AI Image Recognition Market - Growth, Trends, COVID-19 Impact, and Forecasts (2023 - 2028)

AI Image Recognition Market Analysis

The AI image recognition market was valued at USD 2,993.3 million in 2021, and it is expected to register a CAGR of 20.97% during the forecast period 2022-2027. Artificial intelligence (AI) is a technology field that uses technology to replicate the cognitive processes of human intellect. Since its inception, image recognition has long been recognized as one of artificial intelligence's most lucrative and beneficial applications. Image recognition, closely related to computer vision, is an interdisciplinary area of computer science that deals with a computer's capacity to recognize and comprehend the material within images.

• Artificial intelligence (AI) has been incorporated into many aspects of daily life, including language recognition software, AI-enhanced cameras for smartphones, financial transaction analysis in banks, and self-driving car algorithms. With the emergence of AI for numerous applications, from diagnosis to therapy recommendations, medical imaging is going through a fundamental transformation.
• The adoption of artificial intelligence (AI) technology is rising due to its ability to enhance and automate operations and enrich the user experience. The increasing adoption of AI in the healthcare sector, such as in diagnostic radiology, is expected to fuel the growth of the AI market over the forecast period. The defense sector is expected to drive innovations in AI with huge budgets allocated for technology development.
• Big data is being adopted widely in different industries. With robust internet penetration and new technologies, there is massive growth in the data generated globally. The technologies, such as the Internet of Things, Industry 4.0, and 5G, among others, encourage artificial intelligence. Massive growth in data generation due to technological advancements results in big data. AI simplifies big data analytics by automating and improving data preparation, data visualization, predictive modeling, and other complicated analytical operations that may otherwise be time-consuming and labor-intensive. AI speeds up analyzing massive, complex datasets and surfacing relevant user insights.
• As AI and deep learning applications expand globally, from tech giants to small and medium-sized businesses, the need for artificial intelligence technicians has increased significantly. However, there has been a shortage of expert AI technicians.
• COVID-19 positively impacted the market as few industries witnessed an increase in AI adoption; however, others faced a decline. The pandemic educated business executives with vital insights into digital transformation. The potential that data analytics and artificial intelligence bring to an organization is one of the most compelling teachings. For instance, AI aids push processes, people, and services online in the public sector and compel local, regional, and national governments to embrace AI. In a few months, governments globally have learned to use AI as a weapon to fight against the virus, from educating the public and screening patients to tracking and tracing contacts.

AI Image Recognition Industry Segments

Image recognition is the software's ability to identify places, objects, people, writing, and actions in images. Computers can use machine vision technologies in combination with a camera and artificial intelligence software to achieve image recognition. Image recognition is used to perform many machine-based visual tasks, such as labeling the content of images with meta tags, performing image content searches, guiding autonomous robots and self-driving cars, and in accident-avoidance systems.

The study tracks the key market parameters, underlying growth influencers, and major vendors operating in the industry, which supports the market estimations and growth rates during the forecast period. The study also tracks the revenue accrued from the various AI image recognition types used across end-user industries. The study provides the global AI image recognition market trends and key vendor profiles. The study analyzes the impact of the COVID-19 pandemic on the ecosystem.

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AI Image Recognition Market Trends

This section covers the major market trends shaping the AI Image Recognition Market according to our research experts:

Healthcare Sector is Expected to Witness Significant Growth

• The adoption of AI image recognition technology in the healthcare sector is rapidly growing globally, owing to a wide range of applications for artificial intelligence image recognition technology in CT scans, x-rays, ultrasound, and magnetic resonance imaging. Furthermore, from improved security and patient identification to better patient monitoring and diagnosis, AI image recognition technology has helped improve patient experience and reduce the workload for healthcare workers.
• Additionally, AI image recognition models can assist in the diagnosing of various conditions. The models can be trained and deployed to scan images from MRI or x-ray machines, as well as other visual outputs, to detect, locate and flag up medical abnormalities that the model has been trained to identify. For instance, it can identify the number and exact locations of tumors within an image, helping to direct the medical practitioner's attention to the malignant or cancerous elements.
• Furthermore, AI image recognition models help retrieve information on similar conditions identified to be closely related to the patient's results from a medical examination. MRI or x-ray scans are already implemented to provide medical teams with insightful images for various diseases and traumas, including cancer, broken bones, and many other conditions. Image similarity search can benefit this field by retrieving similar images, which can help doctors with an accurate diagnosis by supplying x-ray/MRI images of a similar physical appearance to those images from the patient of concern.
• Additionally, check-in and check-out processes are fundamental in the healthcare setup. AI image recognition technology can make them more accessible and faster, simultaneously decreasing the workload for hospital staff. When a patient enters the facility, the face recognition system scans their face and runs it against the hospital database. The patient's identity is verified in real-time, without the need for paperwork or additional identification documents.
• Furthermore, there are several factors simultaneously driving the integration of AI in radiology. First, in many countries around the world, there is a shortage of doctors trained in radiology, which, considering the rising demand for diagnostic imaging, helps increase work efficiency and productivity.

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