Artificial Neural Network Market Expected to Reach $1.4 Billion by 2032—Allied Market Research

According to a new report published by Allied Market Research, titled, “Artificial Neural Network Market, by Component, Deployment Mode, Enterprise Size, Industry: Global Opportunity Analysis And Industry Forecast, 2023-2032" The artificial neural network market was valued at $227.80 million in 2022, and is estimated to reach $1.4 billion by 2032, growing at a CAGR of 19.9% from 2023 to 2032.

Neural networks are a series of algorithms that duplicate the operations and processes of a human brain to recognize relationships between vast amounts of data. A neural network is used in a variety of applications in financial services, from forecasting and marketing research to fraud detection and risk assessment. Rising unstructured data volumes and the impending need for analytics primarily drive the artificial neural network market growth. Moreover, innovative business offerings such as advanced facial recognition solution by neural network vendors play a significant role in its adoption. However, some of the restraints associated with its business attractiveness are higher testing-related issues during unit or system integration testing as compared to traditional system and the problems associated with handling complex system architecture which can limit the global market growth. However, these challenges are expected to have a limited impact on the artificial neural network market growth due to the emergence of deep learning technology citing the increased need for automation solutions. Overall, the artificial neural network market is expected to continue to grow due to the rise in the adoption of digital services across enterprises.

Artificial Neural Networks (ANNs) fulfill a crucial function within the industrial context through the augmentation of efficiency and the enhancement of decision-making procedures. Within the realm of manufacturing, ANNs possess the capability to streamline production schedules, anticipate equipment failures, and refine quality control. Furthermore, in the context of predictive maintenance, these networks conduct an analysis of sensor data to effectively anticipate potential issues, thereby minimizing periods of inactivity. ANNs also make notable contributions to the domain of supply chain management, optimizing both logistics and inventory management. The capacity of ANNs to absorb knowledge from data empowers industries to base their decisions on data-driven insights, leading to the advancement of operational efficiency and the attainment of cost reductions across the diverse spheres of industrial processes.

On the basis of deployment mode, the on-premise segment is expected to grow at the highest 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. Though on-premise mode is comparatively more expensive than cloud-based services, it is preferred owing to its reliability. However, the cloud segment is expected to exhibit the highest growth during the forecast period. This is attributed to the cost-efficient solutions provided by these solutions.

On the basis of region, North America attained the highest growth in 2022. The presence of prominent players such as Oracle Corporation, IBM Corporation, and others have influenced the growth of the artificial neural network market in North America. Moreover, the rise in government initiatives to strengthen database infrastructure across the region is further expected to drive the demand for Artificial neural network database solutions.  However, Asia-Pacific is projected to be the fastest-growing segment during the forecast period, owing to the availability of cost-effective digital solutions and the rise in the amount of data generation across organizations. In addition, the proliferation of advanced technologies escalates system safety and reduces delays in database operations.

The outbreak of COVID-19 is projected to provide a range of new avenues for the market to grow over the forthcoming period. These novel opportunities include a surge in integration for IoT, artificial intelligence, and other advanced technologies coupled with the growing adoption of cloud solutions in several industrial operations. This entails businesses investing in artificial intelligence solutions for their organizations. Artificial intelligence solutions allow businesses to decode and understand the input in an intelligent system which is sometimes difficult for human beings to understand and allow industries to work digitally. This caused many businesses (both large and small) to invest in artificial intelligence to help increase their business continuation post the outbreak of the COVID-19 pandemic. Further, technology companies often deploy technologies like process automation and internet technology to continuously and rapidly provide improved efficiency and reduce network latency during the outburst of the COVID-19 crisis. Such instances are expected to support the growth of the artificial neural network market forecast period.

Key Findings of the Study

• By component, the solution segment accounted for the largest artificial neural network market analysis in 2022.
• By deployment mode, the on-premise segment accounted for the largest artificial neural network market share in 2022.
• By enterprise size, the large enterprises segment accounted for the largest artificial neural network industry share in 2022.
• By industry, the IT segment accounted for the largest artificial neural network market size in 2022.
• Region wise, North America generated the highest revenue in 2022.

The market players operating in the artificial neural network industry are 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. 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.