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Agentic AI is reshaping customer loyalty by enabling businesses to deliver personalized, proactive, and scalable experiences. Instead of focusing only on rewards, brands now build lasting relationships through intelligent, data-driven customer engagement.
In today’s episode of the Analytics Insight podcast, host Priya Dialani interviews Amresh Acharya, MD & CEO of Loyalty Rewardz, about how Agentic AI is revolutionizing customer engagement and loyalty. The episode features the evolving trend of companies going beyond conventional reward systems to engage customers using artificial intelligence solutions.
Amresh provides us with information on how AI, machine learning, and data science can be used together to improve customer relationships and balance automation with human touch. Amresh also sheds light on the importance of embracing responsible AI, customer data unification, and enterprise-level personalization to grow one’s business in the future. Here are the excerpts from the interview.
Unlike traditional AI, agentic AI does not simply answer customer queries. It understands context, predicts the customer's future needs, and recommends services accordingly. Agentic AI will help brands provide more engaging experiences which do not come across as transactional.
The concept of loyalty has changed. Now customers expect to be understood by brands, remembered by them, and get customized services. Using artificial intelligence allows brands to develop relationships that motivate consumer loyalty.
To some extent, AI-powered customer service can easily handle frequent queries that require quick answers. However, there are occasions when customers need help that cannot be provided by a machine and requires human assistance.
AI performance is dependent upon the data it gets. Correct and correlated data about the customer helps firms understand their behaviors and preferences and personalize for them. Fragmented data prevents the AI from making any relevant suggestions for its customers.
AI implementation starts with good data management, goal setting, and process design. Companies need to begin addressing customer challenges, have appropriate AI governance, and retain human involvement in critical decision-making processes.
