Artificial Intelligence (AI) Market

The global artificial intelligence market size was valued at USD 150.2 billion in 2023 and is expected to grow at a CAGR of 36.8% from 2023 to 2030. The revenue forecast for 2030 is projected to reach $1,345.2 billion. The base year for estimation is 2022, and the historical data spans from 2023 to 2030.

Artificial intelligence (AI) is revolutionizing multiple industries, positioning itself as a key driver for emerging technologies such as big data analytics, robotics, and the Internet of Things (IoT). Furthermore, the rise of generative AI tools such as ChatGPT and AI art generators highlights its mainstream prominence. With its continued trajectory, AI is set to persist as a powerful technological innovator, propelling advancements in the foreseeable future.

Technology Roadmap of Artificial Intelligence till 2030

The artificial intelligence market report covers technology roadmap till 2030, with insights around short-term, mid-term, and long-term developments.

Short-term roadmap (2023-2025)

• Advancements in generative models for content creation.
• Growing Adoption of Federated Learning for Privacy-Preserving Distributed Model Training.
• Advancing transparency and interpretability through Explainable AI methods in decision-making.
• Edge AI gains traction with decentralized Al processing and decision-making.

Mid-term roadmap (2025-2028)

• Sophisticated Generative AI models boost quality and diversity.
• Advancements in federated optimization algorithms and secure aggregation methods boost scalability and performance of federated learning systems.
• Explainable AI will enhance the interpretability and transparency of AI models.
• Edge AI will become more sophisticated, leveraging advanced hardware and algorithms.

Long-term roadmap (2028-2030)

• Al-generated content reaches human-level sophistication, redefining artificial and human creativity.
• Wide deployment of federated learning empowers secure and scalable solutions across industries.
• Explainable AI emerges as a fundamental requirement for AI systems in all industries.
• Advanced AI processing on edge devices for autonomous decision-making, real-time intelligence, and efficient data processing in diverse environments.

Business Models of Artificial Intelligence Market

The artificial intelligence market report covers business models in artificial intelligence market, with insights around various AI-based business model innovations.

AI SaaS Product Vendor

• Develop and maintain AI applications and services that address specific use cases or industries.
• Offers scalable and accessible platform where customers leverage AI capabilities without the need for extensive technical expertise.

AI Platform Vendor

• Offer a suite of tools, frameworks, and services that support the entire AI development lifecycle.
• Enable developers and organizations to leverage the platform's capabilities to build and deploy AI models at scale.

AI Licensing and Intellectual Property Vendor

• Involves the development, licensing, and monetization of AI technologies and intellectual property assets.
• Leverages intellectual property assets to generate revenue and drive innovation in the Artificial Intelligence Market.

AI Technical Consulting Vendor

• Offer a range of services, including AI strategy development, implementation planning, algorithm design, and model deployment.
• Bridges the gap between AI expertise and client requirements, enabling successful AI adoption.

AI Management Consulting Vendor

• Offer expertise in organizational readiness assessment, business process optimization, and AI implementation roadmaps.
• Aims to drive organizational transformation and maximize the value of AI investments.

AI Research and Development Vendor

• Invest in R&D efforts to explore novel algorithms, models, and applications.
• Aims to drive innovation and shape the future of AI technologies.

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Artificial Intelligence Market Growth Dynamics

Driver: Growth in the adoption of autonomous artificial intelligence

The increasing adoption of autonomous artificial intelligence (AI) is driving the growth of the Artificial Intelligence Market. This trend is fueled by advancements in algorithms, machine learning techniques, and natural language processing, enabling the development of sophisticated autonomous AI systems. These systems offer improved accuracy and reliability, attracting organizations from various industries. Autonomous AI optimizes operations, leading to cost savings and enhanced productivity. It finds applications in healthcare, finance, manufacturing, transportation, and retail sectors. The cost reduction associated with autonomous AI, driven by automation, further drives its adoption. As technology advances and more industries recognize its benefits, the Artificial Intelligence (AI) Market size is poised for expansion, fostering innovation and new opportunities.

Restraint: Issues related with data availability and quality

Data availability and quality play a crucial role in restraining the growth of the Artificial Intelligence Market. Limited data availability, particularly in niche industries or specialized domains, hinders the development and application of AI solutions. Without access to comprehensive and diverse datasets, AI algorithms lack the necessary training to make accurate predictions and decisions. Moreover, the quality of data is vital for the effectiveness of AI systems. Inaccurate, incomplete, or biased data leads to flawed outcomes and unreliable AI models. Ensuring data quality requires meticulous data cleaning, preprocessing, and validation processes, which are time-consuming and resource-intensive. Organizations with limited resources struggle to meet these requirements, hindering the development and deployment of AI solutions. To address these issues, it is important to promote data sharing collaborations, invest in data collection and preprocessing capabilities, and establish industry-wide standards for data quality and privacy. These efforts will enhance data availability, improve data quality, and create a more conducive environment for the growth of the Artificial Intelligence (AI) Market.

Opportunity: Rapid growth in the digital data form various sources

The exponential growth of digital data from various sources presents immense opportunities for the AI market. With the proliferation of connected devices, social media platforms, online transactions, and sensors, an unprecedented volume of data is generated every day. This abundance of data offers a vast and diverse resource for AI algorithms to leverage. AI thrives on data, and the availability of large and diverse datasets enables AI systems to learn, analyze, and make accurate predictions. The more data available, the better AI algorithms understand patterns, trends, and correlations. This empowers businesses and organizations to gain valuable insights, make data-driven decisions, and drive innovation. For instance, in marketing, AI algorithms analyze extensive customer data to identify preferences, personalize campaigns, and improve engagement. In healthcare, AI analyzes patient data to identify early signs of diseases, provide personalized treatment plans, and enhance patient care. Furthermore, the growth of digital data fuels the development of AI technologies and solutions. The increasing availability of data spurs investment in AI research and development, leading to advancements in algorithms, machine learning models, and data processing techniques.

Challenge: Concerns related to inaccurately and bias generated output

Issues related to bias and inaccurately generated output pose significant challenges to the growth of the AI market. When AI algorithms are biased or trained on biased data, they perpetuate discriminatory practices or reinforce societal prejudices. For instance, biased facial recognition systems have exhibited higher error rates for women and people with darker skin tones, leading to potential misidentification and discrimination. Such biases erode trust and hinder the adoption of AI technologies, particularly in sensitive areas such as hiring, law enforcement, and healthcare. Moreover, inaccurately generated output from AI systems has serious consequences. For instance, in the healthcare sector, if an AI system inaccurately diagnoses a medical condition or recommends incorrect treatments, it poses risks to patients' health and safety. Such incidents undermine confidence in AI and slow down its adoption. Addressing these challenges requires ongoing efforts to detect and mitigate bias in AI algorithms, improve data quality, and enhance the accuracy and transparency of Artificial Intelligence Market systems to build trust and ensure responsible AI deployment.

Artificial Intelligence Market Ecosystem

The artificial intelligence market report covers market ecosystem which comprises software provider, service provider, cloud provider, hardware and devices provider, network provider, and security provider.

The computer vision segment is expected to grow at the highest CAGR during the forecast period

Based on technology, the artificial intelligence market is segmented into Machine Learning, Natural Language Processing, Context-Aware, and Computer Vision. Computer vision enables innovation in various domains, including self-driving cars, facial recognition, and augmented reality. It enhances consumer experiences, reduces costs, and strengthens security. Manufacturers detect defects, insurance assessors evaluate vehicle damage, medical professionals analyze medical images, and banks verify customer identities using computer vision applications. Its wide-ranging impact across industries demonstrates its significance in driving technological advancements. As a result, the computer vision technology is anticipated to grow at the highest CAGR during the forecast period.

North America to account for the largest market size during the forecast period

North America has emerged as a leading hub for artificial intelligence (AI) adoption, with significant developments and applications across various sectors. The region's favorable ecosystem, coupled with collaborations between academia, industry, and government, has created a fertile ground for AI research, development, and commercialization. As a result, North America continues to be at the forefront of Artificial Intelligence Market adoption, driving technological advancements and shaping the future of AI applications.

Key Market Players

The artificial intelligence market providers have implemented various types of organic and inorganic growth strategies, such as new product launches, product upgradations, partnerships and agreements, business expansions, and mergers and acquisitions to strengthen their offerings in the market. The major players in the artificial intelligence market include Google (US), Microsoft (US), IBM (US), Oracle (US), AWS (US), Intel (US), Salesforce (US), SAP (Germany), Cisco (US), Meta (US), HPE (US), Siemens (Germany), Huawei (China), NVIDIA (US), Baidu (China), SAS Institute (US), OpenAI (US), H2O.ai (US), iFLYTEK (China), Alibaba Cloud (China), General Vision (US), Darktrace (UK), Blackberry Limited (Canada), DiDi Global (China), Face++ (China), Inbenta (US), Anju Software (US), Butterfly Network (US), Atomwise (US), AIBrain (US), SK Hynix (South Korea), Progress (US), PrecisionHawk (US), AgEagle Aerial System (US), Neurala (US), Twitter (US), Aurea Software (US), Persado (US), 8x8 (US), Appier (Taiwan), GumGum (US), IPRO (US), Graphcore (UK), Preferred Networks (Japan), Applied Brain Research (Canada), Pilot AI (US), Iris Automation (US), Gamaya (Switzerland), ec2ce (Spain), Descartes Labs (US), Mythic (US), Ada (Canada), Mostly AI (Austria), Sentient.io (Singapore), Lumen5 (Canada), AI Superior (Germany), Fosfor (India), Intrinsic (US), Jasper (US), Soundful (US), Writesonic (US), One AI (Israel).

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Scope of the Report

This research report categorizes the artificial intelligence market based on component, type, infrastructure type, deployment type, organization size, vertical, and region.

By Offering:

• Hardware
  • Accelerators
  • Processors
    • Microprocessing Unit
    • Graphics Processing Unit
    • Field Programmable Gate Arrays
    • Other Processors
  • Memory
  • Network
• Software
  • By Type
    • Pre-trained Models
    • Customizable AI
    • Edge AI
    •  AI Marketplaces
  • By Deployment
    • Cloud
    • On-Premises
• Services
  • Professional Services
    • Consulting Services
      • Training  & Education
      • Designing & Testing
    • Deployment and Integration
    • Support and Maintenance
  • Managed Services

Artificial Intelligence Market By Technology:

• Machine Learning
  • Deep Learning
    • Convolutional Neural Networks (CNN)
    • Recurrent Neural Networks (RNN)
    • Generative Adversarial Networks (GAN)
    • Transformers
      • GPT 1
      • GPT 2
      • GPT 3
      • GPT 4
    • Large Language Models (LLMs)
  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement Learning
• NLP
  • Natural Language Understanding (NLU)
  • Natural Language Generation (NLG)
• Context awareness
• Computer Vision

By Business Function:

• Finance
• Security
• Human Resources
• Law
• Marketing and sales
• Operations
• Supply Chain Management

Artificial Intelligence Market By Verticals:

• BFSI
• Retail & Ecommerce
• Automotive, Transportation and Logistics
• Government & Defense
• Healthcare & Life Sciences
• Telecom
• Energy & Utilities
• Manufacturing
• Agriculture
• IT/ITeS
• Media & Entertainment
• Other Verticals (Construction, Education, and Travel & Hospitality)

By Region:

• North America
  • US
  • Canada
• Europe
  • UK
  • Germany
  • France
  • Italy
  • Spain
  • Nordic
  • Balkans
  • Rest of Europe
• Asia Pacific
  • China
  • India
  • South Korea
  • ANZ
  • Japan
  • ASEAN
  • Rest of Asia Pacific
• Middle East and Africa
  • KSA
  • Israel
  • Egypt
  • UAE
  • South Africa
  • Rest of Middle East & Africa
• Latin America
  • Brazil
  • Mexico
  • Argentina
  • Central America
  • Rest of Latin America

Recent Developments in Artificial Intelligence Market:

• In May 2023,  Google announced the launch of two new AI powered solutions named Target and Lead Identification Suite, and Multiomics Suite for the life sciences industry, aimed at expediting drug discovery and precision medicine for biotech companies, pharmaceutical firms, and public sector organizations.
• In May 2023, HPE announced an enhancement to its HPE Ezmeral Software platform. HPE Ezmeral Software expands the data and analytics capabilities of HPE GreenLake, extending from the edge to the cloud. It serves as the foundation for machine learning (ML) and artificial intelligence (AI) initiatives, providing the necessary infrastructure and tools for data processing and analysis.
• In April 2023, IBM unveiled its new security suite named IBM Security QRadar Suite, which is designed to unify and boost the security analyst experience throughout the whole incident lifecycle. The IBM Security QRadar Suite represents a significant evolution and expansion of the QRadar brand, encompassing all fundamental threat detection, investigation, and response capabilities.  It has a single, updated user interface for all products that is integrated with cutting-edge AI and automation to enable analysts to work more quickly, effectively, and precisely across their main toolsets.
• In March 2023, Cisco has announced a number of new AI-powered innovations for its Webex collaboration platform. These innovations are designed to help organizations create more engaging and productive hybrid work experiences.
• In September 2022, SAP introduced recent improvements to the SAP SuccessFactors HXM Suite that bring together data, machine learning and artificial intelligence (AI) to provide organizations with a better understanding of the capabilities within their workforce.

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