Experience Exchange: How AI is reshaping IVR and chatbots

What if outdated IVRs and chatbots are quietly driving your customers away? 

Frustration from poor initial interactions can trigger a chain reaction — upsetting customers and overwhelming agents. Is that really how you want your customer service journey to begin?

In our latest Experience Exchange, Tom Lewis, SVP of Consulting at TTEC Digital and Raj Koneru, CEO of Kore.ai, explored how mastering the newest standards in IVR and chatbots, leveraging conversational AI, and understanding critical deployment factors can reshape your customer experience, minimize frustration, and put an end to silent attrition. Here are some of the biggest takeaways from their conversation. 

1. Understanding the outsized impact of large language models (LLMs)

Large language models (LLMs) have shifted the conversational AI landscape. Raj Koneru of Kore.ai notes, “With the LLMs coming into play, a lot of the tasks that you had to do to create that experience have changed and, in some cases, simplified.” LLMs are trained on vast datasets, allowing them to “recognize intent and extract entities from a user's input” with greater precision. This advancement simplifies the creation of more effective conversational experiences.

2. Balancing scripted and autonomous interactions

Looking to the future, Koneru emphasizes the need to balance scripted interactions — which follow predefined paths like traditional IVR prompts — and autonomous interactions, where AI dynamically understands and responds to customer input in real time. He predicts a hybrid approach where “simple transactions and simple flows will use the models and leave it to the model,” while more complex interactions will combine “autonomous and scripted components.” This approach aims to deliver a more natural conversational experience while maintaining necessary control over business rules.

3. Enhancing customer experience through natural language

One of the primary benefits of conversational AI is its ability to facilitate natural language interactions. Koneru notes, “The consumer should be able to say what he or she wants in a very natural way.” He points out that conversational IVRs are already showing improvement over legacy systems, stating, “The fallout from a conversational IVR is much below what it used to be,” highlighting their effectiveness in reducing user frustration and improving engagement.

4. Evolving implementation strategies

Koneru warns against a “big bang” approach to implementing conversational AI. Instead, he supports a “crawl, walk, run” strategy. “Basically, that's the best approach because you start spelling success and you get addicted to it and then add more,” he explains. This incremental approach allows organizations to build confidence and refine their AI systems as they go.

5. Addressing organizational pain points

For successful AI implementation, Koneru stresses the importance of aligning initiatives with organizational pain points. “The first most important thing is what's your pain point?” he asserts. He encourages companies to clearly identify their challenge — whether it’s high customer service costs, difficulty in hiring and training agents, or fragmented data — before investing in AI solutions. This alignment ensures that technological investments are targeted to help you succeed.

6. Choosing the right technology

When selecting AI technologies, Koneru advises companies to focus on understanding the “what and the why” before delving into the “how” of implementation. “Many times, people put the how in front of the what and the why,” he notes. By thoroughly assessing their needs and goals, organizations can choose the most suitable AI tools, whether they require generative AI or traditional conversational AI solutions.

Embrace the change

As AI continues to reshape the landscape of customer interactions, businesses face a clear choice: evolve or fall behind. 

Embracing modern IVR and chat systems isn't just about keeping up with technology — it's about delivering seamless, frustration-free experiences that keep customers loyal and engaged. 

Those who fail to adapt risk losing customers to silent attrition, while those who embrace AI’s full potential will lead the charge in customer satisfaction and operational efficiency.