[199 Pages Report] The Artificial Intelligence in Computer Vision Market size was estimated at USD 10.21 billion in 2023 and expected to reach USD 12.56 billion in 2024, at a CAGR 24.02% to reach USD 46.10 billion by 2030.

The AI in computer vision encompasses developing, integrating, and applying artificial intelligence (AI) algorithms to process, analyze, and interpret images and videos for various end-use industries. This market involves software and hardware components that facilitate AI-driven functionalities such as object recognition, image segmentation, motion detection, and video analytics. The increasing use of object detection in autonomous driving to detect and localize other vehicles, pedestrians, and obstacles on the road is driving the AI in the computer vision market. Furthermore, increasing fraudulent activities in the banking and government sectors is growing the need for AI in computer vision to detect fraud. However, the lack of knowledge, trained professionals, and high costs associated with AI in computer vision limit the adoption. Market players are focusing on training professionals and investing to overcome these issues. Rising government initiatives and the adoption of advanced machine learning and augmented reality are creating lucrative opportunities for market growth.

In the Americas, computer vision technology is widely adopted across different industries, such as retail, healthcare, and automotive. Major tech companies have invested heavily in research and development to create innovative solutions as computer vision carries out repetitive and monotonous tasks faster, simplifying the work for humans. Canada is emerging as a leading hub for artificial intelligence research, with several universities and research centers focusing on computer vision technology. The Canadian government has also prioritized AI investment by allocating funds for innovation and talent development. In the European Union (EU), multiple countries are contributing to the growth of computer vision applications. Several initiatives were established by the European Commission to foster collaboration among European researchers. EU countries, including France, the United Kingdom, and Germany, have invested significantly in computer vision start-ups. The Middle East region is witnessing rapid adoption of AI technologies driven by the government's efforts. Furthermore, in Africa, there is growing interest in applying computer vision to address pressing social issues such as agriculture optimization and wildlife conservation. Several African-based start-ups are leveraging AI-based image recognition tools for crop disease detection and anti-poaching efforts. In APAC countries, including China and Japan, demand is driven by extensive industrial applications of computer vision technology. Moreover, India is emerging as an AI hub with numerous start-ups focusing on computer vision solutions for various sectors, including agriculture, security, and healthcare and has initiated a National Program on AI to foster innovation.

The market dynamics represent an ever-changing landscape of the Artificial Intelligence in Computer Vision Market by providing actionable insights into factors, including supply and demand levels. Accounting for these factors helps design strategies, make investments, and formulate developments to capitalize on future opportunities. In addition, these factors assist in avoiding potential pitfalls related to political, geographical, technical, social, and economic conditions, highlighting consumer behaviors and influencing manufacturing costs and purchasing decisions.

• Market Drivers
  • Increasing demand for quality inspection and automation to perform manufacturing process
  • Growing demand for novel computer vision technologies in consumer electronics
  • Rising government initiatives to promote AI-related technologies and adoption of AI computer vision system
• Market Restraints
  • High manufacturing and maintenance cost associated with AI in computer vision
• Market Opportunities
  • Emerging applications of AI computer vision in agriculture and logistics sector
  • Rising integration of AI with computer vision in autonomous connected vehicles and robotics
• Market Challenges
  • Issues associated with the functionality of AI computer vision systems

• Offering: Increasing consumers preference for AI-powered computer vision solution

  AI-powered computer vision software encompasses various applications designed to analyze, identify, classify, and even predict patterns based on visual data. A key advantage of using AI-driven computer vision software is its ability to process large volumes of visual data at an unprecedented speed and accuracy. AI in computer vision services generally include consulting support to help businesses assess their needs for implementing AI-driven computer vision technologies; system integration and deployment assistance, ensuring the seamless integration of computer vision tools into existing systems; training solutions to help businesses upskill their workforce; and managed services for ongoing maintenance and support.

• Deployment: Expansion of cloud deployment of AI in computer vision

  With the increasing amount of data generated by cameras and IoT devices, cloud-based AI solutions have emerged as a popular choice for implementing computer vision applications. On-Cloud deployment offers several advantages, making it an attractive solution for businesses leveraging AI-powered computer vision technology. Some organizations prefer on-premises deployment for their AI-driven computer vision applications. This choice is often driven by multiple factors, including stringent security requirements, compliance with regulatory standards, and control over proprietary data.

• Application: Increasing use of AI in computer vision for facial detection and object detection for unique identification

  Image classification in computer vision is an essential task that assigns predefined categories and labels to images based on their content. Object detection and recognition involve locating objects within an image and a video frame and accurately identifying their class and category. Facial recognition is a subset of biometric identification using facial features to identify individuals uniquely. Gesture recognition involves interpreting human hand and body movements using computer algorithms. In medical imaging, AI has significantly enhanced disease diagnosis, treatment planning, and image-guided interventions.

• End-User Industry: Increasing adoption of AI computer vision in manufacturing and retail businesses to reduce the workload complexity

  In the automotive industry, AI in computer vision enhances safety and driving experiences. Retail businesses benefit immensely from AI-based computer vision systems by optimizing store layouts, understanding customer behavior patterns, and managing inventory efficiently. In healthcare, AI in computer vision technologies transforms diagnostics, treatment planning, and patient monitoring. Manufacturing processes are being revolutionized by incorporating AI in computer vision systems that ensure production lines' efficiency, quality control, and safety. AI in computer vision applications in security and surveillance has significantly enhanced the protection of public spaces, private properties, and critical infrastructure. In the agriculture industry, AI in computer vision technologies revolutionizes traditional farming practices by optimizing crop management and maximizing yield potential.

The market disruption analysis delves into the core elements associated with market-influencing changes, including breakthrough technological advancements that introduce novel features, integration capabilities, regulatory shifts that could drive or restrain market growth, and the emergence of innovative market players challenging traditional paradigms. This analysis facilitates a competitive advantage by preparing players in the Artificial Intelligence in Computer Vision Market to pre-emptively adapt to these market-influencing changes, enhances risk management by early identification of threats, informs calculated investment decisions, and drives innovation toward areas with the highest demand in the Artificial Intelligence in Computer Vision Market.

The porter's five forces analysis offers a simple and powerful tool for understanding, identifying, and analyzing the position, situation, and power of the businesses in the Artificial Intelligence in Computer Vision Market. This model is helpful for companies to understand the strength of their current competitive position and the position they are considering repositioning into. With a clear understanding of where power lies, businesses can take advantage of a situation of strength, improve weaknesses, and avoid taking wrong steps. The tool identifies whether new products, services, or companies have the potential to be profitable. In addition, it can be very informative when used to understand the balance of power in exceptional use cases.

The value chain of the Artificial Intelligence in Computer Vision Market encompasses all intermediate value addition activities, including raw materials used, product inception, and final delivery, aiding in identifying competitive advantages and improvement areas. Critical path analysis of the <> market identifies task sequences crucial for timely project completion, aiding resource allocation and bottleneck identification. Value chain and critical path analysis methods optimize efficiency, improve quality, enhance competitiveness, and increase profitability. Value chain analysis targets production inefficiencies, and critical path analysis ensures project timeliness. These analyses facilitate businesses in making informed decisions, responding to market demands swiftly, and achieving sustainable growth by optimizing operations and maximizing resource utilization.

The pricing analysis comprehensively evaluates how a product or service is priced within the Artificial Intelligence in Computer Vision Market. This evaluation encompasses various factors that impact the price of a product, including production costs, competition, demand, customer value perception, and changing margins. An essential aspect of this analysis is understanding price elasticity, which measures how sensitive the market for a product is to its price change. It provides insight into competitive pricing strategies, enabling businesses to position their products advantageously in the Artificial Intelligence in Computer Vision Market.

The technology analysis involves evaluating the current and emerging technologies relevant to a specific industry or market. This analysis includes breakthrough trends across the value chain that directly define the future course of long-term profitability and overall advancement in the Artificial Intelligence in Computer Vision Market.

The patent analysis involves evaluating patent filing trends, assessing patent ownership, analyzing the legal status and compliance, and collecting competitive intelligence from patents within the Artificial Intelligence in Computer Vision Market and its parent industry. Analyzing the ownership of patents, assessing their legal status, and interpreting the patents to gather insights into competitors' technology strategies assist businesses in strategizing and optimizing product positioning and investment decisions.

The trade analysis of the Artificial Intelligence in Computer Vision Market explores the complex interplay of import and export activities, emphasizing the critical role played by key trading nations. This analysis identifies geographical discrepancies in trade flows, offering a deep insight into regional disparities to identify geographic areas suitable for market expansion. A detailed analysis of the regulatory landscape focuses on tariffs, taxes, and customs procedures that significantly determine international trade flows. This analysis is crucial for understanding the overarching legal framework that businesses must navigate.

The regulatory framework analysis for the Artificial Intelligence in Computer Vision Market is essential for ensuring legal compliance, managing risks, shaping business strategies, fostering innovation, protecting consumers, accessing markets, maintaining reputation, and managing stakeholder relations. Regulatory frameworks shape business strategies and expansion initiatives, guiding informed decision-making processes. Furthermore, this analysis uncovers avenues for innovation within existing regulations or by advocating for regulatory changes to foster innovation.

The FPNV positioning matrix is essential in evaluating the market positioning of the vendors in the Artificial Intelligence in Computer Vision Market. This matrix offers a comprehensive assessment of vendors, examining critical metrics related to business strategy and product satisfaction. This in-depth assessment empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success, namely Forefront (F), Pathfinder (P), Niche (N), or Vital (V).

The market share analysis is a comprehensive tool that provides an insightful and in-depth assessment of the current state of vendors in the Artificial Intelligence in Computer Vision Market. By meticulously comparing and analyzing vendor contributions, companies are offered a greater understanding of their performance and the challenges they face when competing for market share. These contributions include overall revenue, customer base, and other vital metrics. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With these illustrative details, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.

• Landing AI Launches App Space to Enable Rapid Vision System Development

  Landing AI, the major computer vision cloud platform, launched Landing AI App Space, a new repository of applications and use cases to help developers create their own customized Landing AI-based computer vision solutions more quickly. The App Space shares sample mobile-friendly models via QR codes and curated source code that anybody can use to complete their computer vision projects via LandingLens, Landing AI's flagship product. [Published On: 2023-09-26]

• Landing AI and Snowflake Partner to Empower AI-Driven Computer Vision on Unstructured Data

  Landing AI announced a new partnership with Snowflake Inc., enabling organizations to leverage computer vision for analyzing unstructured data stored on Snowflake. Within the Landing AI platform, models can be trained and deployed as User-Defined Functions (UDFs) on Snowflake. Additionally, Snowflake Marketplace offered pre-trained, industry-standard models such as Snowflake Native Applications. [Published On: 2023-06-27]

• Pangiam and West Virginia University Research Corporation Partner to Develop Artificial Intelligence and Computer Vision Technology

  The partnership between Pangiam and West Virginia University Research Corporation (WVURC) has significant implications for artificial intelligence in the computer vision market. By leveraging WVURC's expertise in AI technology and Pangiam's expertise in biometrics-based identity verification, the new project aims to develop a comprehensive solution to meet the consumer's changing needs. This could further allow the market to expand its capabilities and achieve greater success in the future. [Published On: 2023-05-02]

The strategic analysis is essential for organizations seeking a solid foothold in the global marketplace. Companies are better positioned to make informed decisions that align with their long-term aspirations by thoroughly evaluating their current standing in the Artificial Intelligence in Computer Vision Market. This critical assessment involves a thorough analysis of the organization’s resources, capabilities, and overall performance to identify its core strengths and areas for improvement.

The report delves into recent significant developments in the Artificial Intelligence in Computer Vision Market, highlighting leading vendors and their innovative profiles. These include Intel Corporation, Arm Limited, Samsung Electronics Co. Ltd., Infosys Limited, Qualcomm Technologies, Inc., Groq, Inc., Unity Technologies, Advanced Micro Devices, Inc., Amazon.com Inc., Wovenware, Inc., NetApp, Inc., TechSee Augmented Vision Ltd., Nvidia Corporation, Landing AI, Apple Inc., Clarifai, Inc., XenonStack Pvt. Ltd., Dataiku, Hailo Technologies Ltd., Cognex Corporation, Basler AG, Raydiant, Inc., Oracle Corporation, General Electric Company, LXT, Adobe Inc., Microsoft Corporation, Google LLC by Alphabet Inc., International Business Machines Corporation, Meta Platforms, Inc., and Fujitsu Limited.

This research report categorizes the Artificial Intelligence in Computer Vision Market to forecast the revenues and analyze trends in each of the following sub-markets:

• Offering
  • Hardware
    • Memory
    • Network
    • Processors
      • Application-Specific Integrated Circuit
      • Central Processing Unit
      • Field Programmable Gate Arrays
      • Graphics Processing Unit
      • Vision Processing Unit
  • Services
  • Software
• Processes
  • Inference
  • Training
• End-User Industry
  • Agriculture
    • Automated Irrigation System
    • Crop Monitoring
  • Automotive
    • ADAS & Infotainment
    • Autonomous & Semi-Autonomous Vehicles
  • Consumer
    • Cameras
    • Gaming
    • Smart Phones
    • Wearables
  • Healthcare
    • Medical Adherence
    • Radiology
  • Robotics & Machine Vision
    • Positioning & Guidance
    • Quality Assurance & Inspection
  • Security & Surveillance
    • AI-Guided Drone-Based Surveillance
    • Biometrics
    • Image & Video Analytics
  • Sports & Entertainment
    • Ball Tracking & Player Tracking
    • Commercial Insertion
    • Virtual Reality/Augmented Reality
• Application
  • Industrial
  • Non-industrial
• Deployment
  • On-Cloud
  • On-Premises
• Organization Size
  • Large Enterprises
  • Small & Medium Enterprises

• Region
  • Americas
    • Argentina
    • Brazil
    • Canada
    • Mexico
    • United States
      • California
      • Florida
      • Illinois
      • New York
      • Ohio
      • Pennsylvania
      • Texas
  • Asia-Pacific
    • Australia
    • China
    • India
    • Indonesia
    • Japan
    • Malaysia
    • Philippines
    • Singapore
    • South Korea
    • Taiwan
    • Thailand
    • Vietnam
  • Europe, Middle East & Africa
    • Denmark
    • Egypt
    • Finland
    • France
    • Germany
    • Israel
    • Italy
    • Netherlands
    • Nigeria
    • Norway
    • Poland
    • Qatar
    • Russia
    • Saudi Arabia
    • South Africa
    • Spain
    • Sweden
    • Switzerland
    • Turkey
    • United Arab Emirates
    • United Kingdom

1. Market Penetration: This section thoroughly overviews the current market landscape, incorporating detailed data from key industry players.
2. Market Development: The report examines potential growth prospects in emerging markets and assesses expansion opportunities in mature segments.
3. Market Diversification: This includes detailed information on recent product launches, untapped geographic regions, recent industry developments, and strategic investments.
4. Competitive Assessment & Intelligence: An in-depth analysis of the competitive landscape is conducted, covering market share, strategic approaches, product range, certifications, regulatory approvals, patent analysis, technology developments, and advancements in the manufacturing capabilities of leading market players.
5. Product Development & Innovation: This section offers insights into upcoming technologies, research and development efforts, and notable advancements in product innovation.

1. What is the current market size and projected growth?
2. Which products, segments, applications, and regions offer promising investment opportunities?
3. What are the prevailing technology trends and regulatory frameworks?
4. What is the market share and positioning of the leading vendors?
5. What revenue sources and strategic opportunities do vendors in the market consider when deciding to enter or exit?