Global AI Image Recognition Market - 2023-2030

Global AI Image Recognition Market - 2023-2030

Global AI Image Recognition Market reached US$ 1.9 Billion in 2022 and is expected to reach US$ 4.6 Billion by 2030, growing with a CAGR of 11.8% during the forecast period 2023-2030.

The application of AI image recognition for tasks like quality control, inspection and monitoring is fueled by the global movement toward automation in all industries which helps to boost the market growth of the AI image recognition market. Automation enhances operational efficiency and reduces human intervention in repetitive visual tasks. AI image recognition finds applications in diverse industries, including healthcare, retail, automotive, security and agriculture. The versatility of image recognition technologies contributes to their widespread adoption in solving industry-specific challenges.

In the e-commerce and retail industry, AI image recognition presents opportunities for visual search, product recommendation, inventory management and customer engagement. Enhanced user experiences and personalized services drive adoption in the retail sector. Smart city initiatives provide opportunities for AI image recognition in urban planning, traffic management, public safety and environmental monitoring. The integration of image recognition technologies contributes to the development of efficient and sustainable cities.

The growing application of AI visual recognition in North America's healthcare industry has greatly assisted the market expansion of AI image recognition technology. For instance, in 2022, U.S. spent almost 26% of its GDP on healthcare facilities. In North America, consumers spend a portion of their extra cash on healthcare. The rapid growth of the healthcare industry in the region helps to boost the market growth of AI image recognition.

Dynamics

Growing AI Adoption

As awareness and understanding of AI technologies have grown globally, businesses across various industries recognize the potential benefits of integrating AI image recognition into their operations. The understanding has contributed to a willingness to explore and invest in AI solutions. Ongoing advancements in AI, particularly in deep learning and neural networks, have resulted in more sophisticated and accurate image recognition models. The technological improvements have increased the overall effectiveness and reliability of AI image recognition systems, driving adoption.

According to the data given by Harward Business review in 2021 about 52% of companies accelerated their AI adoption plans because of the COVID crisis. 86%, of participants say that AI is becoming a “mainstream technology” at their company in 2021. Harris Poll, working with Appen, found that 55% of companies reported they accelerated their AI strategy in 2020 due to COVID-19 and 67% expect to further accelerate their AI strategy in 2021. 72% of participants in the survey feel positive about the role that AI play in the future.

Technological Advancements

Advances in deep learning architectures have significantly improved the accuracy and performance of AI image recognition models. Enhanced algorithms and model architectures contribute to more precise image recognition results. Technological advancements in deep learning, especially the development of deeper neural networks, enable AI systems to learn intricate patterns and features within images. The has led to breakthroughs in image recognition tasks, including object detection and classification.

Technological advancements have enabled AI image recognition systems to process and analyze visual data in real time. The is critical for applications such as surveillance, autonomous vehicles and live video analytics where instant decision-making is essential. For instance, on March 08, 2020, researchers from the Institute of Photonics, Austria created an artificial eye on a small chip by using light-sensing electronics with a neural network. The new design, presented in Vienna has been reported to identify an object within a few nanoseconds, which is a serious advancement in the technology.

Lack of Standardization in the AI Image Recognition

Without standardized practices, interoperability between different AI image recognition systems becomes challenging. The lack of compatibility hinders the seamless integration of image recognition solutions into existing workflows and technologies. The absence of standardized benchmarks and evaluation metrics lead to inconsistent performance across different image recognition models. The makes it difficult for businesses and users to compare and choose the most suitable solution for their specific needs.

Standardization is crucial for the fair and accurate evaluation of different AI image recognition models. The lack of standardized evaluation criteria makes it challenging for developers and users to objectively compare the performance of various models. Standardization plays a key role in ensuring transparency and explainability in AI systems. Without standardized methods for model interpretation and explanation, users find it difficult to understand how AI image recognition systems arrive at specific decisions, leading to trust issues.

Segment Analysis

The global AI image recognition market is segmented based on component, application, end-user and region.

Growing Adoption of AI Image Recognition Software in Various Industries

Based on the components, the AI image recognition market is segmented into hardware, software and services. AI image recognition software segment is growing over the forecast period 2023-2030. Artificial intelligence recognizes image software is growing in direct proportion to advances in deep learning and neural networks. Convolutional neural networks (CNNs), in particular, are deep learning models that have shown impressive capabilities in image identification obligations, increasing performance and accuracy.

The availability of large and diverse labeled datasets has played a crucial role in training and fine-tuning sophisticated AI image recognition models. Access to extensive datasets allows software developers to create more accurate and generalized image recognition solutions. The availability of open-source deep learning frameworks such as TensorFlow and PyTorch has democratized AI development.

The has empowered developers to create and customize image recognition models, fostering innovation and accelerating the adoption of AI image recognition software. To fulfill consumer's demand for the AI Image Recognition software major key players in the market launched new products. For instance, on April 07, 2023, Meta launched AI tool that identify, separate items in pictures.

Geographical Penetration

Growing Adoption of AI Image Recognition in Various industries of North America

North America accounted for the largest market share in the global AI image recognition market due to the region’s well-established and robust IT infrastructure providing a solid foundation for the deployment and integration of AI image recognition systems across various industries. North America is anticipated to have the greatest market size in the global image recognition market.

North America is home to the headquarters of many of the top technology companies in the world, such as Google, Microsoft and IBM. The companies promote AI innovation and adopt the application of cutting-edge image recognition technologies. Major key players in the region launched new services for AI image recognition that help boost the regional market growth of the global AI image recognition market.

For instance, on November 03, 2023 oracle announced Oracle Cloud Infrastructure (OCI) AI services that make it easier for developers to apply AI services to their applications without requiring data science expertise. It gives developers the choice of leveraging out-of-the-box models that have been trained on business-oriented data or custom training the services based on their organization’s data.

Competitive Landscape

The major global players in the market include IBM Corporation, Imagga Technologies Ltd, Amazon Web Services, Inc, Qualcomm, Google LLC, Microsoft Corporation, Trax Technology Solutions Pte Ltd, NEC Corporation, Ricoh Company, Ltd and Catchoom Technologies S.L.

COVID-19 Impact Analysis

Geopolitical tensions and conflicts lead to disruptions in the global supply chain, affecting the production and availability of hardware components and technologies necessary for AI image recognition systems. Heightened geopolitical tensions contribute to overall market uncertainty. Businesses become more cautious about investments, potentially impacting the demand for AI technologies, including image recognition solutions.

Geopolitical events result in changes to regulations and policies that govern the development, export or use of certain technologies. Regulatory shifts impact the global market landscape for AI image recognition. During geopolitical conflicts, there is often an increased risk of cyber threats and attacks. As AI image recognition systems deal with sensitive visual data, companies invest more in cybersecurity measures to protect these technologies. Geopolitical instability influence research and development activities in the AI field. Collaboration and knowledge exchange between researchers and institutions in different regions were affected.

Russia-Ukraine War Impact Analysis

Geopolitical tensions and conflicts lead to disruptions in the global supply chain, affecting the production and availability of hardware components and technologies necessary for AI image recognition systems. Heightened geopolitical tensions contribute to overall market uncertainty. Businesses become more cautious about investments, potentially impacting the demand for AI technologies, including image recognition solutions. Geopolitical events result in changes to regulations and policies that govern the development, export or use of certain technologies. Regulatory shifts impact the global market landscape for AI image recognition.

During geopolitical conflicts, there is often an increased risk of cyber threats and attacks. As AI image recognition systems deal with sensitive visual data, companies invest more in cybersecurity measures to protect these technologies. Geopolitical instability influences research and development activities in the AI field. Collaboration and knowledge exchange between researchers and institutions in different regions were affected.

By Component
• Hardware
• Software
• Service

By Application
• Augmented Reality
• Scanning & Imaging
• Security & Surveillance
• Marketing & Advertising
• Image Search

By End-User
• Education
• Gaming
• Healthcare
• Government
• Aerospace & Defense
• Media & Entertainment
• Retail
• Banking Financial Services and Insurance
• Others

By Region
• North America
U.S.
Canada
Mexico
• Europe
Germany
UK
France
Italy
Spain
Rest of Europe
• South America
Brazil
Argentina
Rest of South America
• Asia-Pacific
China
India
Japan
Australia
Rest of Asia-Pacific
• Middle East and Africa

Key Developments
• On October 11, 2023, Klarna, a Swedish fintech company launched AI-powered image Recognition Tool in the market. The tool Shopping Lens uses AI to translate images of products into a search term and directs customers to the best deals on Klarna's app.
• On December 12, 2023, Mastercard, launched Shopping Muse, an AI tool that gives product recommendations. By using this tool shoppers search for products using search terms such as cottage core or beach formal and receive product recommendations based on their demographic profile, intent, purchase history and other traits.
• On October 02, 2023, GoSpotCheck by FORM, the top AI-powered retail execution platform for Beverage Alcohol and CPG launched the latest innovation to its image recognition technology which provides support to the on-premise displays, including beer menu, beer taps, wine menu, cocktail menu and back bar.

Why Purchase the Report?
• To visualize the global AI image recognition market segmentation based on component, application, end-user and region, as well as understand key commercial assets and players.
• Identify commercial opportunities by analyzing trends and co-development.
• Excel data sheet with numerous data points of AI image recognition market-level with all segments.
• PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
• Product mapping available as excel consisting of key products of all the major players.

The global AI image recognition market report would provide approximately 61 tables, 65 figures and 206 Pages.

Target Audience 2023
• Manufacturers/ Buyers
• Industry Investors/Investment Bankers
• Research Professionals
• Emerging Companies