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How big is the artificial neural network market today, and what are its future growth expectations?
The artificial neural network market size has grown rapidly in recent years. It will grow from $0.49 billion in 2024 to $0.58 billion in 2025 at a compound annual growth rate (CAGR) of 17.80%. The growth in the historic period can be attributed to increasing cyberattacks, increased demand for AI and automation, growth in self-sustained systems, increased adoption of the Internet of Things (IoT), and increased cloud adoption.
The artificial neural network market size is expected to see rapid growth in the next few years. It will grow to $1.11 billion in 2029 at a compound annual growth rate (CAGR) of 17.44%. The growth in the forecast period can be attributed to rising demand for artificial intelligence (AI) across industries, increasing demand for cloud-based services, increasing use of voice assistants and conversational AI, increasing usage in drug discovery and healthcare, and rising big data volume. Major trends in the forecast period include advancements in machine learning and neural networks, integration with big data and analytics, connectivity with IoT and edge computing, hybrid cloud and edge integration, and integration with 5G networks.
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What have been the primary factors driving the artificial neural network market’s growth?
The increasing demand for cloud-based solutions is expected to propel the growth of the artificial neural network market going forward. A cloud-based solution refers to a service or application that operates on remote servers accessed via the internet, rather than being hosted on local servers or devices. The increasing demand for cloud-based solutions is attributed to their scalability, cost efficiency, enhanced data accessibility, and support for remote collaboration, which meet the evolving needs of modern businesses. Artificial neural networks enhance cloud-based solutions by enabling advanced data processing, predictive analytics, and intelligent decision-making capabilities for optimized performance and scalability. For instance, in December 2023, Eurostat, a Luxembourg-based government agency in the EU, reported that the proportion of enterprises purchasing cloud computing services rose by 4.2 percentage points in 2023 compared to 2021. Therefore, the increasing demand for cloud-based solutions is driving the growth of the artificial neural network (ANN) market.
What are the key segments within the artificial neural network market?
The artificial neural network market covered in this report is segmented –
1) By Component: Solutions, Platform Or Application Programming Interface (API), Services
2) By Deployment Mode: On-Premises, Cloud
3) By Enterprise: Large Enterprises, Small And Medium Enterprises
4) By Application: Image Recognition, Signal Recognition, Data Mining
5) By End-User: Banking, Financial Services, and Insurance (BFSI), Retail And E-Commerce, IT And Telecom, Manufacturing, Healthcare, Automotive
Subsegments:
1) By Solutions: Software Solutions, Hardware Solutions, Deployment Solutions, Data Management Solutions
2) By Platform Or Application Programming Interface (API): Cloud-Based Platforms, On-Premise Platforms, Open-Source APIs, Proprietary APIs
3) By Services: Consulting Services, Integration And Deployment Services, Support And Maintenance Services, Managed Services
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Which key players are shaping the artificial neural network market?
Major companies operating in the artificial neural network market are Google Inc., Microsoft Corporation, Amazon Web Services Inc., Intel Corporation, IBM Corporation, Qualcomm Technologies Inc., Oracle Corporation, SAP SE, Hewlett Packard Enterprise Development LP, NVIDIA Corporation, Salesforce Inc., Rockwell Automation Inc., OpenAI Inc., H2O.ai Inc., Anaconda Inc., Clarifai Inc., Neurala Inc., Ward Systems Group, BrainChip Holdings Ltd., NeuroDimension Inc.
How will emerging trends drive the artificial neural network market throughout the forecast period?
Major companies operating in the artificial neural network market are focusing on developing innovative platforms, such as AI-based networking platforms, to enhance data processing capabilities, improve predictive analytics, and optimize machine learning models, thereby enabling more efficient and scalable solutions across industries like healthcare, finance, and automotive. AI-based networking platforms refer to advanced systems that integrate artificial intelligence with networking technologies to optimize data flow, enhance network management, and improve overall performance. For instance, in February 2022, the International Telecommunication Union, a Switzerland-based specialized agency, launched the AI for Good neural network, a groundbreaking platform aimed at advancing sustainable development through artificial intelligence. This platform integrates advanced AI algorithms to tackle global challenges such as climate change, poverty, and health disparities. Its key feature is the ability to process and analyze large datasets from diverse sources, delivering valuable insights that enable governments, organizations, and researchers to make informed decisions. The platform also emphasizes collaboration, bringing together experts from different sectors to develop innovative, scalable solutions for sustainable growth, all while aligning with the UN’s Sustainable Development Goals (SDGs).
How do regional factors impact the artificial neural network market, and which region is the largest contributor?
North America was the largest region in the artificial neural network market in 2024.Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the artificial neural network market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
What Does The Artificial Neural Network Market Report 2025 Offer?
The artificial neural network market research report from The Business Research Company offers global market size, growth rate, regional shares, competitor analysis, detailed segments, trends, and opportunities.
An artificial neural network (ANN) refers to a machine learning architecture that mimics the human brain’s neural structure to process data and recognize patterns. It consists of layers of interconnected nodes, including input, hidden, and output layers, which work together to transform input data into meaningful outputs through weighted connections.
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