Artificial Intelligence Market (By Solution; By Technology: Deep Learning, Machine Learning; By End-use) - Global Industry Analysis, Size, Share, Growth, Trends, Revenue, Regional Outlook and Forecast 2023-2032

The global artificial intelligence market was surpassed at USD 136.58 billion in 2022 and is expected to hit around USD 3,261.05 billion by 2032, growing at a CAGR of 37.34% from 2023 to 2032.

Key Pointers

• Software solutions led the market and accounted for more than 36.74% of the global revenue in 2022. This high percentage can be attributed to prudent advances in information storage capacity, high computing power, and parallel processing capabilities to deliver high-end services.
• On the back of its growing prominence because of its complicated data-driven applications, including text/content or speech recognition, the deep learning segment led the market and accounted for around 36.41% share of the global revenue in 2022.
• The advertising & media segment led the market and accounted for more than 19.54% of the global revenue share in 2022. This high share is attributable to the growing AI marketing applications with significant traction.
• North America dominated the market and accounted for over 36.87% share of global revenue in 2022. This high share is attributable to favorable government initiatives to encourage the adoption of artificial intelligence (AI) across various industries. 
• The regional market in Asia Pacific is anticipated to witness significant growth in the artificial intelligence market. This growth owes to the significantly increasing investments in artificial intelligence.

Report Scope of the Artificial Intelligence Market

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.

Artificial Intelligence Market Segmentations:

By Solution

• Hardware
• Software
• Services

By Technology

• Deep Learning
• Machine Learning
• Natural Language Processing (NLP)
• Machine Vision

By End-use 

• Healthcare
  • Robot-Assisted Surgery
  • Virtual Nursing Assistants
  • Hospital Workflow Management
  • Dosage Error Reduction
  • Clinical Trial Participant Identifier
  • Preliminary Diagnosis
  • Automated Image Diagnosis
• BFSI
  • Risk Assessment
  • Financial Analysis/Research
  • Investment/Portfolio Management
  • Others
• Law
• Retail
• Advertising & Media
• Automotive & Transportation
• Agriculture
• Manufacturing
• Others