Diego Martins, Vice President of Artificial Intelligence, Globant, on the future for chatbots.
Chatbots powered by Generative Artificial Intelligence (GenAI) are revolutionizing the way businesses interact with their customers, offering operational efficiency and personalization at scale. However, training an Artificial Intelligence (AI) to deal with complex service situations is still a major challenge, given that the ability of this technology to understand and solve difficult problems can be the difference between a satisfied customer and a frustrating experience.
According to a survey by Capterra, an online market consultancy, 70% of consumers in the country believe that Customer Service (SAC) has improved in recent years. With the integration and advancement of AI in organizations, customer service system tools and conversational AI platforms have helped drive this customer satisfaction.
The benefits that these tools offer, such as 24/7 availability, the absence of language restrictions, multichannel capability, and the maintenance of the context of previous conversations are the differentials of these tools in customer service.
It is also possible to observe that the initial image of chatbots as mere cost savers is changing, as technological capabilities have advanced significantly, allowing for a more satisfactory user experience, especially with the more humanized aspect of interactions during service. This is because, by using GenAI, chatbots can understand the context and nuances of conversations and, in this way, begin to offer support closer to humans, leaving aside the ‘robotic’ profile to create a more engaging and satisfying experience.
Another advantage of this type of service is that GenAI allows for the automation of repetitive processes, freeing agents to focus on complex and higher-value interactions, which ultimately increases efficiency and reduces operational costs.
Furthermore, nowadays, it is no longer difficult to find companies that let the tool resolve 100% of some non-critical conversations or complaints.
However, for these advantages to be put into practice, companies must consider specialized training of the tools. In this sense, generative AI can be combined with classic decision flows and innovative deterministic models to make the most of each technology in unique solutions.
It is important, therefore, to balance the efficiency of chatbots with the need for a human touch so that the tool is able to recognize when a customer needs further assistance and transfer the conversation to an agent smoothly and efficiently.
In this process, there are challenges that must be taken into account. Among them is data management, customization and integration with legacy systems using robust APIs and middleware solutions, in order to ensure that chatbots can access and use accurate and up-to-date information.
As we move into the digital age, the use of these AI tools has ceased to be just a ‘trend’, to become a strategic necessity for any business looking to optimize customer service. In this context, the expectation is that, over time, chatbots will become even more advanced, capable of dealing with more complex interactions, however, always with human supervision, in order to provide increasingly satisfactory and efficient experiences to each user, ensuring not only their satisfaction, but also the loyalty and success of their business.
