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2 days ago
By White Star Capital’s Early Growth Fund team
Notable Horizontal AI tools, such as ChatGPT and Github’s Copilot, have been widely adopted, with 96% of our White Star Capital’s portfolio already leveraging these technologies. Will we see the same market penetration as Vertical AI tools come to market?
As part of our research, we surveyed our 90+ portfolio to understand the opportunities, risks, and challenges for companies building Vertical AI solutions. The results of that survey are included throughout this deep dive.
What is Vertical AI?
While Horizontal AI excels in versatility, Vertical AI leverages deep, industry-specific knowledge to offer precise, tailored functionalities that address distinct challenges.
However, while Vertical AI’s precision holds great promise, its success hinges on solving clear, specific problems. Otherwise, implementing AI just for the sake of it, whether vertical or horizontal, can result in low engagement and underwhelming outcomes, a challenge many companies face today.
For example, customer service is a prime area for the adoption of vertical AI applications, lending itself to natural language processing and the pattern of automation of low-value work — 52% of portfolio companies surveyed have integrated AI tools for customer service.
The success of these models is dependent on the proprietary industry-specific data, as well as publicly available data, required to train them. An AI chatbot is only as effective as the quality of its training data. In customer service, high-quality data ensures accurate, relevant, and appropriate responses, enhancing customer satisfaction, increasing the product’s value, and strengthening brand loyalty.
The release of GPT-4 in March 2023 was a breakthrough with its enhanced accuracy and safeguards against hallucinations. But, it wasn’t ready for customer service “out of the box”.
Many companies are now building their own AI tools, and exploiting their datasets, to create tailored solutions that address specific industry challenges at scale (69% of our portfolio companies have built their own AI tools).
While building AI tools requires significant expertise and resources (successful AI applications rely on deep domain knowledge), the potential payoff is huge.
The Vertical AI advantage: why domain-specific models outperform horizontal approaches
The early days of AI were dominated by a ’horizontal’ strategy, with companies like Google, Amazon, IBM, and Microsoft creating broad AI solutions for various tasks. These Machine Learning as a Service (MLaaS) tools are like Swiss Army knives: versatile and capable of handling multiple tasks but not optimised for any specific one. They often act more as features than standalone products, easily integrated into existing platforms.