Why AI Startups Cost More, Not Less to Build: Investor Insights From ET Soonicorns Summit

Contrary to the popular notion that artificial intelligence (AI) will make company building cheaper and faster, top venture capitalists are finding the opposite is true. According to insights from the recent ET Soonicorns Summit in Bengaluru, AI-native startups are proving to be more capital-intensive than their traditional counterparts, a reality driven by a few key factors.

One of the primary drivers of cost is the talent required to build foundational AI models. As Ritesh Banglani of Stellaris Venture Partners noted, building a business that requires hiring 20 PhDs in India is extremely difficult and expensive. This talent shortage at the foundational level creates a significant bottleneck and drives up salaries for highly specialized roles like data scientists, AI engineers, and researchers.

Beyond talent, the sheer cost of technology infrastructure is a major expense. AI startups rely heavily on cloud-based services to handle the intensive computational needs of training and deploying complex models. This includes everything from the cost of tokens on large language models (LLMs) to the use of powerful GPUs and data storage. These expenses can escalate quickly, especially as models and datasets grow in complexity and scale. In fact, for many AI companies today, a significant portion of their expenses goes directly to these infrastructure costs.

Furthermore, acquiring and processing high-quality data is another substantial financial burden. While foundation models have become more accessible, building a competitive advantage often requires proprietary, industry-specific data. This can involve purchasing expensive datasets, building custom data collection pipelines, and even manually labeling data to ensure accuracy and relevance.

Despite these high capital requirements, investor conviction remains strong. VCs are not shying away from AI; instead, they are looking for startups that can demonstrate a clear path to generating value. The focus has shifted from simple cost reduction to how AI can fundamentally improve business outcomes and increase business velocity. For founders, the message is clear: the AI wave is less about building a company on the cheap and more about fundamental business model innovation that is willing to invest in the core building blocks of the technology to create a defensible and valuable product.