Neural Network Market Size, Share, & Trends Analysis Report By Component, By Vertical, By Region, And Segment Forecasts, 2022 To 2030

The global neural network market size will grow with the rising adoption of cloud-based solutions to automate equipment maintenance processes. The growing prominence of artificial neural networks (ANN) comes on the back of scalability, easy maintenance of generated data, and effective management. Soaring demand for ANN in data mining, signal recognition, image recognition, and drug discovery will bode well for the industry’s growth.

Neural networks have become popular as simulated neural networks (SNNs) and artificial neural networks (ANNs). ANN works similar to the human brain and through the emulation of the latter’s functions, the former plays a pivotal role in developing computational models equipped for pattern recognition. With the complexity of neural networks surging, ANN has become sought-after across healthcare, retail, aerospace & defense, and energy & utilities, among others. For instance, the technology has gained ground in the petroleum industry to assess data regarding possible oil reserves, for drill bit diagnosis, seismic pattern recognition, optimization of good performance, and enhancing gas well production. The industry growth is mainly attributed to real-time operation, adaptive learning, redundant information coding through fault tolerance, and self-organization.

Neural Network Market Segmentation

Expanding the application of artificial neural networks across natural language processing, chatbots, drug discovery, and stock market prediction applications have made the technology trendier across emerging and advanced economies. Integration of deep learning facilities and AI with the existing ANN solution will encourage leading companies to prioritize investments in neural network software and services.

In terms of components, the neural network service will witness strong demand in the wake of expanding penetration of remote training, custom software development, and enterprise resource planning. The ANN service also provides accuracy and quality in results along with good fault tolerance and cost benefits.

With respect to vertical, the IT & telecom sector will exhibit profound demand for neural network software and services, mainly due to the rising penetration of cloud computing solutions. Besides, the trend for PaaS, Security as a Service (SECaaS), and Function as a Service (FaaS) across the IT sector will augur well for leading companies striving to boost neural network market growth. Furthermore, Convolutional Neural Network (CNN) has become sought-after in AI applications, including natural language processing, text digitization, facial recognition, signal processing, and paraphrase detection.

The healthcare sector has showcased increased traction for ANNs in diagnosis systems to detect cancer and heart problems. Healthcare organizations are expected to explore opportunities in neural networks to boost patient care and streamline healthcare management decisions. Industry players are likely to bank on artificial neural networks to boost patient-centered and value-based models of care delivery.

North America accounts for a significant share of the global market against the backdrop of robust adoption from aerospace & defense, healthcare, and energy & utility sectors. Prominently, the aerospace and defense sector across the U.S. and Canada have upped research on ANN. To illustrate, in May 2020, Airbus noted that a flexible neural network was needed for Airbus-Dassault Aviation Future Combat Air System (FCAS).

As most research focuses on CNN input for AI-powered software development, the neural network will continue to gain prominence across the region. Moreover, convolutional neural networks have set the trend to automate the aircraft maintenance visual inspection process. With aerospace manufacturers becoming more resilient, agile, and smart, the aerospace neural network could witness compelling trends.

Industry players anticipate to invest in organic and inorganic strategies to boost their market penetration across untapped areas. In doing so, the leading companies could invest in mergers & acquisitions, research and development activities, product launches, and product rollouts. For instance, in November 2021, Google reported to having developed a new AI model that could reshape medical research. The team of researchers at Google claimed the model could help develop a neural network to boost clinical diagnosis efficiency.