AI is not a business model. It's usually just a component in a larger solution. You need to get a lot of other things right for AI to produce value, notably around the data you gather and pre-process. For most startups, that data is hard to access, and without it, their algorithms won't have much to train on.
While there are a few horizontal ML/AI/data science vendors, most AI is invisible, a component in some vertical solution, and consumed by people and businesses that don't really care how the results are produced, as long as it works.
Very few companies are good at applying AI across the board, like we see at Google, but the number of businesses using predictive models at least in some capacity is growing.
Horizontal means platforms, frameworks and tooling that are agnostic to the industry they're applied to.
Skymind is a machine-learning operations company (one of several): we help businesses train, deploy, monitor and update AI models. The same software is used by telecoms, finance, e-commerce and automotive companies -- horizontal.
There are countless vertical specific companies: e.g. Merlon applies ML to anti-money laundering.
While there are a few horizontal ML/AI/data science vendors, most AI is invisible, a component in some vertical solution, and consumed by people and businesses that don't really care how the results are produced, as long as it works.
Very few companies are good at applying AI across the board, like we see at Google, but the number of businesses using predictive models at least in some capacity is growing.