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For me, the real problem with AI in customer service isn’t that it exists, it’s that it often feels like you’re talking to a robot that doesn’t really “get” what you’re saying. One situation that sticks with me is when I had issues with my bank’s mobile app. I called support, and the first thing I got was the automated AI system. The problem I had wasn’t one of the “standard” ones, so it kept pushing the same canned answers back at me. After a few minutes of frustration, I finally got transferred to a human agent. The interesting thing is, even though that person couldn’t immediately fix the issue, I left the call feeling more relaxed, simply because they asked me the right questions, let me explain everything, and made me feel understood. That human part is what AI still struggles with. If AI is going to make interactions feel personal, it has to do more than spit out quick responses. It needs to listen the way people listen. That means asking clarifying questions before offering a solution. It also means learning from real conversations, not just reading scripts, but actually picking up how humans talk, where they pause, when they use humor, and how they handle frustration. If AI could “sit in” while humans solve problems, it would learn that flow and stop sounding so generic. Amazon’s customer service is actually a good example of where this balance already works. When you reach out, the AI doesn’t try to solve everything on its own. It takes the basic information like your order number or what type of problem you’re having, and then smoothly hands you to a person if the issue needs more attention. Sometimes it even comes back later in the conversation to wrap things up, like confirming a refund. As a customer, you don’t really notice the handoff, because it feels seamless. And that’s the key: it feels like someone is actually paying attention to you, not just pushing you through a system. If I were to sketch it out, it’s kind of like this: Customer explains problem ---> AI listens + asks clarifying Qs ---> Human rep takes over if needed<--- AI can return for simple follow-up (refunds, updates) The point is, personalization doesn’t mean AI has to act exactly like a person. It means the customer walks away feeling like they were heard. If the AI can do that by clarifying, by knowing when to step aside, and by sounding less like a script, then the interaction will feel personal and trustworthy. Otherwise, people will just keep waiting for the human rep, like I did with my bank.

AI is very well capable of interacting with customer and make them feel personal in each interaction by merging data, context and empathy at scale without crossing boundaries of trust. Better customer interactions with less customer efforts and high CSAT scores will definitely help the business expand Customer’s expectation from any service are · Quick response on any queries raised · Receive accurate response on queries raised to avoid asking repeat questions · Faster query resolution with minimum interactions · Easy to interact with and have a sense of personal touch by letting them feel valued, heard and understood · Expect trust on data privacy AI helps in better interaction with customer by: · Collecting the context with consent by pulling required data keeping in mind not using hidden data · Knowing customer better and in depth by building customer profile using data from past purchases, past interactions or support tickets, browsing history, etc · Use smart prompts for Bots that works on prefilling summary and also acknowledge earlier context showing respect and care · Feel customer valued by predicting needs and suggesting next steps that will help query resolution prior customer asks the question · Switch tone basis customer tonality and empathize basis sentiment analysis that reflects customer sentiment For example, Account Payable Helpdesk is the function included in Procure to Pay process that handles queries from vendors, internal or external stakeholders related to invoices processed, payments done and PO created. Below are few AI capabilities mentioned that can be used in AP Helpdesk across PTP: · Build AI Chatbots for automated query handling with 24/7 support and less repetitive tickets · Routes the ticket to required department basis query raised for faster and convenient resolution · Captures invoice data using OCR and NLP from documents or emails · Proactively inform vendors or required stakeholders on invoice status thereby reducing escalations · Resolve complex queries by searching policies, SOPs, etc using intelligent search & knowledge base · Adjust the tone basis customer’s response and urgency thereby building trust · Flags invalid invoices, duplicate payments thereby preventing financial losses