Artificial Intelligence (AI) Market by Offering (Hardware, Software), Technology (ML (Deep Learning (LLM, Transformers (GPT 1, 2, 3, 4)), NLP, Computer Vision), Business Function, Vertical, and Region – Global Forecast 2024 – 2029

OVERVIEW

1. Introduction to the AI Market

Artificial Intelligence (AI) has emerged as a transformative technology, significantly impacting various industries, including healthcare, automotive, finance, retail, and more. AI technologies like machine learning (ML), natural language processing (NLP), computer vision, and robotics are reshaping business processes, enhancing decision-making, and improving operational efficiency. The AI market has experienced rapid growth over the past decade, driven by increased data availability, advances in computing power, and growing demand for intelligent solutions.

The global AI market is expected to grow at a robust CAGR (Compound Annual Growth Rate) over the forecast period, driven by technological advancements, increased adoption of AI-powered solutions, and significant investments in AI research and development. This comprehensive report provides a detailed analysis of the AI market, including market dynamics, segmentation, regional insights, competitive landscape, and future trends.

2. Market Dynamics

The Artificial Intelligence (AI) Market, valued at USD 279.22 billion in 2024, is projected to expand significantly at a CAGR of 37.1% from 2024 to 2030, reaching an estimated USD 1,811.75 billion by the end of the forecast period. This robust growth is driven by ongoing research and innovation from leading tech companies, which are accelerating the integration of advanced AI technologies across various industry sectors, including automotive, healthcare, retail, finance, and manufacturing.

For example, in December 2023, Google LLC unveiled its latest advancement, the ‘Gemini’ large language AI model. Gemini is available in three distinct versions: Gemini Nano, Gemini Pro, and Gemini Ultra. Notably, Gemini distinguishes itself from other models with its native multimodal capabilities, which enable it to process and integrate multiple types of data, setting a new benchmark in AI technology..

Market Drivers

– Technological Advancements: Rapid advancements in AI technologies, such as deep learning, neural networks, and natural language processing, are enhancing the capabilities of AI solutions, leading to increased adoption across various sectors.

– Increased Data Availability: The proliferation of data from various sources, including IoT devices, social media, and digital transactions, provides a fertile ground for AI algorithms to learn and improve, driving market growth.

– Growing Adoption in Diverse Industries: Industries such as healthcare, finance, retail, and automotive are increasingly adopting AI technologies to improve customer experience, optimize operations, and enhance decision-making processes.

– Government Initiatives and Investments: Governments worldwide are investing heavily in AI research and development to gain a competitive edge in the global AI race. For example, China and the U.S. have launched significant initiatives to advance AI capabilities.

Market Restraints

– High Implementation Costs: The cost of deploying AI solutions, particularly in SMEs, can be prohibitive due to the need for specialized hardware, software, and skilled personnel.

– Data Privacy and Security Concerns: AI applications often require access to large datasets, which raises concerns regarding data privacy and security. Regulatory frameworks like GDPR in Europe impose stringent requirements that can hinder AI adoption.

– Lack of Skilled Workforce: There is a significant shortage of skilled AI professionals, such as data scientists and AI engineers, which can slow down the development and deployment of AI solutions.

Market Opportunities

– Integration with Emerging Technologies: The integration of AI with other emerging technologies, such as IoT, blockchain, and edge computing, presents significant growth opportunities. For example, AI-powered IoT devices can enable real-time data analysis and decision-making.

– Expansion in Emerging Markets: Emerging markets in Asia-Pacific, Latin America, and the Middle East offer untapped potential for AI adoption, driven by digital transformation initiatives and growing technology adoption.

– Personalization and Customer Experience: AI’s ability to analyze vast amounts of data and provide personalized recommendations creates opportunities in sectors like retail, healthcare, and finance, where customer experience is critical.

Market Challenges

– Ethical and Bias Issues: AI algorithms can inadvertently perpetuate biases present in training data, leading to ethical concerns and biased decision-making. Addressing these issues is crucial for broader AI adoption.

– Regulatory and Compliance Issues: Navigating the complex regulatory landscape is a significant challenge for AI companies. Compliance with data protection laws, such as GDPR, requires robust data management practices.

– Integration with Legacy Systems: Many organizations face challenges in integrating AI solutions with existing legacy systems, which can be costly and time-consuming.

3. Market Segmentation Analysis

Understanding the AI market’s segmentation is vital for identifying growth opportunities and strategic planning. The market can be segmented based on technology, application, deployment mode, and end-user.

By Technology

– Machine Learning (ML): ML, a subset of AI, is the most widely adopted AI technology, used for predictive analytics, recommendation engines, fraud detection, and more. The growing need for data-driven insights and predictive modeling drives the demand for ML solutions.

– Natural Language Processing (NLP): NLP technology is used for text and speech recognition, sentiment analysis, and language translation. Its adoption is driven by the growing demand for chatbots, virtual assistants, and customer support automation.

– Computer Vision: Computer vision technology is widely used in industries such as automotive (autonomous vehicles), healthcare (medical imaging), and retail (automated checkout). Advancements in deep learning and image processing are driving its growth.

– Robotics Process Automation (RPA): RPA uses AI to automate repetitive tasks and processes, reducing costs and increasing efficiency. Its adoption is growing in industries such as manufacturing, finance, and healthcare.

– Others (Speech Recognition, Expert Systems): Other AI technologies, such as speech recognition and expert systems, are also gaining traction in specific applications, such as virtual assistants and decision support systems.

By Application

– Healthcare: AI is transforming healthcare by enabling precision medicine, improving diagnostic accuracy, and enhancing patient care through AI-powered tools and solutions.

– Automotive: The automotive industry leverages AI for autonomous driving, advanced driver assistance systems (ADAS), predictive maintenance, and in-vehicle personal assistants.

– Finance: AI is widely used in the finance sector for fraud detection, risk management, algorithmic trading, and customer service automation.

– Retail: AI helps retailers enhance customer experience through personalized recommendations, inventory management, and demand forecasting.

– Manufacturing: AI-powered predictive maintenance, quality control, and supply chain optimization are some applications transforming the manufacturing sector.

– Others (Education, Energy, Agriculture): AI is also being adopted in education for personalized learning, in energy for smart grid management, and in agriculture for precision farming.

By Deployment Mode

– Cloud-Based: Cloud-based AI solutions are gaining popularity due to their scalability, flexibility, and cost-effectiveness. These solutions enable organizations to access advanced AI capabilities without significant upfront investments in infrastructure.

– On-Premise: On-premise AI solutions offer better control over data and security, making them suitable for industries with stringent data protection requirements, such as finance and healthcare.

By End-User

– Small and Medium Enterprises (SMEs): SMEs are increasingly adopting AI to enhance their competitiveness, improve customer service, and optimize operations.

– Large Enterprises: Large enterprises are leveraging AI for digital transformation, optimizing business processes, and gaining a competitive edge through innovative AI-driven solutions.

4. Regional Insights

North America

North America dominates the global AI market, primarily due to its technological advancements, robust R&D ecosystem, and the presence of leading AI companies. The U.S., as a major hub for AI innovation, benefits from substantial investments by tech giants such as Google, Microsoft, and IBM, driving significant growth. The region is supported by various government initiatives aimed at fostering AI research and development, including funding programs and policy frameworks that promote innovation and integration across multiple sectors.

 Europe

Europe plays a crucial role in the global AI market, spurred by increasing adoption of AI technologies in industries like healthcare, automotive, and finance. The European Union’s emphasis on ethical AI and stringent data protection regulations, such as the General Data Protection Regulation (GDPR), shapes the market’s trajectory. Key European nations, including the UK, Germany, and France, are spearheading AI integration and research, supported by both public and private sector investments aimed at enhancing AI capabilities and applications.

Asia-Pacific

The Asia-Pacific region is witnessing swift growth in the AI market, driven by rapid digital transformation, supportive government policies, and the presence of major AI players in countries like China, Japan, and India. China, in particular, is a significant driver of regional growth, with extensive investments in AI research and development. The country’s strategic focus on becoming a global AI leader, combined with advancements in technology and increasing adoption of AI across various sectors, propels the overall market expansion in this dynamic region.

Latin America

Latin America is emerging as a promising market for AI, with increasing adoption in sectors such as finance, retail, and healthcare. Countries like Brazil and Mexico are at the forefront of this growth, driven by digital transformation initiatives and a rising awareness of AI’s potential benefits. The region’s evolving tech ecosystem, coupled with investments in AI infrastructure and applications, is fostering innovation and enabling businesses to leverage AI for improved efficiency and competitive advantage.

Middle East & Africa

The Middle East & Africa region is experiencing gradual but notable AI adoption, supported by government-led initiatives and smart city projects. Countries like the UAE and Saudi Arabia are leading the way, making substantial investments in AI research and development to drive economic diversification and technological innovation. The focus on building AI capabilities and infrastructure is gradually transforming the region’s market landscape, paving the way for increased AI integration across various sectors and contributing to long-term growth.

5. Competitive Landscape

The global AI market is highly competitive, with numerous players competing for market share. This section provides an overview of the competitive landscape, highlighting key players, their strategies, and recent developments.

Key Players Overview

– Google LLC: Google’s AI expertise places it at the forefront of artificial intelligence research, allowing the company to offer a wide array of AI-powered solutions. Key offerings include Google AI, TensorFlow, and advanced AI-based cloud services, which support a wide array of applications from natural language processing to machine learning. The company’s commitment to innovation is evident in its continuous efforts to integrate cutting-edge AI capabilities across its product portfolio, driving advancements in technology and user experience.

– Microsoft Corporation: Microsoft AI is a major force in the artificial intelligence sector, offering a broad spectrum of solutions through its Azure AI platform, Cognitive Services, and developer tools. The company is dedicated to advancing AI technology while emphasizing responsible AI practices, including fairness and transparency. Microsoft’s focus on AI-driven digital transformation supports businesses in leveraging AI for enhanced operational efficiency, innovation, and competitive advantage, underscoring its commitment to ethical AI development and deployment.

– IBM Corporation: IBM’s AI platform, Watson, is a prominent player in the artificial intelligence landscape, renowned for its capabilities in predictive analytics, natural language processing, and machine learning. Leveraging Watson, IBM delivers enterprise-grade AI solutions tailored to various industries, including healthcare, finance, and retail. The company places a strong emphasis on data privacy and security, ensuring that its AI technologies uphold stringent standards for protecting sensitive information while driving innovation and operational excellence.

– Amazon Web Services (AWS): AWS in AI provides a robust suite of services through its cloud platform, encompassing machine learning, natural language processing (NLP), and computer vision. By offering these advanced tools, AWS aims to democratize AI, making it accessible to developers and businesses of all sizes. The company’s approach emphasizes scalability and ease of integration, enabling organizations to leverage AI capabilities efficiently and cost-effectively, regardless of their size or industry sector.

– NVIDIA Corporation: NVIDIA in AI stands as a top provider of hardware, renowned for its high-performance GPUs and AI-optimized data center solutions. The company is a pioneer in AI research and development, driving advancements in AI computing and deep learning technologies. NVIDIA’s innovations support a wide range of applications, from deep learning models to complex data processing, establishing it as a critical player in the AI hardware and software ecosystem.

– Intel Corporation: Intel in AI delivers a broad range of hardware and software solutions, featuring AI-optimized processors and advanced deep learning frameworks. The company is dedicated to pushing the boundaries of AI technology, facilitating AI-driven innovation across multiple industries. By enhancing its hardware capabilities and developing robust software tools, Intel supports a variety of applications, from edge computing to large-scale data processing, positioning itself as a key enabler of AI advancements.

Recent Developments

– OpenAI’s Project Q-Star: OpenAI is developing an innovative artificial general intelligence (AGI) model code-named Project Q-Star. This model is expected to have a profound impact on the AI market, potentially leading to breakthroughs in technology interactions, process automation, and addressing some of the world’s most pressing issues.

– Microsoft and NVIDIA Collaboration (March 2024): In March 2024, Microsoft and NVIDIA announced a strategic collaboration aimed at advancing AI in the healthcare and life sciences sectors. The partnership combines Microsoft Azure’s cloud infrastructure and advanced computing capabilities with NVIDIA’s DGX Cloud and Clara suite, with the goal of accelerating innovation and enhancing patient care through advancements in clinical research and drug discovery.

– NVIDIA Generative AI Microservices (March 2024): NVIDIA launched new Generative AI Microservices in March 2024, designed to advance medical technology (MedTech), drug discovery, and digital health. These microservices utilize AI to potentially enhance healthcare technology.

– Google Lumiere Model (January 2024): In January 2024, Google unveiled Lumiere, a new AI model that functions as a text-to-video diffusion tool. Lumiere is capable of generating short video clips from text descriptions and can animate still images or apply specific styles to video creation.

– Google Gemini LLM (December 2023): Google LLC released Gemini, a new large language model (LLM) in December 2023. Gemini is available in three versions: Nano, Pro, and Ultra. A notable feature of Gemini is its ability to handle multiple modalities, setting it apart from other competing LLMs.

– University of Cambridge and Partners – AI Supercomputer ‘Dawn Phase 1’ (November 2023): In November 2023, the University of Cambridge, along with Intel Corporation and Dell Technologies, announced the implementation of the AI supercomputer ‘Dawn Phase 1’. This cutting-edge supercomputer merges high-performance computing (HPC) with AI to address some of the world’s most critical challenges, aiming to boost technology leadership and investment in the UK technology sector.

– Enlitic Curie Platform (March 2023): Enlitic introduced the latest release of the Enlitic Curie platform in March 2023. This platform simplifies workflow management for radiology departments and includes Curie|ENDEX, which uses NLP and computer vision for medical image analysis, and Curie ENCOG, which leverages AI to safeguard Protected Health Information.

– AMD Instinct MI300 Series (June 2023): AMD unveiled its AI Platform strategy in June 2023, featuring the AMD Instinct MI300 Series accelerator family. This includes the AMD Instinct MI300X accelerator, developed for training and inference of large language models and generative AI workloads.

– IBM and Wimbledon (June 2023): IBM announced a partnership with The All England Lawn Tennis Club for the 2023 Wimbledon Championship in June 2023. IBM Watsonx’s generative AI technology will be used to produce video commentary highlights and provide AI Draw Analysis for insights into player draws.

– H20.ai and GeoTechnologies Partnership (April 2023): In April 2023, H20.ai formed a strategic partnership with GeoTechnologies, a Japan-based provider of map data and location solutions. The partnership uses H20.ai’s H2O AI Cloud to develop an AI-powered platform for assessing sidewalk safety using onboard camera footage.

– Iris.ai EIC Accelerator Funding (January 2023): Iris.ai announced in January 2023 that it received the EIC Accelerator Blended finance, which is the EIC’s flagship startup funding program. The funding includes a €2.4 million grant and up to €12 million in investments from the EIC and the European Investment Grant.

– AiCure Clinical Site Services Program (September 2022): AiCure launched its clinical site services program in September 2022, providing data-driven, actionable insights to minimize research risks and optimize workflow by partnering with sponsors and research sites.

– Atomwise and Sanofi Collaboration (August 2022): In August 2022, Atomwise entered an exclusive strategic research collaboration with Sanofi for AI-powered drug discovery. The partnership involves using Atomwise’s AtomNet platform for the computational discovery and research of up to five drug targets.

– Francisco Partners Acquires IBM Watson Health (June 2022): Francisco Partners acquired the healthcare analytics and data assets from IBM’s Watson Health division in June 2022. The newly formed standalone company, named Merative, organizes its products into six categories.

– Sensely and Keralty S.A.S Partnership (April 2022): In April 2022, Sensely and Keralty S.A.S, along with its American affiliate Sanitas USA, Inc., announced a multi-year partnership. This collaboration aims to enhance the next-gen mySanitas application using Sensely’s advanced visual UI and multilingual symptom assessment tool.

6. Future Trends and Opportunities

Increasing AI Adoption in SMEs

The trend of AI adoption among small and medium-sized enterprises (SMEs) is gaining momentum as these businesses recognize the benefits of integrating AI technologies into their operations. Unlike large enterprises that have traditionally led AI adoption, SMEs are now finding AI solutions more accessible and cost-effective. This shift is fueled by advancements in cloud computing and AI-as-a-Service (AIaaS) offerings, which provide scalable and affordable AI tools. SMEs are leveraging AI for various applications, including process automation, enhanced customer engagement, and gaining a competitive edge in the market. This democratization of AI is transforming how smaller businesses operate, making advanced technologies available to a broader audience.

Expansion of AI in Emerging Markets

Emerging markets, particularly in regions such as Asia-Pacific, Latin America, and the Middle East, present substantial growth opportunities for AI technology. These regions are undergoing rapid digital transformation driven by favorable government policies, increased internet connectivity, and a surge in technology adoption. Investments in infrastructure and innovation are accelerating AI integration in these markets, which are adopting AI solutions to drive economic development, enhance public services, and improve quality of life. As these markets continue to evolve, they are becoming key players in the global AI landscape, contributing significantly to the industry’s expansion.

Integration of AI with IoT and Edge Computing

The convergence of AI with the Internet of Things (IoT) and edge computing is poised to revolutionize various industries. AI-powered IoT devices, which can analyze and process data in real-time, are enhancing operational efficiency and decision-making processes across sectors. The integration with edge computing allows data to be processed closer to the source, reducing latency and enabling quicker responses to emerging situations. This synergy facilitates smarter and more responsive systems, from industrial automation to smart cities, driving further growth and innovation in the AI market.

Rise of AI in Healthcare

AI’s role in healthcare is rapidly expanding, driven by the sector’s need for advanced technologies to improve patient outcomes and operational efficiency. AI applications in healthcare include predictive analytics for disease prevention, diagnostic tools that enhance accuracy, and virtual health assistants that provide personalized care. The use of AI is transforming healthcare delivery by enabling more precise and efficient treatments, reducing costs, and enhancing patient engagement. As AI technology continues to advance, its impact on healthcare is expected to grow, addressing complex medical challenges and improving overall care.

Ethical AI and Responsible AI Practices

With the widespread adoption of AI, there is a heightened focus on ethical and responsible AI practices. Organizations are increasingly prioritizing transparency, fairness, and accountability in their AI systems to address concerns about bias and misuse. This includes implementing measures to ensure that AI algorithms are fair and do not perpetuate discrimination, and establishing governance frameworks to oversee AI development and deployment. The emphasis on ethical AI practices is shaping the future of AI technology, ensuring that its benefits are realized in a manner that aligns with societal values and expectations.

AI in Autonomous Vehicles

The automotive industry is experiencing a transformative shift toward autonomous vehicles, largely driven by advancements in AI technology. AI systems in autonomous vehicles process vast amounts of data from sensors, cameras, and other sources to make real-time driving decisions, enhancing safety and efficiency on the road. This technological evolution is accelerating the development of self-driving cars, which are expected to revolutionize transportation by reducing human error, optimizing traffic flow, and providing new mobility solutions. The growing demand for autonomous vehicles is a significant driver of AI adoption in the automotive sector, paving the way for a future of smarter and safer transportation.

7.  Artificial Intelligence Market Report Overview

8. Global Artificial Intelligence Market Report Segmentation

This report provides a comprehensive forecast of revenue growth across global, regional, and country levels and analyzes the latest industry trends within various sub-segments from 2017 to 2030. According to Grand View Research, the global artificial intelligence market is segmented into the following categories:

Solution Outlook (Revenue, USD Billion, 2017 – 2030)

• Hardware

  • Accelerators

  • Processors

  • Memory

  • Network

• Software

• Services

  • Professional

  • Managed

Technology Outlook (Revenue, USD Billion, 2017 – 2030)

  • Deep Learning

  • Machine Learning

  • Natural Language Processing (NLP)

  • Machine Vision

  • Generative AI

Function Outlook (Revenue, USD Billion, 2017 – 2030)

  • Cybersecurity

  • Finance and Accounting

  • Human Resource Management

  • Legal and Compliance

  • Operations

  • Sales and Marketing

  • Supply Chain Management

End-use Outlook (Revenue, USD Billion, 2017 – 2030)

 • 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

Regional Outlook (Revenue, USD Billion, 2017 – 2030)

• North America

  • U.S.

  • Canada

• Europe

  • U.K.

  • Germany

  • France

• Asia Pacific

  • China

  • Japan

  • India

  • South Korea

  • Australia

• South America

  • Brazil

  • Mexico

• Middle East and Africa (MEA)

  • Saudi Arabia (KSA)

  • UAE

  • South Africa

Frequently Asked Questions