Market Size

Global AI in Edge Computing Market reached US$ 16.54 billion in 2024 and is expected to reach US$ 83.86 billion by 2032, growing with a CAGR of 22.50% during the forecast period 2025-2032. 

The global Artificial Intelligence (AI) in Edge Computing market is experiencing rapid growth, driven by the increasing demand for real-time data processing and the proliferation of Internet of Things (IoT) devices. The integration of AI capabilities into edge devices is transforming industries by enabling real-time analytics and decision-making at the source of data generation. For instance, McDonald's has implemented AI-powered drive-through systems and internet-connected kitchen equipment to enhance customer service and operational efficiency.

Market Dynamics

Driver - Proliferation of IoT Devices

  • The exponential growth of IoT devices is a significant driver for AI in edge computing. As more devices become interconnected, the volume of data generated increases substantially, necessitating efficient data processing methods.Edge computing addresses this need by enabling data analysis closer to the source, reducing latency and bandwidth requirements.
  • The integration of AI further enhances the ability to derive actionable insights in real-time, making it essential for applications like autonomous vehicles, smart cities, and industrial automation.

Restraint - High Initial Investment and Infrastructure Challenges

  • Implementing AI in edge computing requires substantial initial investments in hardware, software, and network infrastructure. Organizations may face challenges in upgrading existing systems to support edge computing capabilities, and the costs associated with deploying and maintaining these systems can be prohibitive.
  • Additionally, ensuring data security and compliance with regulatory standards adds complexity to the implementation process, potentially hindering the widespread adoption of AI in edge computing solutions.

Market Segment Analysis

The global AI in Edge Computing market is segmented based on component, deployment type, organization size, technology, application, end-use industry, and region.

Industrial Internet of Things (IIoT) represent the largest application segment in the global market. 

The Industrial Internet of Things (IIoT) represents the largest segment within the AI in edge computing market, as industries increasingly adopt connected devices to enhance operational efficiency, safety, and productivity. In the energy sector, edge computing facilitates efficient management of distributed energy resources. General Electric employs edge computing techniques to estimate the lifespan of components in heat recovery steam generators, which are subject to extreme conditions, thereby optimizing maintenance schedules and improving reliability. Furthermore, the transportation industry benefits from edge computing through enhanced vehicle-to-infrastructure communication. In Ulm, Germany, a project involving Bosch and the University of Ulm integrates sensors into traffic infrastructure to assist autonomous vehicles in navigating complex urban environments. 

Market Geographical Share

North America leads the AI in edge computing market, attributed to its advanced technological infrastructure, significant investments in AI research and development, and a robust ecosystem of tech companies.

The region's emphasis on maintaining leadership in AI has led to substantial investments in infrastructure. For instance, Microsoft and BlackRock announced a $30 billion fund to invest in AI infrastructure include data centers and energy project, focusing on enhancing AI capabilities in the United States. The U.S. government has also prioritized self-sufficiency in semiconductor production, as highlighted by the 2022 CHIPS Act, to reduce reliance on foreign manufacturing and bolster domestic AI capabilities.

Moreover, North American companies are at the forefront of integrating AI into edge computing. Qualcomm, for example, is expanding beyond mobile handsets into automotive and IoT sectors, leveraging its Snapdragon platform to deliver AI capabilities at the edge. The company projects its automotive revenue to reach $4 billion by fiscal 2026 and $8 billion by 2029, with IoT revenue expected to grow to $14 billion, reflecting the region's dynamic market landscape. 

Technology Roadmap

The global AI in Edge Computing market is expected to evolve significantly over the coming years, driven by advancements in network infrastructure, the expansion of IoT, and the increasing adoption of artificial intelligence (AI) at the edge. Government initiatives, regulatory frameworks, and private sector investments are set to accelerate AI adoption in cybersecurity across multiple industries.

Technology Roadmap of Global for Mobile Edge Computing

2024

The focus is on enhancing edge computing hardware to support AI workloads, with advancements in specialized processors and energy-efficient designs. Standardization efforts are underway to ensure interoperability among edge devices, facilitating broader adoption across industries.
2028
Edge AI systems have become more autonomous, with improved machine learning models capable of on-device training and adaptation. Integration with 5G networks is widespread, enabling ultra-low latency applications such as autonomous transportation and real-time industrial control systems.
2032
Edge computing and AI are deeply integrated into critical infrastructure, including smart grids, healthcare diagnostics, and next-generation industrial automation. AI-powered edge devices leverage quantum computing advancements to process vast amounts of data in real time, further reducing reliance on centralized cloud computing. 

Major Global Players

The major Global players in the market include NVIDIA, Amazon Web Services, Inc., Arctic Wolf Networks Inc., Tata Consultancy Services, Microsoft Corporation, Infosys, IBM Corporation, Intel Corporation, Cisco Systems, Inc., and Nokia.

Why Choose DataM?

  • Data-Driven Insights: Dive into detailed analyses with granular insights such as pricing, market shares and value chain evaluations, enriched by interviews with industry leaders and disruptors.
  • Post-Purchase Support and Expert Analyst Consultations: As a valued client, gain direct access to our expert analysts for personalized advice and strategic guidance, tailored to your specific needs and challenges.
  • White Papers and Case Studies: Benefit quarterly from our in-depth studies related to your purchased titles, tailored to refine your operational and marketing strategies for maximum impact.
  • Annual Updates on Purchased Reports: As an existing customer, enjoy the privilege of annual updates to your reports, ensuring you stay abreast of the latest market insights and technological advancements. Terms and conditions apply.
  • Specialized Focus on Emerging Markets: DataM differentiates itself by delivering in-depth, specialized insights specifically for emerging markets, rather than offering generalized geographic overviews. This approach equips our clients with a nuanced understanding and actionable intelligence that are essential for navigating and succeeding in high-growth regions.
  • Value of DataM Reports: Our reports offer specialized insights tailored to the latest trends and specific business inquiries. This personalized approach provides a deeper, strategic perspective, ensuring you receive the precise information necessary to make informed decisions. These insights complement and go beyond what is typically available in generic databases.

Target Audience 2024

  • Manufacturers/ Buyers
  • Industry Investors/Investment Bankers
  • Research Professionals
  • Emerging Companies