Is AI eating software?
The phrase “AI is eating software” signals a monumental shift in how businesses approach software development and operations. AI systems are rapidly transforming, and in some cases, replacing traditional software. This echoes Marc Andreessen’s famous 2011 statement that “software is eating the world,” highlighting how software was at the heart of industry disruption. Now, AI is beginning to take over the roles that software once monopolized.
A Look Back: When Software Ate the World
When Andreessen said, “software is eating the world,” he was pointing to the massive transformation across industries — retail, media, entertainment, and more — that was driven by software innovation. Companies like Amazon, Netflix, and Spotify didn’t just revolutionize their sectors; they redefined them with software. These companies created platforms that scaled globally, unconstrained by the physical limitations of traditional business models.
This software-driven revolution was powered by advancements in computing, the internet’s growth, and easier access to development tools. Physical businesses — whether bookshops or record stores — were overtaken by digital platforms that offered global reach and scalability. Amazon, for example, didn’t just create an online bookstore. It built an infrastructure to sell practically anything.
AI Eats Software: A New Era of Disruption
Today, AI is pushing disruption even further, not just augmenting software but, in many cases, replacing it. Klarna’s use of AI to replace traditional SaaS tools, such as customer service systems and internal knowledge management, is a prime example of this shift. Klarna’s AI-driven platforms perform tasks previously handled by traditional software tools like Salesforce and Workday, suggesting that the need for such software could soon fade.
Just as Amazon transformed retail, AI is reshaping how software is built, used, and integrated. Systems like ChatGPT go beyond code generation; they deliver adaptive, context-aware solutions that can replace the need for separate applications.
Klarna’s AI-First Revolution
Klarna offers a preview of what an AI-first architecture looks like in practice. Rather than depending on external SaaS platforms like Salesforce, the company has developed AI-driven tools to manage key operations such as customer service, marketing, and legal processes.
One of the most notable examples is Klarna’s internal AI assistant, Kiki, which handles over 2,000 employee queries daily in just seconds, slashing the reliance on traditional knowledge management systems. Klarna’s AI-enhanced customer service has also cut response times from 11 minutes to under 2 minutes, showcasing AI’s potential for enhancing operational efficiency.
Understanding AI-First Architecture
An AI-first architecture represents a fundamental redesign of how systems are conceived and constructed. AI is no longer an add-on; it’s deeply integrated into the system, enabling dynamic, learning-based features that evolve with data.
Key aspects of an AI-first architecture include:
• Core Integration: AI drives essential functions and user interactions.
• Adaptive Design: These systems learn and adapt rather than follow rigid, pre-programmed instructions, adjusting to new contexts in real-time.
• Comprehensive Components: AI-first systems often incorporate a Cognitive API Layer for model integration, an Autonomous Agent Apps Layer for AI-to-API interactions, and Guardrails to optimize performance.
• Data-Centric Focus: AI-first architectures use data as fuel, continuously improving through a feedback loop.
Klarna’s AI-First Strategy in Action
Klarna’s AI-powered system touches nearly every department:
• Communications: Klarna uses AI to analyze media sentiment in real-time, allowing more accurate responses to public opinion. According to Filippa Bolz, Klarna’s head of communications, “The tool we’ve built using ChatGPT provides objective analysis within seconds, ensuring our messaging resonates with each audience.”
• Legal: Klarna’s legal department drafts contracts using ChatGPT, reducing what once took hours to mere minutes. Selma Bogren, Klarna’s senior managing legal counsel, notes, “ChatGPT allows me to tweak a generated contract in ten minutes instead of drafting from scratch.”
Challenges of AI-First Architecture
Despite its promise, an AI-first approach is not without challenges. Custom AI development requires significant upfront investment and a cultural shift within the organization. Employees need to be prepared to work alongside AI and fully leverage its capabilities. However, the long-term gains in productivity and cost efficiency make this approach increasingly appealing to businesses looking to maintain a competitive edge.
The Future of Enterprise Tech
Klarna’s transition to an AI-first architecture is a signal of what’s to come. As more companies realize AI’s potential to replace traditional software solutions, we may soon see AI-first become the standard in industries ranging from fintech to healthcare. In this future, AI doesn’t just assist with tasks; it becomes the driving force behind how businesses operate — smarter, faster, and more effectively.
This article fits well into a Medium audience, providing a high-level exploration of AI’s transformation of enterprise tech, while grounding the discussion with practical examples from Klarna’s experience. It resonates with both tech enthusiasts and business professionals by highlighting the disruptive potential of AI across various sectors.
