With the business world expanding rapidly, keeping up with the space and pleasing consumers is increasingly challenging. As demand for advanced self-service options grows, AI and machine learning are set to play a pivotal role in enhancing customer experience on behalf of brands. Over the next few years, the landscape of customer service will continue to evolve as technologies become more sophisticated, offering new capabilities while also presenting challenges that brands need to navigate carefully.
Advanced AI capabilities
“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,” Raghunandan Saraf, CEO and founder, Saraf Furniture, told BrandWagon Online. Additionally, AI-enabled multilingual support promotes consistent service across languages, thereby encouraging more inclusivity in diverse global markets. From what it is understood, AI’s voice recognition capabilities and predictive models are poised to revolutionise customer support and set new standards for proactive, personalised, and seamless customer experiences.
80% of customer service and support organisations will be applying Gen AI to improve agent productivity and customer experience by 2025, as per a study by Gartner. AI’s role in customer support is expanding significantly, with advancements in machine learning enabling more intuitive and effective interactions. Currently, AI systems handle routine inquiries and provide personalised responses based on user data. “In the next few years, AI will play a vital role in handling and responding to customers at an individual level considering their history, preferences as well as their current mood while interacting with the brand in real-time,” Atif Shamsi, CEO and founder, OuchCart, said. Experts believe that these interactions will be highly dynamic, as machine learning algorithms adapt with each interaction to increase accuracy and relevance.
Challenges
AI can pose challenges, particularly when it lacks the contextual understanding of specific industries, leading to generic or even incorrect responses. Many vendors struggle with complex deployments, inefficient integrations, and high total cost of ownership (TCO), resulting in subpar personalisation and agent experiences. A hybrid support model that combines AI efficiency with human expertise is essential when AI struggles to address complex customer issues. Routine queries are better handled by AI, while complex or emotionally sensitive situations may require human intervention.
To address these challenges, continuously training AI systems through machine learning helps them understand more intricate problems over time. Employing real-time monitoring tools can identify when customer frustration is building up, promptly switching to human support before dissatisfaction escalates. “Additionally, businesses should inform their customers about what AI can do and what its limitations are to set clear expectations. Customer tone and urgency can also be analysed using sentiment analysis and NLP to provide more personalised and empathetic responses,” Saraf added.
Personalisation and self-service
“We invest in training our AI using data from escalations to improve its capabilities and reduce limitations. Despite this, we ensure customers can easily access human support when needed,” Shamsi highlighted. 71% of consumers expect companies to deliver personalised interactions, according to a report by McKinsey & Company. To be sure, since personalisation is a critical feature, AI-driven self-service platforms should offer personalised experiences based on customer data, preferences, and previous interactions. This helps create a sense of familiarity and relevance, enhancing the overall user experience.
Furthermore, the platform should feature robust self-service resources like knowledge bases and FAQs (Frequently Asked Questions) to help customers find answers independently and reduce the need for human agent intervention.
“Finally, the issue with specific weaknesses of Gen AI is not something unique to artificial intelligence but is about balance,” Shamsi said. Combining the effectiveness and rigidity of AI with the warmth and knowledge of human agents allows brands to offer the best of both worlds: an innovative yet endearing customer support service that handles clients’ problems effectively while making them feel valued at every turn.