Can AI agents outsmart SaaS?
For nearly two decades, SaaS has been the go-to for businesses seeking efficiency and reduced IT overhead, driving the global SaaS spend from $31B in 2015 to ~$250B this year. But AI agents are reshuffling the deck.
🤜🏻 Klarna’s AI push
One striking example is Klarna’s decision to abandon major SaaS vendors, including Salesforce and Workday, to build its own AI-powered systems. Using OpenAI’s enterprise ChatGPT, Klarna automates tasks that used to require entire teams or SaaS solutions. Its AI-driven customer service assistant replaced 700 employees and handled 2.3 million interactions in its first month. AI offers a lifeline to profitability to a company trying to claw back from a $1B loss in 2022 (down to $32M in H1 2024).
SaaS pioneers are taking notice too. At Dreamforce 2024, Salesforce introduced Agentforce, a move from "human-in-the-loop" to “human-at-the-helm”, with autonomous agents capable of managing customer interactions independently. These bots seamlessly integrate data across Salesforce’s unified platform.
⛽️ The new efficiency paradigm: people-light, systems-light, data-smart
A trend is emerging: businesses will be people-light, systems-light, and data-smart. Organizations are not just looking to automate tasks; they’re aiming to consolidate data, eliminate costs and redundancy, and increase agility. According to Bettercloud’s State of SaaS Ops 2024 report, organizations now use an average of 112 different SaaS tools, down from 130 last year - a first-time decline.
Startups will have more options to embrace modular, low-code platforms to compose AI-driven workflows handling specific tasks. In fintech, AI-powered platforms that dynamically adjust credit risk in real-time can slash the need for third-party solutions.
📊 Three Implications for Startups Operations
While this shift won’t happen overnight, startups should rethink their approach to product architecture, operations, and human capital. This transition also calls for capital solutions that support lean, right-sized growth.
- Data-centric solutions: startups must architect their solutions around data. Capturing, securing, and processing data intelligently is a competitive edge.
- Operational efficiency: startups must increase operational efficiency while keeping costs down. AI/LLM agents and modular platforms can provide agility without the cost of complex systems.
- Human expertise still matters: AI won’t replace human insight and creativity. In fact, with the right AI tools, employees can deliver not just products but better business outcomes—turning the human touch into a new differentiator.
In short: businesses and startups should reimagine their product and operational strategy around data, efficiency, and the right capital solutions to sustain growth. The companies that thrive will be the ones that move beyond automating tasks to re-engineering entire workflows, making them smarter, leaner, and more human-centered.