Is there a connection between the spread of neural networks and the quality of customer service?

Many users across various industries have recently witnessed a decline in customer service quality. Some attribute this to the delegation of responsibilities to AI. This is a rather unconventional trend, considering that technological advancements are typically geared towards enhancing user convenience, streamlining workflows, and finding quicker solutions. We sought the opinions of experts to shed light on this matter.

Sara Blackwood, Executive Director of IT company “BeGeniusNow”, believes that AI’s emergence marks yet another technological revolution. “It will substantially reshape the future of customer service. At present, we are in a transitionary phase. Chatbots are still in their infancy, and people have limited skills in formulating queries for them. When integrated into real service platforms, such as bank customer support or online stores, users often encounter confusion, apathy, and unresolved issues,” shared the expert.

Another expert, Vage Zakaryan, Head of Development at Gem Space superapp, drew conclusions from personal experience regarding the decline in service quality:

“The persistent trend toward automating all processes reduces the time available for personal interaction. There is an increasing dependence on algorithms to handle everything, which consequently lowers the bar and standards for personalized customer service by company employees. As a frequent consumer myself, both for work-related purposes and in everyday life, I have noticed a certain depersonalization in the services provided by most companies. In some cases, this can be advantageous—less unnecessary communication and time saved. However, in other instances, an excessive focus on standardization compromises quality and undermines an individualized approach,” highlighted the specialist.

For companies aiming to enhance the quality and speed of their customer service, it is advisable to utilize bots and AI sparingly and only in areas where support is straightforward and lacks the need for extensive data analysis. Neural networks are not yet capable of conducting deep semantic analysis of dialogues, especially in critical or urgent situations. Furthermore, it is unwise to lower the benchmark for personalized service with the hope of complete automation. In the forthcoming years, replacing humans with machines will undoubtedly not be feasible. Therefore, companies must consciously nurture and train their employees in this field. Employees represent the face of a company and often serve as a catalyst for its profitability, so the level of client-oriented specialist training should be elevated irrespective of the industry.

For those in search of superior services and customer care, it is recommended to explore alternative service providers more frequently, rather than limiting themselves to a few familiar options. This will intensify competition among providers, which invariably has a positive impact on service levels and quality.