Artificial Intelligence (AI) Market Size, Share & Trends Analysis Report By Data Type (Image, Video, Text, Sound, Time Series, Point Cloud), By Solutions (Hardware, Software, Services), By Technology (Deep Learning, Machine Learning, NLP, Machine Vision), By End-User (Healthcare, BFSI, Law, Retail, Advertising and Media, Automotive and Transportation, Agriculture, Manufacturing) and By Region(North America, Europe, APAC, Middle East and Africa, LATAM) Forecasts, 2022-2030

Market Overview

The global artificial intelligence (AI) market size was valued at USD 92.7 billion in 2021. It is expected to reach USD 1596.86 billion by 2030, growing at a CAGR of 37.20% during the forecast period (2022–2030).

As opposed to the intelligence displayed by animals and humans, machines can demonstrate artificial intelligence (AI) by perceiving, synthesizing, and inferring information. The field of computer science known as artificial intelligence (AI) focuses on creating and managing tools that can make decisions and carry out tasks on behalf of people. Artificial intelligence algorithms are currently put to the test against intelligence benchmarks that are beyond the comprehension of humans, such as Al applications in quantum and supercomputers. It is anticipated that such developments in artificial intelligence technology will help the industry grow over the forecast period.

Market Dynamics

Global Artificial Intelligence (AI) Market Drivers

Growing Demand for High-Performance Products

Most companies that produce hardware parts like CPUs, ASICs, FPGAs, and GPUs are in the software sector now. FPGAs are now compatible with sophisticated software practices and available to those who organize and construct algorithm models thanks to recent trends in design tools. Artificial intelligence hardware-based solutions are now available to address issues with power consumption, sluggish processing, and inefficiency. Additionally, as the global artificial intelligence (AI) market matures, a new business model must be developed through predictive, effective automation and scalable parallel processing capabilities. The demand for lower power and higher performance in end-user applications led to the need for hardware-based artificial intelligence products. Very few businesses have developed these components over the past few years. However, vendors like IBM Corporation and Intel Corporation have begun producing artificial intelligence chipsets to achieve high performance in scaling dynamic processes concurrently to gain a competitive advantage.

Potential Research and Development into AI Systems

Layers of algorithms are used by artificial intelligence to process data, comprehend spoken language, and recognize objects visually. These algorithms are utilized for automated computation, reasoning, and data processing. The need to enhance these algorithms to offer better and more effective solutions for various end-use applications has grown. Traditional algorithms have shortcomings in terms of efficiency and accuracy. Artificial intelligence researchers are constantly working to improve algorithms for various applications.

Manufacturers and technology developers have turned their attention to creating standardized algorithms. For example, the traditional GPUs from NVIDIA used a machine-learning algorithm for voice recognition and image labeling. This approach needed help with accuracy and turnaround time. The company modified its algorithm by fusing big data and computational power to alter these dynamics. As a result, machines and devices now operate with greater accuracy, which is what is fueling the development of AI computing and artificial intelligence.

Global Artificial Intelligence (AI) Market Restraints

Substantial Amount of Demonstrative Data Needed

The need for a large amount of data to train AI systems for character and image recognition is one of the major issues limiting industry growth. Furthermore, the problem of data traceability is made worse by the stacking of such a large amount of data. Artificial intelligence is used by businesses like Facebook and Google, Inc. in image recognition applications, which need access to many data. In addition, the information required to identify tumors in X-rays is scarce in the healthcare industry. Making effective decisions with the help of available data is the main issue in artificial intelligence due to the lack of data availability. Additionally, the method of training networks with less data is still being developed and is anticipated to go commercial in the following 10 to 12 years. The lack of established standards for data collection and requirements is another issue with artificial intelligence.

Global Artificial Intelligence (AI) Market Opportunities

Growing Government Efforts and Investments to Use AI Technology

The government has boosted its investments in Al and related technologies due to their growing popularity and the ease with which they may be implemented. Governmental agencies, public sector organizations, and NGOs have started allocating funds for Al-based pilot programs for various applications, including traffic management, road and public safety, and digitization of government records. For instance, located in Hyderabad, INAI (Intel AI) was established in October 2020 thanks to a joint effort of the Telangana government, Intel India, the International Institute of Information Technology, Hyderabad (IIIT-H), and the Public Health Foundation of India (PHFI). The center will prioritize challenges in India's healthcare and smart mobility sectors.

Regional Analysis

By region, the global artificial intelligence (AI) market is segmented into North America, Europe, Asia-Pacific, South America, and the Middle East and Africa.

Asia-Pacific Dominates the Global Market

Asia-Pacific is the most significant shareholder in the global artificial intelligence (AI) market and is expected to grow at a CAGR of 49.3% during the forecast period. In this region, the use of artificial intelligence technology to secure financial and banking-related data has increased significantly. For instance, in September 2019, Microsoft researchers and the fund management company China Asset Management in China worked together to create an AI model. An enormous amount of real-time financial transaction data is analyzed by this AI model.

Additionally, a machine learning-based AI platform called KRTI 4.0 was provided by Infosys Limited, a leading provider of IT services in India. It enables wise decision-making at all organizational levels. KRTI 4.0 is intended to serve as an enterprise-wide decision-making support tool, facilitating the seamless transfer of lessons learned from one facility to the entire organization while speeding up the analytical knowledge.

North America is expected to grow at a CAGR of 33.20% during the forecast period. The frontiers of artificial intelligence applications are countries like the United States and Canada, which were early adopters in the North American market. Consumer trends like online shopping and the widespread use of digital devices with face and voice recognition will continue to fuel this region's growth. The market has been boosted by investments in North American businesses offering AI solutions and services. For instance, in August 2018, Scale Inc., a provider of API used by manufacturers of autonomous vehicles, announced that it had raised USD 18 million to train data obtained from companies like Embark and Lyft, Inc.

Ventures, Accel, and Index Y Combinator took the lead in the funding round. One of the most critical trends in the area is using AI for voice and speech recognition. For instance, the American AI company Globalme Localization Inc. gave the American audio company Sonos Inc. access to its dialect and accent audio collection. Sonos Inc. collected accent and speech data from three countries before integrating the smart home assistants with its wireless speakers. The organization was able to fine-tune its speech recognition engines and increase the quality of its customers' voice calls as a result of this integration. Virtual assistants in business scale and automate responses to back up claims, enhancing customer satisfaction and lowering costs. The region's expanding use of biometry enables the artificial intelligence market to expand into entirely new application areas.

Europe is expected to grow significantly over the forecast period. Business virtual assistants scale and automate responses to support claims, boosting client satisfaction and cutting costs. For instance, Vodafone Limited (U.K.) improved the customer experience by about 68% after introducing its chatbot, TOBi, for customer queries. The region's growing adoption of biometry paves the way for the market for artificial intelligence to grow into entirely new application fields. Additionally, the German Interior Minister announced a plan to implement biometric applications at 14 airports and 134 train stations in January 2020 to enhance security in Germany.

Brazil's security systems have been strengthened due to rising criminal activity, which encourages the use of AI applications. For instance, the Brazilian government installed 106 smart cameras in March 2020 all over Bahia and So Paulo to improve security, increase surveillance, and deter crime. The city of Sao Paulo has strategically placed drones, smart cameras, and a classification algorithm for real-time analysis.

The Middle East and African nations are implementing AI in asset and wealth management. For instance, the Israeli start-up Presenso provides cloud-hosted industrial asset predictive maintenance software. Machine learning techniques enable industrial manufacturers to find anomalies in their sensor data. Machine learning applications are required due to rising investments in the telecom and surveillance sectors. For the development of surveillance and telecommunications, several African nations, including Kenya and Uganda, have received funding and infrastructure from Chinese businesses, such as Huawei Technologies Co., Ltd. For border security in Turkey, about 30 locally produced drones with facial recognition and AI are in use.

Segmental Analysis

The global artificial intelligence (AI) market share is segmented by data type, solution, technology, and end-user.

Based on data type, the global artificial intelligence (AI) market is bifurcated into image, video, text, sound, time series, and point cloud.

The image segment is the highest contributor to the market and is expected to grow at a CAGR of 41.4% during the forecast period. AI-based software is used in healthcare to improve image acquisition support and provide an improvised image of a body part. Innovative diagnostic products with AI powering them have been introduced to the market, and they are anticipated to grow the segment's market share over the forecast period. For instance, Agfa Radiology Solutions announced the release of the SmartXR portfolio in 2020, which employs a distinctive combination of hardware and AI-powered software to give digital radiography (DR) equipment intelligence.

Based on the solution, the global AI market is bifurcated into hardware, software, and services.

The services segment owns the highest market share and is expected to grow at a CAGR of 49.2% during the forecast period. Installation, integration, maintenance, and support projects fall under artificial intelligence services. The launch of IBM Watson AIOps, newly added AI-powered services and capabilities, was announced by International Business Machines (IBM) Corporation in May 2020. These services are made for enterprise automation, increasing IT infrastructures' cost-effectiveness and resilience. The market for AI services is anticipated to grow due to the use of AI in customer service support.

The market for AI-based software is expanding due to careful advancements in data storage capacity, powerful computing, and parallel processing capabilities that deliver high-end AI software in dynamic end-user verticals. LogMeIn, Inc., a U.S.-based provider of SaaS (Software-as-a-Service) and cloud-based customer engagement, remote connectivity, and collaboration services, has seen a marked increase in new sign-ups across the board.

Based on technology, the global AI market is bifurcated into deep learning, machine learning, NLP, and machine vision.

The deep learning segment is the highest contributor to the market and is expected to grow at a CAGR of 36.8% during the forecast period. Deep learning presents profitable investment opportunities as it aids in overcoming the difficulties associated with large amounts of data. Many major tech companies are making strategic moves to increase their knowledge of deep learning technology. For instance, in December 2019, Intel Corporation purchased Israel-based deep learning company Habana Labs Ltd. Deep learning (neural network) tools provided by businesses like Ward Systems Group, Inc. and NeuroDimension, Inc. for training AI on various AI topics. Recurrent neural networks are also becoming increasingly popular for time series analysis and forecasting. A deep learning application is the recurrent neural network.

One of the most well-known business AI trends is automated machine learning. AutoML is used to carry out tiresome modeling tasks. For instance, after lots of repetition, Google LLC's AutoML achieved a high level of accuracy. Trending ML algorithms are used by many businesses to enhance decision-making procedures. All business intelligence platforms now have embedded analytics with integrated machine learning models. Additionally, Microsoft bought Semantic Machines, a startup focused on machine learning, in May 2018 to implement conversational AI for its Cortona smart assistant.

Based on end-user, the global AI market is bifurcated into healthcare, BFSI, law, retail, advertising and media, automotive and transportation, agriculture, and manufacturing.

The healthcare segment owns the highest market share and is expected to grow at a CAGR of 49.9% during the forecast period. The conversational AI platform is one of the most popular applications across all end uses. For instance, Google LLC introduced a Rapid Response Virtual Agent for call centers in April 2020. The diagnostics process has been transformed by image recognition in the healthcare industry. In addition, the U.K.-based AI company DeepMind created neural networks as accurate as medical professionals at diagnosing eye diseases. Viz.ai, Inc. had received FDA approval to analyze CT scans and alert medical professionals to patients who may have strokes. These factors are anticipated to drive the healthcare segment over the forecast period.

By projecting outcomes into the future and analyzing historical trends, AI aids banks and financial institutions detect anti-money laundering patterns and identify fraud. One of the significant trends that most financial institutions utilize is cognitive process automation. It makes it possible to automate financial services prone to errors, like claims management.

Recent Developments

• July 2022- AiCure, a company specializing in improving clinical trials through artificial intelligence (AI) and advanced data analytics, announced that the DHA PTSD-DT Program would use AiCure's AI platform in its post-traumatic stress disorder (PTSD) adaptive platform trial (APT) to compare the effectiveness of various PTSD treatments in both active-duty service members and veterans.
• August 2022- Atomwise, a pioneer in the application of artificial intelligence (AI) to the discovery of small molecule drugs, announced that it had formed an exclusive strategic research partnership with Sanofi. This partnership will use Atomwise's AtomNet platform for computational discovery and research of up to five drug targets.