Can AI improve customer service ?

 

Exclusive to BrandWagon: Can AI improve customer service while overcoming its obstacles?

According to a Gartner survey, 80% of customer care and support organizations would use Gen AI to increase agent efficiency and enhance the customer experience by 2025.

The business world is growing quickly, making it harder to stay in the space and satisfy customers. Artificial intelligence (AI) and machine learning (ML) are expected to be key components in helping brands improve customer experience as the need for sophisticated self-service alternatives rises. In the upcoming years, as technology advance and offer new possibilities and problems that brands must carefully handle, the customer service landscape will continue to change.

enhanced AI capabilities

Saraf Furniture’s CEO and founder, Raghunandan Saraf, told BrandWagon Online that “advanced Natural Language Processing (NLP) and voice recognition tools can contribute to a more immersive experience for customers by offering lifelike conversations that transcend platforms and are contextually sensitive.

“ Furthermore, AI-enabled multilingual support encourages increased inclusivity in a variety of international marketplaces by fostering consistent service across languages. Based on current understanding, AI’s predictive models and voice recognition skills have the potential to completely transform customer service and establish new benchmarks for prompt, individualised, and seamless customer experiences.

According to a Gartner survey, 80% of customer care and support organizations would use Gen AI to increase agent efficiency and enhance the customer experience by 2025.

With improvements in machine learning enabling more natural and efficient interactions, artificial intelligence’s involvement in customer assistance is growing dramatically.

At the moment, AI systems answer common questions and offer customized answers based on user information.

Atif Shamsi, the CEO and founder of OuchCart, stated that artificial intelligence (AI) will become increasingly important in the next years for handling and responding to clients on an individual basis while taking into account their past, present, and preferences while interacting with the business in real-time. Experts predict that because machine learning algorithms adjust to improve accuracy and relevance with every connection, these interactions will be quite dynamic.

Obstacles

AI can be problematic, especially when it doesn’t grasp the context of particular sectors, which might result in responses that are too general or even inaccurate.

A lot of vendors have trouble with difficult deployments, ineffective integrations, and expensive total cost of ownership (TCO), which leads to poor agent experiences and personalization. When AI is unable to resolve complicated customer issues, a hybrid assistance model that blends human expertise with AI efficiency becomes crucial.

Artificial intelligence is better at handling routine requests, yet humans may still be needed in difficult or emotionally charged situations.

In order to overcome these obstacles, AI systems are continually trained via machine learning, which gradually increases their understanding of increasingly complex issues.

By using real-time monitoring technologies, one can quickly transfer to human help when a customer’s displeasure reaches a critical level and prevent further escalation. In order to set clear expectations, businesses should also tell their customers about the capabilities and limitations of AI.

Sentiment analysis and NLP can also be used to analyze the urgency and tone of the customer in order to deliver more individualized and sympathetic responses, Saraf continued.

Customization and independent maintenance

“To increase our AI’s potential and lessen its limits, we invest in training it with data from escalations. In spite of this, Shamsi said, “we make sure clients can simply contact human support when needed.” As per a McKinsey & Company survey, 71% of consumers anticipate personalized interactions from companies. AI-driven self-service systems should, in fact, provide customized experiences based on customer data, preferences, and past interactions, as customisation is a crucial feature. This improves the user experience overall by fostering a feeling of familiarity and relevancy.

Strong self-service tools like knowledge bases and FAQs (Frequently Asked Questions) should also be included in the platform to assist users in finding solutions on their own and lessen the need for human agent assistance.

In the end, Shamsi stated, “the problem with particular weaknesses of Gen AI is not something unique to artificial intelligence but is about balance.” Brands can give the best of both worlds with this innovative yet charming customer care solution that effectively addresses clients’ problems while making them feel appreciated at every stage. This is made possible by combining the efficacy and rigidity of AI with the warmth and understanding of human agents.