Klarna’s $15 billion IPO was more than a financial milestone. It spotlighted how the Swedish buy-now-pay-later (BNPL) firm is grappling with artificial intelligence (AI) at the heart of its operations.
Back in 2023, Chief Executive Sebastian Siemiatkowski suggested AI could replace large parts of the company’s customer-service workforce. The remarks sparked pushback from employees and skepticism from customers, many of whom doubted whether the technology was advanced enough to provide empathy and reliability at scale.
Pivoting and Learning
Klarna’s first wave of AI adoption proved too rigid, with customers finding the experience inconsistent. The company now pivoted toward a blended approach: AI for speed and scale, humans for empathy and trust. That adjustment echoes a lesson resonating across industries. AI works best when it augments, rather than replaces, human agents.
The company’s focus on human-powered customer support shows how the firm is hiring again to ensure customers always have the option of speaking to a person. “From a brand perspective, a company perspective, I just think it’s so critical that you are clear to your customer that there will be always a human if you want,” Siemiatkowski told Bloomberg News, as reported by PYMNTS.
As Vinod Muthukrishnan, vice president and chief operating officer of Webex Customer Experience Solutions at Cisco, explained, many financial institutions are moving past pilots and into deployment.
“These firms are increasingly leveraging their AI focus on hyper-personalized CX [customer experience] such as personal financial advice or dynamic credit limit adjustments and offers, all enabled via real-time analytics,” he told PYMNTS. Retailers and service providers face similar opportunities, provided they align strategy with measurable ROI.
Five Areas for AI, Customer Care
1. Proactive Issue Resolution
AI can anticipate problems before customers complain. Declined payments, unexpected fees or delivery delays can be flagged and addressed in real time, turning frustration into loyalty. Most firms still operate reactively, in part because data remains siloed across payments, logistics and support and closing these gaps could sharply reduce call volumes.
2. Hyper-Personalized Support
Consumers now expect service that reflects their history and preferences. AI can tailor repayment options, loyalty incentives, or offers based on real-time data. Walmart, for example, has deployed AI-powered personalization tools to refine its app and eCommerce experience. Predictive analytics can also flag anomalies that suggest fraud or disputes, thereby reducing chargebacks. Yet many retailers still rely on generic scripts.
3. Multilingual, 24/7 Coverage
Global commerce does not keep office hours. AI chatbots and voice systems provide round-the-clock, multilingual support. New multimodal systems can handle voice, text, and even images, creating richer customer interactions. PYMNTS has reported that customers value this always-on flexibility, but many firms still lean on nine-to-five call centers or outsourced night shifts.
4. Sentiment Detection and Emotional Intelligence
Speed matters, but empathy builds loyalty. AI can read tone and phrasing in real time, alerting human agents when a customer is upset. This hybrid model ensures efficiency without sacrificing trust. Rezolve’s Brain Suite applies empathy-driven AI to reduce cart abandonment, which accounts for nearly 70% of lost online sales. Yet sentiment detection remains rare in many call centers.
5. Insights Beyond the Call Center
Complaints can expose flaws in checkout flows, packaging or design. AI can analyze these patterns, turning customer service into a source of business intelligence. Google’s Vision Match tools, for example, feed insights from shopping behavior back into product strategy. Few enterprises close this loop.
ROI as the Deciding Factor
For executives, ROI is the real test. Projects that fail to deliver lower handle times, better satisfaction scores, or reduced churn rarely scale. “AI as with any new technology risks adoption and integration without a clear strategic alignment,” Muthukrishnan warned. “Too many pilots or implementations can lead to a fragmented focus.”
“We’re already in market with our AI agent for autonomous and scripted self-service,” Todd Fisher, CEO and co-founder of CallTrackingMetrics, told PYMNTS.
“In a recent survey, 72% of respondents rated Webex AI Agent as equal, if not better, than a human agent. And our customers have reported an 85% reduction in agent call escalations, a 22% reduction in average handle time, and a 39% increase in CSAT [customer satisfaction] scores.”
Source: https://www.pymnts.com/