As AI adoption becomes increasingly important to both organizations and individuals alike , understanding the difference between the types of AI solutions available becomes essential. The decision of opting for a broader and more ‘horizontal’ solution versus a niche ‘vertical’ one is of great strategic importance for all users.

Horizontal AI is AI that is generic and can be applied across multiple domains and use cases. The focus of Horizontal AI is mainly on the general capabilities such as language understanding, vision and automation. 

It is the “jack of all trades” and can adapt to various domains and tasks such as data analysis, content creation or customer support. Large Foundation Models(FMs) power horizontal AI systems (GPT 4 or Gemini) . Even LLMs , a type of FM are examples of horizontal AI. While horizontal AI systems might have a variety of uses, they lack the depth to perform complicated tasks and require oversight because of their poor accuracy. 

Given that Horizontal AI is broad by nature, they are built for and best at integrating into diverse environments via API’s or plugins, with operations requiring depth and expertise being left to Vertical AI systems. Productivity suites such as Copilot , Internal AI support tools and AI browser extensions and search engines are all examples of Horizontal AI systems.