Klarna’s strategic pivot: from BNPL pioneer to data backbone of AI-powered shopping
Klarna, the Swedish fintech best known for its buy-now-pay-later (BNPL) services, is quietly repositioning itself for the next era of digital commerce — one powered not just by flexible payments, but by data and artificial intelligence. What began as a niche payment innovation has evolved into an ambitious bid to become the foundational data infrastructure for the emerging world of AI-driven shopping.
At the heart of this shift is Klarna’s Agentic Product Protocol, an initiative launched in December 2025 that reflects a broader strategic conviction: as artificial intelligence agents become the interface through which consumers discover and buy products, the structured data that underpins those agents will determine who wins in the next generation of commerce. Klarna’s protocol makes more than 100 million products — and their real-time prices and availability in 12 markets — instantly discoverable and interpretable by AI systems. This sets a de facto standard for how data is shared, discovered and consumed by autonomous shopping agents. Klarna Investors
In practical terms, the Agentic Product Protocol acts as a common language linking merchants, platforms and AI assistants. For merchants, the technical benefit is straightforward: they can “connect once” and have their entire catalogues surfaced across any AI-enabled shopping interface that supports the standard. For AI agents, the structured feed eliminates one of the biggest barriers to autonomous commerce — understanding what exists, at what price, and where it’s available — without the need for bespoke integrations or manual feeds. FStech
This move is not happening in a vacuum. Just weeks earlier, Klarna announced a strategic partnership with Google Cloud to integrate advanced generative AI capabilities into its shopping experience. By leveraging Google’s AI stack, Klarna can now generate dynamic “lookbooks,” create hyper-personalised marketing campaigns, and enhance its massive image library using next-generation models. Early pilots reportedly boosted order volume by approximately 50% and increased app engagement — metrics that underscore how AI can shift consumer behaviour when coupled with rich transaction and product data. PR Newswire
If one part of Klarna’s strategy is data aggregation and standardisation, another is AI-driven personalisation and execution. The company has long embedded AI into its products — from internal assistants that aid customer service and credit decisions to front-end recommendation engines that tailor the shopping experience to individual tastes. This aligns with broader trends in e-commerce: consumers increasingly expect experiences where products find them, rather than the other way around. PaymentsJournal
The aspiration to be the data backbone of AI commerce also ties neatly into Klarna’s IPO narrative and brand repositioning. Having filed for a US listing in 2025 with a target valuation around $20 billion, Klarna’s leadership has been keen to emphasize a broader commercial identity beyond BNPL. The company’s technology now facilitates millions of daily transactions, collects vast amounts of behavioural data on consumer preferences, and integrates shopping, payments and now AI discovery into a single platform. Digital Commerce 360
This strategy offers multiple commercial advantages. On the revenue side, Klarna’s data-rich environment is fertile ground for both personalised advertising and referral fees, complementing — and in some cases outstripping — its traditional payments business. Further, by providing AI agents with a structured, live catalogue of products across global markets, Klarna positions itself as the connective tissue between merchants and the next wave of autonomous commerce, irrespective of the frontend interface consumers ultimately use.
Perhaps most importantly, Klarna’s data-centric pivot reflects a larger shift in how digital ecosystems are likely to be architected in the AI age. In early internet commerce, platforms competed primarily on user base and transaction volume. In the AI era, data portability, real-time discovery and machine readability will increasingly define competitive advantage. Klarna’s protocol and partnerships signal an early bet on that future.
Whether this ambition fully materialises will depend on merchant adoption, interoperability between AI agents, and the evolution of consumer behaviour. But Klarna’s strategic choices of late — from open standards for product data to deep integration with generative AI — suggest it sees the future of shopping as less about discreet payments and more about data-powered, AI-orchestrated discovery and fulfilment.
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