AI Powered Software in 2025
An early hypothesis focused on data, depth, and distribution
Artificial Intelligence is on a path to disrupt tens of millions of cognitive dominant jobs, spanning a huge number of functions and industries. Currently, a common talking point among venture capitalists is that the value creation opportunity is the cost savings potential, with buyers generating labor savings and AI companies capturing 10%-20% of those savings.
This fails to capture the full story. While operational labor replacements will be a temporary value creation mechanism, AI point solutions will eventually compete against similar software offerings and have limited standalone moats. Competition (and subsequent margin compression) is accelerated by AI, as code generation enables rapid software development and replication.
Companies will need to deliver both lower costs and increased product quality to capture and maintain material take rates. AI that replaces labor can and will drive cost savings, but only those businesses that offer transcendent and differentiated product quality will build enduring moats. To achieve these outcomes, rapid feature/product expansion (beyond initial labor savings features) and the creation + usage of previously unusable/unavailable data will be required. With this data, the correct positioning in the value chain, and the features enabled by foundation models, companies will be able to drive incremental volume, revenue, and/or product margin, making their products an inextricable part of a customer’s business.
Therefore, we believe the largest opportunities exist in companies that focus on specific verticals where unique data can be combined with industry insights to deliver meaningfully better customer experiences. Even the best AI models generally do not contain the industry expertise or context necessary for the best outcomes. Vertical businesses can connect to legacy systems to extract and leverage existing data, drive downstream operations, and, over time, expand feature and product offerings that span the full value chain.
An example (that conveniently talks the Logos book) is Mia, which provides AI-powered automotive retail software. At first glance, Mia is a straightforward replacement of labor with its AI-powered customer service for automotive dealers. Alone, this first product solves a material labor and cost challenge for dealerships. Mia’s AI-powered customer service provides 24/7 coverage and connectivity to additional dealer systems that enable automated and seamless downstream operations including scheduling, test-drives, inventory management, service optimization, and financing administration. However, Mia sees these customer interactions as a wedge to capture customer data and build a machine deliver outbound customer communications that deliver high ROI customer retention and marketing interactions. Dealerships spend $500K+ annually1 on marketing across channels to refill the sales funnel due to low consumer retention rates (i.e. repeat purchase) of ~30%2. Successful delivery of these services can make Mia an invaluable part of the full dealer value chain and can transform both the processes and economics of consumer acquisition and retention.
This perspective is not in keeping with the historical outcomes of software. Total software market capitalization in the United States is $6T+3, with the top fifteen vertical software businesses only comprising ~$300B (<5%)4. IT budgets in most industries are <10% of revenue5, with vertical SaaS spend (where applicable) often <1% of customer revenue. As software replaces headcount, we expect to see material expansion of IT budgets driven by vertical software offerings.
The shift toward vertical AI businesses—those that leverage unique industry data to create differentiated, deeply embedded products—will redefine traditional IT budget constraints and significantly expand the total addressable market for software. Identifying these businesses early, as they transform operational economics, is central to our investing approach.
CapitalIQ.