General Purpose Software is Old News - Vertically-Integrated AI SaaS is Set to Take Over the Tech World

AI continues to conquer the tech world despite it being only months since ChatGPT impressed the world with its capabilities. Experts are already discussing vertical AI as the next logical iteration of vertical SaaS, opening up several new opportunities.

Vertical SaaS Revolutionized Tech World, Now it is AI’s Turn

Vertical SaaS (vSaaS) is already a game-changer in the tech world. Vertical-integrated software is just like any other vertically-integrated industry. The general idea is that you cover everything within a specific industry of task yourself so you don’t have to outsource anything.

The most popular example is Andrew Carnegie’s US Steel company that took over the entire industry when it was vertically integrated. No other company could beat US Steel’s prices so they were eventually driven out of the market.

Andrew Carnegie

Most software nowadays is built for a general audience to ensure it can sell to enough people. Now software companies are building ultra-specific vertically-integrated software to beat out all competitors in the specific field.

The technique simply creates superior products compared to general-purpose software.

Upon realizing how successful vertically-integrated software can be, even the largest horizontal tech firms decided to verticalize their products. Some examples include cloud giants like Azure, Amazon Web Services, and Google Cloud Platform.

Now, with the AI changing the tech world forever, the shift to vertical AI SaaS is a near certainty.

The experts are already discussing and building vertically-integrated AI platforms, bundled alongside workflow SaaS and built on top of models that have been uniquely trained using industry-specific datasets.

Three Layers of AI

While AI is developing and quite rapidly, at that, it is splitting into three separate layers — foundational models, AI infrastructure, and AI applications.

The first layer, the foundational models, are expected to become the bedrock of the entire AI stack. Several firms already emerged as leaders in the sector, including Cohere, Anthropic, and OpenAI itself.

Some companies focus on the infrastructure layer, while others are used for data generation, labeling, or training.

Then, there are foundational models and infrastructures that allow for countless AI business applications to emerge. Anyone can use AI-powered apps, they fit any industry, and they can accomplish a variety of tasks.

Experts predict that some of the AI applications will be bound to remain broadly horizontal, meaning that they will be useful to customers in any industry. AI in customer support is a good example of this. Another example includes digital assistants, copywriting apps, and AI-enabled search firms.

Most of the AI apps out today are great at a wide range of tasks. For example, AI image generators are already starting to shape the next era of entertainment and art.

Marvel’s Secret Invasion show was the first massive production to use AI-generated art to create its opening credits sequence.

However, many of the next generation of AI solutions will soon be vertical, meaning that they will be industry-focused and purpose-built to solve one task or one series of tasks.

This will be the most powerful AI-enhanced software applications as they will be incredibly fine-tuned to solve or complete their task extremely well and quickly.

AI-Native Apps vs Vertical SaaS Leaders

Experts suggest two opportunities here — new AI-native vertical applications and existing vertical SaaS leaders that will simply embed AI functionality.

However, despite the two emerging and growing side by side, experts believe that Vertical AI winners will ultimately be those who can access proprietary industry data and effectively train language models against the datasets.

The winner will also have to package the models via applications, deliver tremendous utility, and do all of it extremely quickly.

In the end, AI-native apps will have to fight vertical SaaS leaders in each industry individually until it is decided which one is better for each specific industry.

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