ARE YOU A PARK OR GARDEN?
Imagine for, a moment, a large public park. It offers a wide variety of plants and flowers, and is enjoyed by a wide range of people looking to enjoy some time outdoors and perhaps learn a bit about the most popular trees and animals. But the soil is fairly average, capable of growing the most common plants but more difficult terrain that can’t develop more exotic or specialized species. Yes, it caters to the biggest audience, but the park is simply not capable of providing the specific nutrients or attracting the right pollinators for each type of plant.
The park in many ways is like Generative AI. It can grow, but it’s not as robust or targeted as some categories need to utilize specialized data and inputs.
Now imagine a garden. It may be smaller in scale, but it contains the rarest, most nutrient-rich soil, and a vast network of bees and butterflies that help pollinate the plants. The garden flourishes quickly because it has both the best resources and best helpers, tailored specifically to the needs of each plant species. The garden can deliver more beautiful flowers and fruit because it has been developed specifically to serve that purpose.
The garden, of course, is Vertical AI. These intelligence systems excel in specific domains by leveraging specialized knowledge and relationships to deliver highly targeted and effective solutions that Generative AI systems can’t deliver.
HOW TO MAKE VERTICAL AI WORK
The travel industry, for example, is highly specialized and uses specific language and data that generative AI systems struggle to understand. Vertical AI systems, on the other hand, are designed to enhance productivity in specific sectors by understanding industry-specific jargon and terminology in ways that more general tools can’t.
That gives Vertical AI a significant advantage, and is why so many customers choose cloud-based solutions (Software as a Service) instead of their own enterprise solutions. However, there are significant challenges to building a successful, cost-efficient Vertical AI that can be scaled quickly and efficiently:
- THE COST (AND QUALITY) OF DATA: High-quality, consistent data is obviously essential. Most companies need to invest in outside, third-party data sources that are prohibitively expensive or difficult to obtain.
- CUSTOMER ACQUISITION: The costs of acquiring customers ready and willing to engage with new AI platforms is also a major cost consideration.
The winners in Vertical AI need to find ways to solve these two challenges, or face enormous costs that will present obstacles to profitable growth. Companies with access to extensive data and established customer relationships are at an enormous advantage, as they can minimize the massive data and customer acquisition costs at launch, allowing them to scale their Vertical AI platforms quickly and profitably.
With Vertical AI, there is so much to be learned, but even more to be excited about. In the travel category alone, there are huge opportunities in areas like price prediction, data mapping, fintech, and advertising technologies that can revolutionize the industry. Travel data platforms must dedicate themselves to growing a true and bountiful garden of AI-driven solutions, one nourished by the rarest soil (data) and tended by the most dedicated pollinators (customers). For Vertical AI platforms to succeed, every bloom needs to tell a story of precision, care and unparalleled growth.
