AI technologies

The current AI ecosystem consists of machine learning, robotics, artificial neural networks and natural language processing (NLP). In machine learning, programs learn from existing data and apply this knowledge to new data or use it to predict data. The field of robotics is concerned with developing and training robots. Usually, the ability of a robot to interact with people and the world follows general rules and is predictable. However, current efforts also revolve around using deep learning to train robots to act with a certain degree of self-awareness. For more on the AI ecosystem, trends, drivers, and applications, please take a look at the Statista In-depth Report: Artificial intelligence 2021.

AI investment and startups

The global artificial intelligence market, currently valued at 327.5 billion U.S. dollars, continues to grow driven by the influx of investments it receives. From 2015 to 2020, the total yearly corporate global investment in AI increased by 55 billion U.S. dollars, with much of it coming from private investments from U.S. companies. The most recent top funded artificial intelligence startups in the United States are that of UiPath, Nuro, and Indigo Ag to name a few. UiPath is the AI startup to watch, as it is considered the second most valuable AI unicorn startup worldwide at 35 billion U.S. dollars and has accomplished the designation of the most popular robotic process automation (RPA) product vendor across Global 2000 enterprises.

AI jobs and popular AI use cases

The increase in AI investment is coupled with an increase in the need for AI talent. Many companies have posted job opportunities for those with AI talent across IT departments as well as in other business areas. Additionally, many countries have seen their AI hiring rate increase over the past few years, with Brazil seeing the most at 3.4 times more AI-related occupations in 2020 compared to 2016. This increase in hiring AI talent goes hand in hand with the overall global increase in artificial intelligence and machine learning use cases throughout companies. Popular use cases for AI and machine learning include improving customer experience and generating customer insights. Given the increase in use cases, we can expect to see more of AI in the coming years.

This text provides general information. Statista assumes no liability for the information given being complete or correct. Due to varying update cycles, statistics can display more up-to-date data than referenced in the text.