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Artificial Intelligence Market Worth $1,345.2 billion by 2030, Growing at a CAGR of 36.8% Report by MarketsandMarkets™

MarketsandMarkets Research Pvt. Ltd.
MarketsandMarkets Research Pvt. Ltd.

As per the report by MarketsandMarkets, the global Artificial Intelligence Market size is projected to reach USD 1,345.2 billion by 2030, at a CAGR of 36.8% during the forecast period, 2023-2030

Chicago, Aug. 17, 2023 (GLOBE NEWSWIRE) -- The global Artificial Intelligence Market size to grow from USD 150.2 billion in 2023 to USD 1,345.2 billion by 2030, at a Compound Annual Growth Rate (CAGR) of 36.8% during the forecast period, according to a new report by MarketsandMarkets™. The growth of the artificial intelligence market is propelled by its synergistic interaction with various other technologies. The advancements in computing power, including the development of high-performance processors and GPUs, enable the efficient processing of complex AI algorithms. Additionally, the proliferation of big data and advancements in data storage technologies provide the necessary fuel for training and improving AI models. Moreover, the growth of cloud computing infrastructure and the availability of AI-as-a-Service platforms make artificial intelligence more accessible to businesses of all sizes, facilitating rapid adoption and implementation.

Browse in-depth TOC on "Artificial Intelligence Market"

538 - Tables
74 - Figures
624 - Pages

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Scope of the Report

Report Metrics

Details

Market size value in 2023

USD 150.2 billion

Market size value in 2030

USD 1,345.2 billion

Growth rate

CAGR of 36.8%

Market size available for years

2017–2030

Base year considered

2022

Forecast period

2023–2030

Forecast units

Value (USD) Billion

Segments Covered

Offering, Technology, Business Function, Verticals, and Region

Geographies Covered

North America, Europe, Asia Pacific, Middle East & Africa, and Latin America

Companies Covered

Some of the significant Artificial Intelligence (AI) Market vendors are Google (US), Microsoft (US), IBM (US), Oracle (US), AWS (US), Intel (US) and many more.

Furthermore, the convergence of artificial intelligence with other transformative technologies such as the Internet of Things (IoT), robotics, natural language processing (NLP), and computer vision enhances artificial intelligence capabilities and expands its application areas. These synergistic relationships between artificial intelligence and other technologies create a virtuous cycle, driving innovation and fueling the overall growth of the artificial intelligence market.

By verticals, the artificial market has been divided into retail & eCommerce, BFSI, Government & Defense, Healthcare & Life Sciences, Telecom, Energy & Utilities, Manufacturing, Agriculture, IT/ITeS, Media & Entertainment, Automotive, Transportation and Logistics and other verticals (Construction, education, and travel and hospitality). Artificial Intelligence is at the forefront of driving advancements and delivering numerous benefits across various sectors, revolutionizing processes, increasing efficiency, and fostering innovation. In healthcare & life sciences, artificial intelligence plays a crucial role in enhancing diagnostic accuracy, enabling personalized medicine, and facilitating drug discovery. The finance industry leverages AI-powered algorithms to improve risk assessment, detect fraud more effectively, and enhance customer service. Retail & eCommerce utilizes artificial intelligence for demand forecasting, personalized marketing strategies, and optimizing supply chain operations. The automotive sector undergoes a remarkable transformation with artificial intelligence, utilizing autonomous vehicles, advanced driver assistance systems, and predictive maintenance capabilities. These instances highlight the wide-ranging impact of artificial intelligence across sectors, driving positive change and unlocking new possibilities.

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By business function, the artificial intelligence market has been divided into finance, security, Human Resources, marketing and sales, operations, supply chain management and law. Artificial Intelligence is making a significant impact across these functions, revolutionizing traditional processes and introducing innovative solutions. In marketing and sales, AI-powered algorithms analyze vast amounts of data to identify customer preferences and behaviors, enabling personalized targeting and enhanced customer experiences. AI-driven chatbots automate customer support, providing quick and efficient responses. Operations and supply chain management benefit from AI's predictive capabilities, optimizing inventory management, demand forecasting, and logistics. AI's data analysis and pattern recognition abilities also enhance risk management and fraud detection, improving security in BFSI sector. In Human Resources, artificial intelligence streamlines recruitment processes, automates repetitive tasks, and assists in employee training and development. As businesses continue to embrace AI, it becomes a critical driver of efficiency, innovation, and competitive advantage across various functions, reshaping the way companies operate and deliver value.

The artificial intelligence market, by offering, has been segmented into hardware, software, and services. The hardware market has been further segmented into Accelerators, Processors, Memory, and Network. The different types of processors considered in this report are Microprocessor Units (Microprocessing Units), Graphics Processing Units (Graphics Processing Units s), Field-programmable Gate Arrays (Field Programmable Gate Arrays), and other processors (ASIC, DSP, IPU, and VPU). The increasing demand for AI applications and the need for faster processing speeds are driving the development of AI hardware. Factors such as the growing volume of data, complex neural networks, and the need for real-time processing are pushing the development of specialized hardware. The AI market for software has been further segmented into By type and By deployment. The by type is further bifurcated into Pre-trained Models, Customizable AI, Edge AI, AI Marketplaces. The by deployment segment is further bifurcated into Cloud, and On-premises. The service market has been classified into professional services and managed services.

The artificial intelligence market, by technology, has been segmented into Machine Learning, NLP, Context Awareness, and Computer Vision. The Machine learning segment is further bifurcated into Deep Learning, Supervised Learning, Unsupervised Learning, and Reinforcement Learning. The deep learning is further segmented into Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Generative Adversarial Networks (GAN), Transformers, and Large Language Models (LLMs). The transformers are further bifurcated into GPT 1, GPT 2, GPT 3, and GPT 4. The NLP segment is divide into Natural Language Understanding (NLU) and Natural Language Generation (NLG). This section discusses the AI market size and the growth trends across various technologies.

The artificial intelligence market has been segmented into five geographic regions: North America, Europe, Asia Pacific, Middle East and Africa, and Latin America. Among these regions, Asia Pacific is expected to grow at the highest CAGR during the forecast period. Governments and businesses in countries such as China, Japan, and South Korea are actively investing in AI research and development, fostering an environment conducive to artificial intelligence innovation. Also, industries such as healthcare, finance, retail, and automotive are adopting AI solutions for enhanced efficiency, customer experience, and decision-making.

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Top Trends in Global Artificial Intelligence (AI) Market

The global Artificial Intelligence (AI) Market is growing rapidly, and there are a number of key trends that are driving this growth. Some of the top trends in the global Artificial Intelligence (AI) Market include:

  • As AI technology advances, ethical issues are becoming increasingly important. In order to address bias, transparency, fairness, and accountability in AI systems, organisations are concentrating more and more on responsible AI practises. To direct the use of ethical AI, industry guidelines and regulatory entities are forming.

  • The automation of numerous jobs and procedures across businesses is greatly aided by AI. Businesses may streamline operations, cut costs, and increase efficiency by automating repetitive processes and workflows thanks to robotic process automation (RPA) and artificial intelligence (AI) capabilities.

  • Significant AI adoption is occurring in the healthcare industry for activities including patient data analysis, medication discovery, personalised therapy recommendations, and medical imaging analysis. Medical practitioners are being helped in their decision-making by AI-powered diagnostic tools and predictive analytics.

  • The banking sector keeps using AI for fraud detection, algorithmic trading, risk assessment, chatbots for customer support, and credit scoring. To increase forecast accuracy and decision-making, AI-powered computers analyse enormous volumes of financial data.

  • Chatbots and virtual assistants are just two examples of the advanced NLP technologies. They are able to discern subtleties in human language and respond accordingly, which improves customer service and interaction.

  • AI and edge computing work together to bring data processing and analysis closer to the data source, cutting latency and enabling real-time decision-making. IoT devices and driverless vehicles stand to benefit especially from this.

  • The industrial industry is embracing AI-driven supply chain optimisation, predictive maintenance, and quality control. AI aids in the discovery of trends, outliers, and potential for manufacturing process optimisation.

  • Through personalised learning experiences, automated grading, intelligent tutoring systems, and adaptive material distribution, AI is revolutionising the educational landscape. It improves educational outcomes while accommodating various learning styles and velocities.

  • Realistic images, movies, and even text are produced using AI-driven generative models like transformers and GANs (Generative Adversarial Networks). Applications for these models can be found in design, entertainment, and content development.

  • Governments and regulatory agencies are paying more attention to creating policies and rules for AI development and application. The three main areas of concern are ensuring data privacy, eliminating bias, and upholding openness.

  • Demand is surpassing supply for AI specialists with knowledge of machine learning, data science, and AI ethics. To close the AI skills gap, organisations are spending money on employee training and upskilling.

  • AI is being developed to work with humans, not to replace them. AI-powered solutions help professionals make decisions by enhancing their skills and knowledge.

Key Industry Development

The Artificial Intelligence (AI) Market is constantly evolving, with new technologies and solutions emerging all the time. Here are some of the key industry developments that are shaping the market:

  • Convolutional neural networks (CNNs) and transformer models, two deep learning techniques, have made significant advances in a number of AI applications, including speech recognition, image identification, and natural language processing (NLP). The precision and capability of AI systems have increased as a result of these developments.

  • AI computations are now faster and more effective because to the development of specialised processors for the field, such as graphics processing units (GPUs) and application-specific integrated circuits (ASICs). Real-time AI application deployment and the training of complex AI models require this hardware acceleration.

  • The ethical aspects of developing AI have received more attention from the AI community. To prevent unfavourable social effects, this entails eliminating biases in algorithms, guaranteeing transparency and explainability, and adhering to responsible AI practises.

  • Around the world, regulatory organisations and governments have been putting frameworks in place to control the creation and use of AI. These rules cover data protection, accountability, transparency, and responsible usage of AI technologies.

  • AI's usage in healthcare was hastened by the COVID-19 pandemic. AI has been employed in the creation of vaccines, the discovery of drugs, the analysis of diagnostic imaging, the monitoring of patients, and the prognostication of disease outbreaks.

  • The OpenAI-developed GPT-3 gained notoriety for its capacity for language production. It demonstrated the capability of large-scale language models to carry out a range of functions, from producing text that resembles human speech to powering chatbots and virtual assistants.

  • Autonomous vehicle technology has advanced significantly in recent years. In order to improve road safety and alter transportation, AI algorithms are being used for perception, decision-making, and navigation.

  • Businesses are using AI more and more to give customers individualised experiences. By providing personalised information and help, chatbots and recommendation engines driven by AI increase client engagement.

  • AI is being used to quickly identify and address cybersecurity risks. To find abnormalities and probable breaches, machine learning algorithms analyse patterns in network behaviour and traffic.

  • AI is essential to the financial sector's fraud detection, algorithmic trading, credit scoring, and risk assessment processes. To create predictions and judgements that are based on data, AI models analyse enormous volumes of data.

  • AI computations could be considerably accelerated by quantum computing, which would allow for the solution of challenging issues that are currently beyond the capabilities of conventional computers. The intersection of AI and quantum computing is a growing area of research.

  • Massive databases are being analysed by AI to find prospective medication candidates and forecast their efficacy, revolutionising the drug discovery process. This method shortens the drug development process' timeframe and lowers expenses.

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