AI (Artificial Intelligence) copywriting platform writerbuddy.ai has released the results of a study looking at investment into AI. The company analysed over 10,000 AI companies and their funding data between 2015 and 2023, using data from CrunchBase, NetBase Quid, S&P Capital IQ, and NFX.
It found that corporate AI investment has risen consistently to the tune of billions. Investment soared from $12.75bn (£10.3bn) in 2015, to $93.5bn in 2021, a 633.33 per cent increase over the six-year period.
If you compare the change from 2020 to 2021 with the previous three years, where AI investment remained almost consistent, it’s clear that the 2020 pandemic accelerated this growth.
Although there was a slight drop in investment volumes in 2018, there has been a recurring boost in investment volumes every year since then. And as consulting firms like McKinsey and Delloite continue to fuel the digital transformation craze and AI becomes more accessible, the firm said it expects more investors to fund AI-focused/machine learning operations (MLOps) startups.
The rise of Open AI
The incredible rise of Open AI dominates AI funding. OpenAI leads the pack with over $11bn amassed since its inception, while all the other companies received a combined funding of about $3bn. However, all 10 of the most-funded MLOps startups each received over $100m in funding.
The next best-funded AI startup was Anthropic. It was founded by OpenAI’s former employees, who aimed to develop more human-like and safe AI. The company raised $1bn in funding in three rounds. Google is its most recent investor, having sunk $300m into the company. Scale AI, data annotation platform that provides high-quality data to train AI models, has raised $602.6m, with the most recent investment round amassing $117m, to support 15 AI projects.
Other AI firms that have attracted significant investment include Anyscale, a computing platform that simplifies the development, deployment, and management of Ray applications at scale ($259m); Inflection AI, which enables developers to train AI models without sharing that data with anyone ($225m); and Weights & Biases, which created a developer-first MLOps platform that offers performance visualisation tools for machine learning ($200m).