North America dominated the market and accounted for over 36.8% share of global revenue in 2022

The global artificial intelligence market size was valued at USD 136.55 billion in 2022 and is projected to expand at a compound annual growth rate (CAGR) of 37.3% from 2023 to 2030. The continuous research and innovation directed by tech giants are driving the adoption of advanced technologies in industry verticals, such as automotive, healthcare, retail, finance, and manufacturing. For instance, in November 2020, Intel Corporation acquired Cnvrg.io, an Israeli company that develops and operates a platform for data scientists to build and run machine learning models, to boost its artificial intelligence business. Technology has always been an essential element for these industries, but artificial intelligence (AI) has brought technology to the center of organizations. For instance, from self-driving vehicles to crucial life-saving medical gear, AI is being infused virtually into every apparatus and program.

AI is proven to be a significant revolutionary element of the upcoming digital era. Tech giants like Amazon.com, Inc.; Google LLC; Apple Inc.; Facebook; International Business Machines Corporation; and Microsoft are investing significantly in the research and development of AI. These companies are working to make AI more accessible for enterprise use cases. Moreover, various companies adopt AI technology to provide a better customer experience. For instance, in March 2020, McDonald’s made its most significant tech investment of USD 300 million to acquire an AI start-up in Tel Aviv to provide a personalized customer experience using artificial intelligence.

The essential fact accelerating the rate of innovation in AI is accessibility to historical datasets. Since data storage and recovery have become more economical, healthcare institutions and government agencies build unstructured data accessible to the research domain. Researchers are getting access to rich datasets, from historic rain trends to clinical imaging. The next-generation computing architectures, with access to rich datasets, are encouraging information scientists and researchers to innovate faster.

Furthermore, progress in profound learning and ANN (Artificial Neural Networks) has also fueled the adoption of AI in several industries, such as aerospace, healthcare, manufacturing, and automotive. ANN works in recognizing similar patterns and helps in providing modified solutions. Tech companies like Google Maps have been adopting ANN to improve their route and work on the feedback received using the ANN. ANN is substituting conventional machine learning systems to evolve precise and accurate versions. For instance, recent advancements in computer vision technology, such as GAN (Generative Adversarial Networks) and SSD (Single Shot MultiBox Detector), have led to digital image processing techniques. For instance, images and videos taken in low light, or low resolution, can be transformed into HD quality by employing these techniques. The continuous research in computer vision has built the foundation for digital image processing in security & surveillance, healthcare, and transportation, among other sectors. Such emerging methods in machine learning are anticipated to alter the manner AI versions are trained and deployed.

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