From static to strategic: Navigating Nuance’s end-of-life with generative AI

Nuance is sunsetting its legacy speech recognition suite. For enterprises, this change is an opportunity to rethink how they interact with customers. Moving from static conversation models to modern platforms affects both strategy and execution.

In a recent episode of Unlocking Vertex AI, host Caleb Johnson sat down with Mark Eichten, Executive Director of TTEC Digital’s Conversational AI Practice, to unpack what this transition means for organizations and how to navigate it with confidence.

Static models are holding enterprises back

Nuance’s end-of-life announcement signals more than the end of product enhancements — it marks the decline of rigid, static systems that demanded extensive data prep and fine-tuning. As Eichten noted, these systems created significant overhead in both development and administration.

Today, generative AI platforms offer a faster, more flexible alternative. Basic agents can be built in under thirty minutes for demo purposes, and pilot data can be used to iterate and enhance experiences rapidly. This agility is a game-changer for enterprises looking to modernize their customer engagement strategies.

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Hybrid agents reduce risk

Rather than diving headfirst into fully generative systems, Eichten recommends a hybrid agent approach. This combines deterministic elements — ideal for regulated or compliance-heavy content — with generative components that handle FAQs and dynamic queries.

 This strategy allows organizations to test the waters with low risk, building confidence in generative capabilities while maintaining control over critical messaging.

Making data “AI-ready”

One of the most overlooked aspects of successful AI adoption is data readiness. Eichten emphasized that enterprise data must evolve from being “human-ready” to “AI-ready.” That means structuring content — whether HTML, PDFs, or CRM records— so it can be ingested and understood by large language models.

Strong data governance is essential. Inconsistent or unclear information can reduce accuracy and harm customer trust. Enterprises that invest in clean, well-organized data achieve better performance and more reliable customer interactions.

Beyond self-service

Generative AI isn’t just about answering questions, it’s about understanding the customer journey. By leveraging enterprise-wide data, organizations can influence behavior, drive upsell opportunities and resolve issues more effectively.

This shift moves conversational AI from a support tool to a strategic asset, capable of shaping customer experiences at every touchpoint.

More than a migration

The move from Nuance is an opportunity for enterprises to rethink how they engage customers. By adopting hybrid strategies, prioritizing data readiness, and leveraging modern platforms effectively, organizations can create smarter, more human-like agents that elevate the entire customer experience.

As Eichten put it, “We’re not just building agents — we’re building experiences.”

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