We are living through a technological revolution that is redefining the foundations of enterprise software: artificial intelligence (AI).

In recent years, tech giants like Microsoft, Amazon, and Google have invested billions of dollars in integrating AI into their products, aiming to enhance productivity while reducing costs. In this context, Klarna, the Swedish fintech, is making a bold move by abandoning standard commercial tools like Salesforce and Workday to build its own AI-powered internal systems.

Is this strategy the future of enterprise software or an excessively high-risk gamble?

The Rise of AI in Business: An Unstoppable Trend

The integration of AI into internal systems is not an isolated phenomenon. According to a McKinsey report, companies that have adopted AI comprehensively have reported a 20% improvement in process efficiency and a 30% reduction in operational costs.

The global AI market is projected to reach $407 billion by 2027, reflecting the magnitude of this trend. Companies like Microsoft and Amazon are already demonstrating the impact of this technology. For instance, Microsoft has recorded a 70% increase in software development productivity thanks to its AI-powered GitHub Copilot platform. Amazon, for its part, has achieved savings of up to $700 million by using AI to optimize and refactor its code.

More than 60% of large companies globally are implementing AI in at least one internal process, and that number is expected to grow rapidly in the coming years. In the financial sector alone, Goldman Sachs estimates that the mass adoption of AI could generate up to $500 billion in annual savings.

The trend is clear: AI is not just a competitive advantage; it is a necessity for staying relevant in the global market.

Klarna and the AI-Powered Internal Software Approach

Klarna is no stranger to disruption. Its “buy now, pay later” model transformed the e-commerce industry, and now the company is channeling that innovative spirit into its internal systems.

Klarna has decided to build its own software instead of continuing to use commercial solutions like Salesforce and Workday.

After successfully automating two-thirds of its customer service inquiries with AI, the fintech is betting that it can replicate that success in other internal areas.

The rationale behind this decision is clear: the cost of developing internal software with AI is decreasing, and the potential benefits are substantial. Rather than spending tens of millions of dollars on annual licenses, Klarna believes it can create tailored solutions that not only save costs but also optimize its processes in ways that standard commercial software cannot.

Is the Break-Even Point Closer Than It Seems?

The cost of commercial software solutions can be astronomical. For companies the size of Klarna, software expenses over a decade can easily exceed $100 million. However, with the declining costs of software production and data storage, the break-even point for developing internal solutions is closer than ever. According to consultancy Gartner, the cost of software development has decreased by about 30% over the past five years, while the cost of data storage has fallen by more than 60%.

This means that companies like Klarna are in a unique position to take advantage of this environment. With an annual budget of $10 million, Klarna could build a highly sophisticated AI-powered CRM, something that would traditionally have required a much larger budget. This type of investment is comparable to financing a startup with a Series A round of $20-30 million, but with the advantage that Klarna already has a clear use case and an established customer base.

The Risk of Building vs. Buying

Of course, Klarna’s strategy is not without risks. Developing and maintaining internal systems is a costly process that requires a talented engineering team and ongoing investment.

Many companies that have attempted to develop their own software have ended up reverting to commercial solutions after incurring enormous development and maintenance costs. Even large companies like IBM have struggled to maintain their internal systems long-term without resorting to external vendors.

However, Klarna appears to be ready to take on this challenge. The company has demonstrated in the past that it is not afraid to make risky decisions if it believes they can provide long-term advantages.

And if they succeed, the rewards could be significant: a fully customized internal infrastructure that provides a competitive edge that other competitors will find difficult to replicate.

A New Paradigm in Enterprise Software?

If Klarna succeeds in developing an AI-based internal infrastructure, we could be witnessing the birth of a new paradigm in enterprise software. Instead of relying on standardized commercial solutions, Klarna could establish a model based on data lakes, AI, and custom software that could revolutionize not only the fintech sector but also other industries.

Companies like Microsoft, Amazon, and Google have already demonstrated that AI can radically transform productivity. Microsoft and ServiceNow have reported productivity improvements of between 50% and 70%, and Amazon has optimized its development costs by hundreds of millions of dollars thanks to AI. Klarna, with its focus on automation and personalization, could be the next company to show how AI can redefine the way large organizations operate.

Final Reflection

Klarna’s bet on AI is risky, but the potential rewards are enormous.

If they can develop internal software that outperforms commercial solutions, they will not only save millions of dollars but also create a sustainable competitive advantage in a constantly evolving market.

In an environment where technology and data costs continue to decline, the possibility of Klarna transforming its operations with AI is closer than ever. And if they succeed, they could be the example that many other companies will follow in the coming years.

The future of enterprise software is no longer in generic commercial solutions. It lies in the customization enabled by AI. Klarna knows this, and they are betting everything on it.