Widespread frustration with rigid touch-tone Interactive Voice Response (IVR) systems for customer service underscores the need for more direct and intuitive language interaction. While speech technologies are necessary, the key challenge lies in routing intents from user phrasings to IVR menu paths, a task where Large Language Models (LLMs) show strong potential. Progress, however, is limited by data scarcity, as real IVR structures and interactions are often proprietary. We present a novel LLM-based methodology to address this gap. Using three distinct models, we synthesized a realistic 23-node IVR structure, generated 920 user intents (230 base and 690 augmented), and performed the routing task. We evaluate two prompt designs: descriptive hierarchical menus and flattened path representations, across both base and augmented datasets. Results show that flattened paths consistently yield higher accuracy, reaching 89.13% on the base dataset compared to 81.30% with the descriptive format, while augmentation introduces linguistic noise that slightly reduces performance. Confusion matrix analysis further suggests that low-performing routes may reflect not only model limitations but also redundancies in menu design. Overall, our findings demonstrate proof-of-concept that LLMs can enable IVR routing through a smoother, more seamless user experience -- moving customer service one step ahead of touch-tone menus.

Transformer-based Large Language Models (LLMs) have paved the way for "AI interviewers" that can administer voice-based surveys with respondents in real-time. This position paper reviews emerging evidence to understand when such AI interviewing systems are fit for purpose for collecting data within quantitative and qualitative research contexts. We evaluate the capabilities of AI interviewers as well as current Interactive Voice Response (IVR) systems across two dimensions: input/output performance (i.e., speech recognition, answer recording, emotion handling) and verbal reasoning (i.e., ability to probe, clarify, and handle branching logic). Field studies suggest that AI interviewers already exceed IVR capabilities for both quantitative and qualitative data collection, but real-time transcription error rates, limited emotion detection abilities, and uneven follow-up quality indicate that the utility, use and adoption of current AI interviewer technology may be context-dependent for qualitative data collection efforts.

Securing the Future of IVR: AI-Driven Innovation with Agile Security, Data Regulation, and Ethical AI Integration Khushbu Mehboob Shaikh T echnical Lead, Principal T echnical Account Manager Twilio Inc. Irving, Texas, United States ORCID: 0009-0000-8681-5830 Georgios Giannakopoulos Principal Engineer, Independent Researcher The Hague, The Netherlands ORCID: 0000-0002-3707-3276 Abstract --The rapid digitalization of communication systems has elevated Interactive V oice Response (IVR) technologies to become critical interfaces for customer engagement. With Artificial Intelligence (AI) now driving these platforms, ensuring secure, compliant, and ethically designed development practices is more imperative than ever . AI-powered IVRs leverage Natural Language Processing (NLP) and Machine Learning (ML) to personalize interactions, automate service delivery, and optimize user experiences. However, these innovations expose systems to heightened risks, including data privacy breaches, AI decision opacity, and model security vulnerabilities. We propose a practical governance framework that embeds agile security principles, compliance with global data legislation, and user-centric ethics. Emphasizing privacy-by-design, adaptive risk modeling, and transparency, the paper argues that ethical AI integration is not a feature but a strategic imperative. Through this multidimensional lens, we highlight how modern IVRs can transition from communication tools to intelligent, secure, and accountable digital frontlinesresilient against emerging threats and aligned with societal expectations. I NTRODUCTION Interactive V oice Response (IVR) systems have long served as essential digital entry points in customer service operations, enabling organizations to automate call handling, reduce wait times, and streamline user interactions [1].

Interactive Voice Response (IVR) systems have undergone significant transformation in recent years, moving from traditional code-based development to more user-friendly approaches leveraging widgets and, most recently, harnessing the power of Artificial Intelligence (AI) for automated IVR flow creation. This paper explores the evolution of IVR building techniques, highlighting the industry's revolution and shaping the future of IVR systems. The authors delve into the historical context, current trends, and future prospects of IVR development, elucidating the impact of AI on simplifying IVR creation processes and enhancing customer experiences.

The time is right for investing in the global natural language processing (NLP) market, projected to grow from $20.98 billion in 2021 to $127.26 billion in 2028 at a CAGR of 29.4% in that forecast period. To get a sense on NLP user perspectives, this past February, Applause surveyed its global crowdtesting community to gain insight into perceptions around the use of artificial intelligence (AI) voice applications such as chatbots, interactive voice response (IVR), and other conversational assistants. Check out our summary infographic for some highlights. We had over 6,600 responses from around the world. I want to share our findings and call out a few interesting points.

The time is right for investing in the global natural language processing (NLP) market, projected to grow from $20.98 billion in 2021 to $127.26 billion in 2028 at a CAGR of 29.4% in that forecast period. To get a sense on NLP user perspectives, this past February, Applause surveyed its global crowdtesting community to gain insight into perceptions around the use of artificial intelligence (AI) voice applications such as chatbots, interactive voice response (IVR), and other conversational assistants. Check out our summary infographic for some highlights. We had over 6,600 responses from around the world. I want to share our findings and call out a few interesting points.

Imagine you're planning a vacation for your family. You've spent a generous amount of time researching destinations, booking flights, securing a car rental, and finally, the hotel. After thoroughly researching all of your options, you settled on a property and pick up the phone. After a few rings, you hear a voice on the other end of the line, and you immediately tense up--a voice bot. What could have been a quick and painless phone call turns into a one-sided conversation that seems to take you in circles until finally, you're able to talk to a human on the other end of the line. In 2021, customers value a personal connection, but the convenience of a voice bot is hard to beat for some businesses that just don't have the manpower to handle their current call volume.

The primary focus of every business is to increase growth and value for customers, to meet and exceed their expectations. Nearly 60% of the consumers prefer to communicate with customer service through phone or email. If the customer service branch of the company uses outdated technology, the customers might not be able to reach them, and the staff cannot remain available 24*7. This is where conversational IVR comes to play. For businesses trying to get an edge in the competitive market, improving their organization's customer experience is of high priority.

We are at a true cusp of innovation within all aspects of our life. From shopping to communication, we all rely on technology to make our life easier. There has never been a more critical time to place customers' needs first. With current events, banking has never been more vital, and with a substantial shift in user behavior, the technology that supports customers must also transform and adapt. Those that fail to stay up to speed means losing customers to the competition.

Everyone take a deep breath and calm down. The likeliness of a robot taking over your job any time soon is very low. Yes, artificial intelligence (AI) is a growing trend, and machine learning has improved by leaps and bounds. However, the information technology career field is fairly safe, and if anything, AI/machine learning will only make things better for us in the future. However, a few IT jobs already have experienced the impact of AI, and I want to cover those here.