Visual Artificial Intelligence Market Trends:the global market size is projected to grow from USD 86.87 billion in 2024 to USD 138.35 billion by 2030

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Published: 2024-07-10

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According to the new market research report "Visual Artificial Intelligence - Global Market Share and Ranking, Overall Sales and Demand Forecast 2024-2030", published by QYResearch, the global Visual Artificial Intelligence market size is projected to grow from USD 86.87 billion in 2024 to USD 138.35 billion by 2030, at a CAGR of 8.06% during the forecast period (2024-2030).

 Visual Artificial Intelligence

Source: QYResearch, "Visual Artificial Intelligence - Global Market Share and Ranking, Overall Sales and Demand Forecast 2024-2030”

 

  • Global Visual Artificial Intelligence Top 16Players Rankingand Market Share (Ranking is based on the revenue of 2023, continually updated)

Visual Artificial Intelligence
Source: QYResearch, "Visual Artificial Intelligence - Global Market Share and Ranking, Overall Sales and Demand Forecast 2024-2030”

This report profiles key players of Visual Artificial Intelligence such as Keyence, Cognex, SenseTime, OMRON, Teledyne, Basler, Megvii Technology, OPT Machine Vision Tech, Daheng New Epoch Technology, YITU Technology, CloudWalk Technology, ArcSoft, Hikvision, Shenzhen Intellifusion Technologies, Dahua Technology, Deep Glint International, etc.

In 2023, the global top five Visual Artificial Intelligence players account for 29.02% of market share in terms of revenue. Above figure shows the key players ranked by revenue in Visual Artificial Intelligence.

 

  • Visual Artificial Intelligence, Global Market Size, Split by Product Segment

Visual Artificial Intelligence
Source: QYResearch, "Visual Artificial Intelligence - Global Market Share and Ranking, Overall Sales and Demand Forecast 2024-2030”

 

In terms of product type, Hardware is the largest segment, hold a share of 58.67%.


  • Visual Artificial Intelligence, Global Market Size, Split by Application Segment

Visual Artificial Intelligence
Source: QYResearch, "Visual Artificial Intelligence - Global Market Share and Ranking, Overall Sales and Demand Forecast 2024-2030”

 

In terms of product application, City Management is the largest application, hold a share of 34.37%.


  • Visual Artificial Intelligence, Global Market Size, Split by Region

 Visual Artificial Intelligence

 Source: QYResearch, "Visual Artificial Intelligence - Global Market Share and Ranking, Overall Sales and Demand Forecast 2024-2030”


Market Drivers:

Increasing Demand for Automation: As industries seek to automate various processes to enhance efficiency and reduce costs, the demand for visual AI solutions rises. Visual AI enables automation in tasks such as quality control, surveillance, and inspection, leading to improved productivity.

Advancements in Deep Learning and Computer Vision: Deep learning techniques, particularly in the field of computer vision, have significantly improved the accuracy and performance of visual AI systems. Breakthroughs in algorithms and hardware accelerate the development of more sophisticated visual AI applications.

Rapid Growth of Image and Video Data: With the proliferation of digital devices and platforms, there's an explosion of image and video data generated daily. Visual AI technologies enable businesses to extract valuable insights from this vast amount of unstructured data, driving demand for solutions that can analyze and interpret visual content at scale.

Industry-specific Applications: Various industries, including healthcare, retail, automotive, agriculture, and manufacturing, are adopting visual AI for specific use cases tailored to their needs. For example, in healthcare, visual AI assists in medical imaging analysis and disease diagnosis, while in retail, it facilitates personalized shopping experiences through visual search and recommendation systems.

Enhanced User Experiences: Visual AI enhances user experiences across multiple domains, such as augmented reality (AR), virtual reality (VR), and mixed reality (MR). These technologies leverage visual AI to deliver immersive and interactive experiences, driving demand for solutions that can understand and respond to users' visual inputs in real time.

Regulatory Compliance and Safety Standards: Industries with stringent regulatory requirements, such as automotive and aerospace, increasingly rely on visual AI solutions to ensure compliance with safety standards and regulations. Visual AI-powered systems assist in tasks like autonomous driving and aircraft maintenance, where accuracy and reliability are paramount.

Growing Investments and Partnerships: The visual AI market is witnessing significant investments from both established companies and startups, fueling innovation and driving market growth. Partnerships between technology providers, research institutions, and industry players further accelerate the development and adoption of visual AI solutions.

Cost Reduction and Scalability: Advancements in cloud computing and edge computing technologies have made visual AI more accessible and scalable for businesses of all sizes. Cloud-based visual AI platforms offer cost-effective solutions with flexible deployment options, allowing organizations to leverage AI capabilities without heavy upfront investments in infrastructure.

 

Restraint:

Data Privacy and Security Concerns: The widespread use of visual AI involves the collection and analysis of large amounts of sensitive visual data, raising concerns about data privacy and security. Unauthorized access, misuse, or breaches of visual data could lead to legal and ethical challenges, hindering adoption in sectors where data protection regulations are stringent.

Ethical and Bias Issues: Visual AI systems can inadvertently perpetuate biases present in training data, leading to unfair or discriminatory outcomes, particularly in applications such as facial recognition or hiring processes. Addressing biases and ensuring fairness in visual AI algorithms is a complex challenge that requires careful design, transparent methodologies, and ongoing monitoring.

Complexity and Integration Challenges: Implementing visual AI solutions often requires integration with existing systems, workflows, and infrastructure, which can be complex and time-consuming. Organizations may face challenges in data preprocessing, model training, and deployment, especially if they lack in-house expertise or encounter compatibility issues with legacy systems.

Lack of Standardization and Interoperability: The absence of standardized frameworks and protocols for visual AI interoperability hampers collaboration and integration between different systems and vendors. As a result, organizations may face difficulties in exchanging data, deploying unified solutions, or scaling visual AI implementations across multiple platforms or environments.

Cost and Return on Investment (ROI) Uncertainty: While visual AI offers numerous potential benefits, including efficiency gains, cost reduction, and insights generation, the upfront costs of implementation and uncertainty about ROI may deter some organizations from investing in visual AI solutions. Demonstrating tangible business value and quantifiable returns becomes crucial for driving adoption in cost-conscious industries.

Regulatory and Legal Challenges: Regulatory frameworks governing the use of visual AI, such as data protection regulations, intellectual property laws, and sector-specific regulations, vary across jurisdictions and may pose compliance challenges for organizations operating in multiple regions or industries. Navigating complex regulatory landscapes requires careful legal analysis and compliance measures.

Limited Access to High-quality Training Data: Training high-performing visual AI models often relies on access to diverse and representative training data, which may be limited or expensive to acquire, especially for niche or specialized applications. Data acquisition, annotation, and curation processes can be resource-intensive and time-consuming, posing challenges for startups and smaller enterprises with limited budgets.


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QYResearch is a world-renowned large-scale consulting company. The industry covers various high-tech industry chain market segments, spanning the semiconductor industry chain (semiconductor equipment and parts, semiconductor materials, ICs, Foundry, packaging and testing, discrete devices, sensors, optoelectronic devices), photovoltaic industry chain (equipment, cells, modules, auxiliary material brackets, inverters, power station terminals), new energy automobile industry chain (batteries and materials, auto parts, batteries, motors, electronic control, automotive semiconductors, etc.), communication industry chain (communication system equipment, terminal equipment, electronic components, RF front-end, optical modules, 4G/5G/6G, broadband, IoT, digital economy, AI), advanced materials industry Chain (metal materials, polymer materials, ceramic materials, nano materials, etc.), machinery manufacturing industry chain (CNC machine tools, construction machinery, electrical machinery, 3C automation, industrial robots, lasers, industrial control, drones), food, beverages and pharmaceuticals, medical equipment, agriculture, etc.

 

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