In this hyper competitive age, adopting AI is something individuals and organizations alike are prioritizing in order to increase efficiency and productivity. While everyday users might find general purpose Horizontal AI applications more useful given how versatile they are,  the real value for enterprises lies in specialized ‘vertical’ AI systems.

Vertical AI systems are solutions built from the ground up for specific industries and domains. They understand the unique nuances of the industry they are designed for . They are linked to specific facts and are ‘grounded’ to the truths of the industry to prevent them from making generalist errors. 

AI systems that analyze tissue samples and radiological scans and perform diagnosis (healthcare), tools that perform legal due diligence against specific case law and regulations(law) , applications that scan transactions in real time to flag frauds (finance) are all examples of Vertical AI systems in action.  

This specialization comes at a price though. Vertical AI systems are more expensive in terms of both monetary cost and  in terms of the time taken to build them. In a shift that seems inevitable, organizations are adopting Agentic Vertical AI – agents that ‘know’ and can ‘do’ tasks and execute complex operations. to stay competitive .