agentic AI moves beyond providing insights to interacting with enterprise systems to complete tasks like ticket creation or scheduling. It changes the listener's perspective by shifting the focus from 'AI as a calculator' to 'AI as a coworker' that requires new governance frameworks.
• RAG (Retrieval-Augmented Generation): RAG bridges the gap between generic LLM knowledge and specific business needs by 'augmenting' the model with enterprise-specific knowledge bases. It is the core requirement for turning 'vanilla' AI into an enterprise-ready tool.
• Edge AI: Edge AI is critical for enterprise communications where milliseconds of latency can lead to poor outcomes in live interactions. It also ensures data sovereignty, keeping sensitive communications within the organization's perimeter.

Key Takeaways

• Audit your internal workflows for friction before selecting AI vendors.