<img src="https://ml.globenewswire.com/Resource/Download/908fb457-7f8e-4a08-9081-5565e3dfb3d7?size=2" nborder="0" align="left" hspace="5" vspace="5" title="22157.jpg" alt="Company Logo"/>Dublin, Aug. 12, 2026 <a href="https://www.globenewswire.com" target="_blank">(GLOBE NEWSWIRE)</a> -- The <a href="https://www.researchandmarkets.com/reports/5396891/artificial-intelligence-of-things-solutions-by?utm_source=GNE&amp;utm_medium=PressRelease&amp;utm_code=kr7z38&amp;utm_campaign=2324670+-+AI+of+Things+(AIoT)+Solutions+Market+Outlook+Report+2026-2030+%7c+Agentic+AI+and+IoT+Convergence+Accelerates+Autonomous+Decision-Making+Across+Global+Industries&amp;utm_exec=jocamsai" rel="nofollow" target="_blank" title="Artificial Intelligence of Things Solutions by AIoT Market Applications and Services in and Industry Verticals 2026-2030">"Artificial Intelligence of Things Solutions by AIoT Market Applications and Services in and Industry Verticals 2026-2030"</a> has been added to ResearchAndMarkets.com's offering. Agentic AI is advancing the Internet of Things (IoT) from rules-based automation toward autonomous, goal-directed operations. The convergence of artificial intelligence and connected devices-commonly associated with the Artificial Intelligence of Things (AIoT)-enables enterprise, industrial, and consumer systems to evaluate real-time conditions, anticipate operational consequences, and take corrective action with limited human intervention. This transition is supporting the growth of Decisions as a Service (DaaS), through which organizations can access AI-powered operational decisions via application programming interfaces, cloud platforms, edge infrastructure, and managed services. DaaS solutions may be customized by industry, business objective, transaction volume, or measurable outcome. From Rules-Based Automation to Autonomous IoT Operations Traditional IoT deployments generally depend on static thresholds and predefined workflows. Agentic IoT systems apply contextual analysis, probabilistic reasoning, and continuous optimization to pursue defined objectives across dynamic physical environments. <ul><li>Autonomous operations: AI agents evaluate sensor data, environmental conditions, historical patterns, and operational constraints before initiating actions.</li><li>Adaptive optimization: Connected systems monitor results, identify deviations, and modify their behavior to improve performance.</li><li>Real-time decision services: AI models support operational choices through edge computing, cloud platforms, software-as-a-service applications, and managed AIoT services.</li></ul> AIoT Applications Across Key Industry Sectors Agentic AI can transform passive IoT data networks into responsive, self-managing systems. High-value applications are emerging across manufacturing, utilities, energy, transportation, logistics, smart cities, product delivery, customer support, sales, and supply chain management. <ul><li>Predictive maintenance: AI agents detect equipment anomalies, assess failure risks, initiate parts procurement, and coordinate technician schedules.</li><li>Smart grid management: Autonomous systems forecast demand, balance energy distribution, integrate distributed resources, and support market-based power transactions.</li><li>Supply chain logistics: Connected vehicles and logistics platforms optimize routes using weather conditions, port congestion, inventory availability, delivery priorities, and network capacity.</li><li>Product lifecycle management: IoT-generated intelligence supports design improvements, performance monitoring, service delivery, and customer-facing operations.</li></ul> Utilities and energy service providers are expected to lead adoption because of their reliance on continuous data, distributed infrastructure, real-time balancing, and predictive analytics. AIoT capabilities will also become increasingly common within connected enterprise infrastructure, analytics platforms, software solutions, and SaaS-managed service offerings. Streaming Data, Edge Computing, and AIoT Analytics The expansion of IoT networks is generating substantial volumes of structured and unstructured machine data. Combined with human-generated information, these data streams create significant opportunities for AI-powered analytics, operational intelligence, and automated decision-making. Real-time data processing will remain central to the AIoT market. Organizations require the ability to capture streaming data, identify relevant attributes, apply contextual intelligence, and execute decisions with minimal delay. Edge computing will be particularly important for industrial systems and other use cases in which latency, connectivity, resilience, and local processing directly affect operational performance. In many deployments, data and actionable intelligence will become services in their own right. AIoT infrastructure will support more efficient connected operations, improved human-machine interaction, advanced data management, IoT Data as a Service, and AI-based Decisions as a Service. AIoT Adoption Challenges Deploying autonomous AI agents across physical infrastructure introduces significant technical, security, governance, and operational requirements. <ul><li>Latency: Time-sensitive applications may require edge processing when cloud-dependent architectures cannot meet response requirements.</li><li>Safety and reliability: Industrial environments require predictable performance, rigorous validation, and appropriate human oversight for probabilistic AI systems.</li><li>Cybersecurity: Compromised agents could affect valves, locks, vehicles, machinery, energy systems, and other connected assets, converting digital vulnerabilities into physical risks.</li><li>Governance: Enterprises must establish accountability, auditability, access controls, data policies, and escalation procedures for autonomous decisions.</li></ul> AIoT Market Report and Forecast, 2026-2030 This AIoT market report analyzes enabling technologies, leading companies, competitive solutions, infrastructure, services, and industry-specific applications. It includes quantitative market sizing and forecasts for AIoT infrastructure, managed services, platforms, and selected solutions from 2026 through 2030. The report also evaluates the relationship between 5G and AIoT, the role of blockchain in connected ecosystems, and market opportunities for Data as a Service, Decisions as a Service, and AIoT solutions for smart cities. As enterprises prioritize automation and digital transformation, the integration of Agentic AI with IoT is positioned to become an increasingly important component of global business operations. Key Topics Covered 1. Executive Summary 2. Introduction 2.1 Defining AIoT 2.1.1 AI in IoT vs. AIoT 2.2 Artificial General Intelligence 2.2.1 Ambient Intelligence and Smart Lifestyles 2.3 IoT Network and Functional Structure 2.3.1 Economic and Social Impact 2.3.2 Enterprise Adoption and Investment 2.4 AIoT Market Dynamic Analysis 2.4.1 Market Drivers and Opportunities 2.4.2 Market Restraints and Challenges 2.5 AIoT Value Chain Analysis 2.5.1 Device Manufacturers 2.5.2 Equipment Manufacturers 2.5.3 Platform Providers 2.5.4 Software and Service Providers 2.5.5 User Communities 3. Technology and Application Analysis 3.1 AIoT Market Analysis 3.1.1 Equipment and Component 3.1.2 Cloud Equipment and Deployment 3.1.3 3D Sensing Technology 3.1.4 Software and Data Analytics 3.1.5 AIoT Platforms 3.1.6 Deployment and Services 3.2 AIoT Sub-Market Analysis 3.2.1 Supporting Device and Connected Objects 3.2.2 IoT Data as a Service 3.2.3 AI Decisions as a Service 3.2.4 APIs and Interoperability 3.2.5 Smart Objects 3.2.6 Smart City Considerations 3.2.7 Industrial Transformation 3.2.8 Cognitive Computing and Computer Vision 3.2.9 Consumer Appliances 3.2.10 Domain Specific Network Considerations 3.2.11 3D Sensing Applications 3.2.12 Predictive 3D Design 3.3 AIoT Technology Analysis 3.3.1 Cognitive Computing 3.3.2 Computer Vision 3.3.3 Machine Learning Capabilities and APIs 3.3.3.1 Deep Machine Learning 3.3.3.2 Machine Learning APIs 3.3.4 Neural Networks 3.3.5 Context Aware Processing 3.4 AIoT Enabling Technology Analysis 3.4.1 Edge Computing 3.4.1.1 AIoT Edge Architecture 3.4.1.2 Edge AI Platform 3.4.2 Blockchain Networks 3.4.3 Cloud Technologies 3.4.4 5G Technologies 3.4.5 Digital Twin Technology and Solutions 3.4.6 Smart Machines 3.4.7 Cloud Robotics 3.4.8 Predictive Analytics and Real Time Processing 3.4.8.1 All Flash Array 3.4.8.2 Real Time Operating Systems (RTOS) 3.4.9 Post Event Processing 3.4.10 Haptic Technology 3.5 AIoT Applications Analysis 3.5.1 Device Accessibility and Security 3.5.2 Gesture Control and Facial Recognition 3.5.3 Home Automation 3.5.4 Wearable Device 3.5.5 Fleet Management 3.5.6 Intelligent Robots 3.5.7 Augmented Reality Market 3.5.8 Drone Traffic Monitoring 3.5.9 Real-time Public Safety 3.5.10 Yield Monitoring and Soil Monitoring Market 3.5.11 HCM Operation 4. AIoT Company Analysis 4.1 Sharp Corporation 4.2 SAS Institute Inc. 4.3 DT42 Co. Ltd. 4.4 Baidu Inc. 4.5 Alibaba Group Holding Limited 4.6 Tencent 4.7 Xiaomi 4.8 NVIDIA Corporation 4.9 Intel Corporation 4.10 Qualcomm Technologies Inc. 4.11 Innodisk Corporation 4.12 GBT Technologies 4.13 Micron Technology Inc. 4.14 ShiftPixy 4.15 Uptake Technologies Inc. 4.16 C3 AI Inc. 4.17 Alluvium IoT Solutions Pvt Ltd. 4.18 Arundo (Stanford Startx Company) 4.19 Canvass Analytics Inc. 4.20 Falkonry Inc. 4.21 Interactor 4.22 Google (DeepMind) 4.23 Cisco Systems 4.24 IBM Corporation 4.25 Microsoft Corporation 4.26 Apple Inc. 4.27 Salesforce Inc. 4.28 Infineon Technologies AG (Cypress Semiconductor) 4.29 Amazon Inc. 4.30 AB Electrolux 4.31 ABB Ltd. 4.32 AIBrian Inc. 4.33 Analog Devices Inc. 4.34 ARM Limited 4.35 Atmel Corporation (Microchip Technology) 4.36 Ayla Networks Inc. 4.37 Brighterion Inc. 4.38 Buddy (Blue Frog Robotics) 4.39 CloudMinds 4.40 Cumulocity IoT (Software AG) 4.41 Smarsh Inc. (Digital Reasoning Systems) 4.42 Enea AB 4.43 Express Logic Inc. (Microsoft Corporation) 4.44 Meta Platform Inc. (Facebook) 4.45 Fujitsu Ltd. 4.46 Thales Group (Gemalto N.V.) 4.47 General Electric (GE) 4.48 General Vision Services 4.49 Graphcore 4.50 H2O.ai 4.51 Haier Group 4.52 Helium Systems 4.53 Hewlett Packard Enterprise 4.54 Huawei Technologies 4.55 Siemens AG 4.56 SK Telecom 4.57 SoftBank Robotics 4.58 SpaceX 4.59 SparkCognition 4.60 STMicroelectronics 4.61 Broadcom Inc. (Symantec) 4.62 Tellmeplus (OVHCloud) 4.63 Tesla Inc. 4.64 Texas Instruments 4.65 Thethings.io 4.66 Veros Systems (Baker Hughes Company) 4.67 Whirlpool Corporation 4.68 Wind River Systems Inc. 4.69 Juniper Networks Inc. 4.70 Nokia Corporation 4.71 Oracle Corporation 4.72 PTC Corporation (ServiceMax) 4.73 Losant IoT 4.74 Robert Bosch GmbH 4.75 Pepper 4.76 Terminus Group 4.77 Tuya Inc. 4.78 NXP Semiconductors (Freescale Semiconductor) 4.79 Axiomtek Co. Ltd. 4.80 Pinnacle Solutions Inc. 4.81 Schneider Electric 4.82 TCL Technology 4.83 GREE Electric Appliances Inc. 4.84 Hisense International 4.85 Lenovo 4.86 Midea 5. AIoT Market Analysis and Forecasts 2026-2030 5.1 AIoT Market 2026-2030 5.1.1 Global AIoT Market 2026-2030 5.1.2 Global AIoT Market by Segment 5.1.2.1 Global AIoT Market by Infrastructure Type 5.1.2.1.1 Global AIoT Market by Chipset Type 5.1.2.1.1.1 Global AIoT Market by 3D Sensing Technology 5.1.2.1.1.2 Global AIoT Market by 3D Sensing Application 5.1.2.1.2 Global AIoT Market by Cloud Infrastructure Type 5.1.2.2 Global AIoT Market by Software and Platform Type 5.1.2.2.1 Global AIoT Market by Analytics Software Type 5.1.2.3 Global AIoT Market by Service Type 5.1.2.3.1 Global AIoT Market by Professional Service Type 5.1.3 Global AIoT Market by AI Technology 5.1.4 Global AIoT Market by Application 5.1.5 Global AIoT Market by IoT Sector 5.1.6 Global AIoT Market by City vs. Rural Zone 5.1.7 Global AIoT Market by Deployment 5.1.8 Global AIoT Market by Marketing Channel 5.1.9 Global AIoT Market by Enterprise Size 5.1.10 Global AIoT Market by Industry Vertical 5.1.11 Global Smart City Market in AIoT 5.1.12 Global IoT Data as a Service Market in AIoT 5.1.13 Global AI Decision as a Service Market in AIoT 5.1.14 Global Blockchain Driven AIoT Market 5.1.15 Global 5G Driven AIoT Market 5.1.16 Global AIoT Market by Region 5.1.16.1 North America AIoT Market by Country 5.1.16.2 APAC AIoT Market by Country 5.1.16.3 Europe AIoT Market by Country 5.1.16.4 MEA AIoT Market by Country 5.1.16.5 Latin America AIoT Market by Country 5.2 Regional AIoT Market 2026-2030 5.2.1 North America AIoT Market by Infrastructure, Platform, Service, Technology, Application, Deployment, Marketing Channel, Industry Vertical, Smart City, IoT DaaS, AI Decision Service, Blockchain, and 5G 5.2.2 APAC AIoT Market by Infrastructure, Platform, Service, Technology, Application, Deployment, Marketing Channel, Industry Vertical, Smart City, IoT DaaS, AI Decision Service, Blockchain, and 5G 5.2.3 Europe AIoT Market by Infrastructure, Platform, Service, Technology, Application, Deployment, Marketing Channel, Industry Vertical, Smart City, IoT DaaS, AI Decision Service, Blockchain, and 5G 5.2.4 MEA AIoT Market by Infrastructure, Platform, Service, Technology, Application, Deployment, Marketing Channel, Industry Vertical, Smart City, IoT DaaS, AI Decision Service, Blockchain, and 5G 5.2.5 Latin America AIoT Market by Infrastructure, Platform, Service, Technology, Application, Deployment, Marketing Channel, Industry Vertical, Smart City, IoT DaaS, AI Decision Service, Blockchain, and 5G 5.3 AIoT Deployment Unit 2026-2030 5.3.1 Global AIoT Deployment Unit 2026-2030 5.3.2 Global AIoT Deployment Unit by Segment 5.3.2.1 Global AIoT Deployment Unit by Infrastructure Type 5.3.2.1.1 Global AIoT Deployment Unit by Chipset Type 5.3.2.1.2 Global AIoT Deployment Unit by Cloud Infrastructure Type 5.3.2.2 Global AIoT Deployment Unit by Software and Platform Type 5.3.3 Global AIoT Deployment Unit by Region 5.3.3.1 North America AIoT Deployment Unit by Country 5.3.3.2 APAC AIoT Deployment Unit by Country 5.3.3.3 Europe AIoT Deployment Unit by Country 5.3.3.4 MEA AIoT Deployment Unit by Country 5.3.3.5 Latin America AIoT Deployment Unit by Country 5.4 Regional AIoT Deployment Unit 2026-2030 5.4.1 North America AIoT Deployment Unit by Infrastructure and Software Platform 5.4.2 APAC AIoT Deployment Unit by Infrastructure and Software Platform 5.4.3 Europe AIoT Deployment Unit by Infrastructure and Software Platform 5.4.4 MEA AIoT Deployment Unit by Infrastructure and Software Platform 5.4.5 Latin America AIoT Deployment Unit by Infrastructure and Software Platform For more information about this report visit <a href="https://www.researchandmarkets.com/reports/5396891/artificial-intelligence-of-things-solutions-by?utm_source=GNE&amp;utm_medium=PressRelease&amp;utm_code=kr7z38&amp;utm_campaign=2324670+-+AI+of+Things+(AIoT)+Solutions+Market+Outlook+Report+2026-2030+%7c+Agentic+AI+and+IoT+Convergence+Accelerates+Autonomous+Decision-Making+Across+Global+Industries&amp;utm_exec=jocamsai" rel="nofollow" target="_blank" title="">https://www.researchandmarkets.com/r/sww1xj</a> About ResearchAndMarkets.com ResearchAndMarkets.com is the world's leading source for international market research reports and market data. 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AI of Things (AIoT) Solutions Market Outlook Report 2026-2030 | Agentic AI and IoT Convergence Accelerates Autonomous Decision-Making Across Global Industries

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