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A12999 | Pages: 450 | Charts: 90 | Tables: 154 |
Artificial neural network (ANN) is based on a computational algorithm replicating the biological network of human brains composed of neurons, used for solving complex nonlinear functions. The general form of this model is referred to as a black box model representing high dimensional, nonlinear data. The ANN model has found extensive application in various fields like medical science, environmental engineering, weather forecasting, and economics. In addition, artificial neural network solutions are used for numerous applications in day-to-day life. The field has seen exponential growth in the last few years. It is majorly used in spell check, machine translation facial recognition, and other applications almost everywhere in the real world.
The global artificial neural network market is segmented on the basis of component, deployment mode, enterprise size, industry, and region. By component, it is categorized into solution and services. On the basis of deployment mode, it is divided into on-premise and cloud. By enterprise size, it is segmented into large enterprises and small and medium-sized enterprises. Depending on industry, it is categorized into healthcare, BFSI, retail and e-commerce, manufacturing, automotive, and others. Region wise, the market is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
[COMPONENTGRAPH]
On the basis of component, the global artificial neural network market share was dominated by the solution segment in 2022 and is expected to maintain its dominance in the upcoming years, as the growing need for a high level of personalization are one of the primary reasons enterprises are increasing their investment in the artificial neural network market. However, the services segment is expected to witness the highest growth, as these services help to reduce the time and costs associated with optimizing systems in the initial phase of deployment.
[DEPLOYMENTMODEGRAPH]
On the basis of deployment mode, the on-premise segment is expected to grow at a significant growth rate during the forecast period. An increase in the need for secure and reliable data within the organization is fueling the market growth for on-premises-based artificial neural network solutions.
[ENTERPRISESIZEGRAPH]
By enterprise size, the large enterprises are expected to grow at the highest growth rate during the forecast period, as these enterprises consist of huge employee structures and artificial neural network solutions are used.
[INDUSTRYGRAPH]
Based on industry, the healthcare segment accounted for the largest share in 2022 owing to the development digital technologies in healthcare sector.
[REGIONGRAPH]
The key factors that drive the growth of the artificial neural network market include the growing demand for AI-based solutions. AI solutions provide the underlying infrastructure and resources needed to deliver digitalization to end-users, making it an essential enabler for businesses. This is attributed to the rising number of countries committing to adopt AI solutions. The growth of the artificial neural network market is augmented by the rising need for intelligent business processes. It is optimizing business operational processes with the integration of advanced technologies and AI solutions. Leveraging automation trends and the use of smart operations in industries, such as banking and finance, could lead to predictive maintenance and predictive quality.
However, a significant challenge in this market is the lack of computational resources and a skilled workforce with expertise in ANN. Training deep neural networks, especially large ones, can be computationally intensive and require powerful hardware, such as graphics processing units (GPUs) or specialized hardware like tensor processing units (TPUs). Consequently, this factor impedes the wider adoption of these solutions, particularly among organizations with limited expertise. To tackle this challenge, service providers might need to offer more flexible and scalable alternatives to cater to a broader spectrum of businesses. However, advancements in big data analytics and the availability of high-performance computing systems are anticipated to emerge as lucrative opportunities over the artificial neural network market forecast period.
By region, North America dominated the market share in 2022 for the artificial neural network market. This growth is attributed to rising focus on regulatory compliance solutions for data privacy and security. This region is more focused on regulatory compliance solutions for data privacy and security which is anticipated to propel the growth of the artificial neural network market. However, Asia-Pacific is expected to exhibit the highest growth during the forecast period. This is attributed to the increase in penetration of digitalization and higher adoption of advanced technology which are expected to provide lucrative growth opportunities for the market in this region.
The surge in the expansion of AI-based solutions is a key driver for the growth of the global market. AI solutions provide the underlying infrastructure and resources needed to deliver digitalization to end-users, making it an essential enabler for businesses. This is attributed to the rising number of countries committing to adopt AI solutions. Further, government policies are undertaking increased initiatives to embrace advanced technology, with plans for integrating a new digital solution. Therefore, AI solutions gained wider traction among end-users, taking advantage of AI solutions in several industries.
Moreover, organizations may avoid the upfront costs associated with purchasing and maintaining on-premises hardware infrastructure. Consequently, regional governments and private and public businesses invest in AI solutions. For instance, in April 2023, Ericsson partnered with the Government of Canada to raise $352.40 million (CAD 470 million) in funding to enhance the presence of the global leaders in advanced 5G, 6G, AI, cloud RAN, and core network technologies. Such investment and advancements in AI solutions will eventually contribute to the growth of the global market.
The lack of computational resources and knowledgeable employees with expertise in artificial neural network solutions are the key constraints to the growth of the global market. Deep neural network training, particularly for large enterprises, can be computationally demanding and requires expensive technology, such as specialized hardware like tensor processing units (TPUs) or graphics processing units (GPUs). The adoption of artificial neural network solutions by several individuals and enterprises may be hindered by their inability to access such resources.
Furthermore, deep learning and artificial neural networks need a thorough comprehension of intricate mathematical ideas and procedures. Effective neural network development and implementation frequently involves knowledge of linear algebra, mathematics, optimization, and machine learning. These measures cause business operations to be restricted in an unplanned manner, which negatively impacts punctuality and the allocation of resources in artificial neural network solutions. Moreover, there is a limitation of professionals with expertise in artificial neural network solutions and deep learning services, making it difficult for organizations to find and hire individuals to design, train, and deploy neural networks effectively. These concerns about computational resources and lack of expertise are anticipated to hinder the artificial neural network market growth.
The rise in the trend of big data analytics solutions in several sectors and among individuals is directly influencing the growth of the global artificial neural network industry. In addition, the increase in demand for data analytics in different industry aspects like customer satisfaction, reliability, operational efficiency, and safety is the key factor driving the global market growth. Consequently, big data analytics solutions are gaining significant adoption to increase the use of IT and control systems among business operators, particularly smartphone usage and other digital technologies. According to the article published by Keboola in June 2022, nearly 90% of enterprise analytics and business professionals stated that data and analytics are key to their organization's digital transformation.
In addition, increased use of smartphones and the internet helps consumers to easily access online platforms, by simply downloading the application on their phones. Such ease of access has contributed to the high growth adoption for the global market, which in turn is expected to contribute to the increased installation of artificial neural network market, globally.
Furthermore, the rise in demand for data analytics for the analysis of data generated in numerous processes highlights key business insights which in turn support the growth of the market. In order to analyze the data, appropriate database technology is essential. The artificial neural network serves this purpose in case of unstructured data by providing support for moderate data analytics. The need for data analytics, especially on unstructured data, is further expected to increase in the forecast period. Hence, these multiple benefits offered by data analytics solutions in database operations will boost the demand for the artificial neural network market.
Moreover, several public and private organizations are continuously involved in promoting digitalization in analytical operations. For instance, in August 2021, Covera Health, a healthcare data analytics platform, raised $25 million in funding to focus on reducing medical errors, which in turn, augments the market growth on a global scale.
Competitive analysis and profiles of the major players, such as Amazon Web Services Inc., Google Inc., Hewlett Packard Enterprise Development LP, IBM Corporation, Intel Corporation, Microsoft Corporation, NVIDIA Corporation, Oracle Corporation, Qualcomm Technologies Inc. and Salesforce Inc., are mentioned in the report. These major players have adopted various key development strategies such as business expansion, new product launches, and partnerships, which help to drive the growth of the artificial neural network market globally.
For instance, in February 2023, the Naval Postgraduate School (NPS) partnered with Qualcomm Technologies, Inc., to focus on emerging disruptive technologies with potential applications to U.S. Navy and U.S. Marine Corps capability needs.
For instance, in May 2022, GE Healthcare launched expansion of its deep learning image reconstruction solution, AIR Recon DL, as an upgrade as well as with new purchases across its product portfolio. This marks a significant moment in the democratization of artificial intelligence (AI) and deep learning for the benefit of healthcare systems and patients around the globe.
For instance, in November 2021, Qualcomm Technologies, Inc. collaborated with Google Cloud, to accelerate neural network development and differentiation for snapdragon mobile, and XR platforms, snapdragon ride platform, and Qualcomm Technologies™ IoT platforms by utilizing Google Cloud Vertex AI neural architecture search (NAS) with the Qualcomm artificial intelligence (AI) engine.
The global artificial neural network market analysis has witnessed stable growth during the COVID-19 pandemic, owing to the dramatically increased digital penetration during the period of COVID-19-induced lockdowns and stringent social distancing policies, which further fueled the demand for advanced smart tools such as artificial neural network tools. According to an article published by Harvard Business Review, in September 2021, nearly 52% of companies accelerated their AI adoption plans because of the Covid crisis, and nearly 86% businesses stated that AI is becoming a mainstream technology at their company.
Furthermore, the increasing number of COVID-19 cases caused many organizations to adopt remote working tools. According to an article published by TechTarget, in December 2020, more than 67% of organizations that adopted work-from-home policies post the outbreak of COVID-19, plan to keep their remote working options available for their employees even after the period of pandemic. Thus, such factors propelled the growth of global artificial neural network market during the period.
Key Market Segments
Key Market Players