Klarna’s AI U-Turn: Why Human Empathy Trumps Automation in Customer Service

Klarna is reversing course on AI-driven customer service, reintroducing human representatives after discovering that complex issues require human empathy. Despite reducing staff in 2022, the company found customer satisfaction declined with AI handling. Klarna now adopts a hybrid approach, using AI for routine tasks while humans manage complex inquiries.
Klarna’s AI U-Turn: Why Human Empathy Trumps Automation in Customer Service
Written by Jaclyn Gibson

Klarna’s AI Pivot: A Return to Human Touch in Customer Service

In a significant strategic shift, Swedish fintech giant Klarna is scaling back its artificial intelligence initiatives in customer service, acknowledging that the human element remains crucial for maintaining customer satisfaction and loyalty.

According to Bloomberg, Klarna CEO Sebastian Siemiatkowski recently announced the company would reintroduce human representatives to handle customer inquiries after its ambitious AI deployment failed to deliver expected returns. “We’ve learned that while AI can handle many routine tasks efficiently, complex customer issues still benefit from human empathy and problem-solving skills,” Siemiatkowski stated.

This marks a notable reversal for Klarna, which had previously touted its AI investments as a cornerstone of its operational efficiency strategy. Fortune reports that Klarna had reduced its workforce by 700 employees in 2022, replacing many customer service functions with AI-powered chatbots and automated systems.

The company’s internal data revealed a troubling trend: customer satisfaction metrics declined as AI handled more complex service issues. “The ROI on pure AI-based customer service hasn’t materialized as we anticipated,” a senior Klarna executive told Finextra. “We’re now pursuing a hybrid approach that leverages AI for routine matters while routing complex issues to trained human representatives.”

Industry analysts see this as part of a broader reassessment of AI’s limitations in customer-facing roles. Greg Linden, a prominent tech commentator, noted on BlueSky that “companies are discovering that AI works best as an augmentation tool for human workers rather than a wholesale replacement.”

The timing of Klarna’s shift comes as the buy-now-pay-later (BNPL) sector faces increased regulatory scrutiny and growing competition. According to PYMNTS, maintaining strong customer relationships has become increasingly important for differentiation in the crowded BNPL market.

Yahoo Finance reports that Klarna isn’t abandoning AI entirely but is instead refining its application. The company continues to use machine learning for fraud detection, credit risk assessment, and initial customer query routing—areas where the technology has demonstrated clear value.

This recalibration reflects a maturing perspective on AI’s role in financial services. “The initial hype around AI replacing human workers has given way to a more nuanced understanding of where technology adds value and where human judgment remains essential,” noted a LinkedIn post from a financial technology consultant commenting on Klarna’s strategy shift.

The move aligns with trends in other technology sectors. Runtime News recently reported that database company Neo4j is similarly refocusing on performance and reliability rather than pursuing cutting-edge AI features that don’t address core customer needs.

For Klarna, which reported its first annual profit in four years in 2023, balancing technological innovation with customer experience is crucial to maintaining its growth trajectory. The company serves over 150 million users worldwide and partners with more than 500,000 merchants.

As one industry observer noted on Mastodon, “Klarna’s pivot isn’t an indictment of AI but rather a recognition that customer service requires a human touch that technology still can’t fully replicate.”

The company’s experience offers valuable lessons for the broader fintech industry as it navigates the promises and limitations of artificial intelligence in customer-facing applications.

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