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Generative AI heralds a new era in customer service chatbots

The emergence of tools like ChatGPT has transformed conversational interactions between humans and machines. Generative AI's ability to provide accurate and contextually relevant responses makes it particularly valuable for automated customer service environments, such as chatbots and virtual avatars.

La IA generativa marca un cambio de era en los ‘chatbots’ de atención al cliente

The adoption of chatbots has surged in recent years, particularly following the pandemic. DataHorizzon Research reports that the chatbot market was valued at $4.6 billion in 2022, with projections indicating a compound annual growth rate of 21.6 percent, which could drive the market to $32.4 billion by 2032. Additionally, a 2022 survey by customer service company Tidio found that nearly 9 in 10 digital users interacted with a chatbot, with around 80 percent of those users rating their experience as positive.

Despite their advancements, chatbots still face several challenges in providing a truly conversational experience. Their dialogue abilities are often confined to a set of predetermined questions. Moreover, issues with language processing and machine translation pose significant hurdles, particularly for multinational organizations operating across diverse linguistic regions. Additionally, chatbots currently struggle with handling multiple queries simultaneously.

Generative AI is helping to overcome these barriers and achieve more natural interaction. GenAI's large language models and natural language processing are able to generate accurate and contextually relevant responses, build a conversation with the user, and provide high quality translations. These capabilities make it possible for the user to address the machine in a similar way as he or she would address another human being.

According to Gartner estimates, organizations are implementing conversational AI at a rapid pace. The consultancy estimates that by 2026 more than 80 percent of companies will be using models and APIs or will have brought GenAI-based applications into production; a huge leap from just 5 percent in 2023.

La IA generativa marca un cambio de era en los ‘chatbots’ de atención al cliente

The benefits of using chatbots and avatars that integrate natural language processing extend to multiple industries:

The IBM Institute for Business Value has explored the potential of generative AI in the healthcare sector and found that it can shorten the time teleoperators spend addressing patient inquiries by 20 percent. Their study also indicates that direct-query chatbots can provide responses more tailored to a patient's specific condition compared to traditional, generic FAQ sections. This ability to offer more precise alternatives to FAQs benefits not only healthcare users but also clients in banking, insurance, and energy sectors, among others.

Specifically in the financial arena, some Asian banks are beginning to explore how combining digital identity solutions with 'chatbots' and generative AI-based avatars can help them channel hyper-personalized  financial health recommendations through a conversational exchange with their customers.

In addition, among the wide range of AI functionalities presented by Google at its 2024 annual developer conference, the company explored how AI agents can be used to facilitate online purchase returns. The tech giant is working on a tool that locates the receipt in the buyer's email, completes the return form and schedules item pickup.

It is estimated that implementing this technology at scale in customer service centers could boost productivity by 30 percent to 50 percent, according to Boston Consulting Group, as it helps make users' conversations with chatbots faster, more efficient and more satisfying. A survey conducted by the consultancy in 2022 revealed that 95 percent of global customer service managers expected to be able to offer AI-based bots in the next three years.

Two of the key challenges to overcome before the use of generative AI-based chatbots becomes widespread are to overcome ‘hallucinations’ arising from the use of language models and to identify potential biases in the data and understand how to eliminate them. This will result in more accurate and neutral responses, two key elements for end-customer service.

With advancements in language modeling and artificial intelligence, the future promises a range of intelligent, highly responsive, and accurate solutions. These innovations are set to significantly enhance the user experience across all digital service sectors.