Artificial Intelligence Of Things (AIoT) Market Size and Share
Market Overview
| Study Period | 2019 - 2030 |
| Market Size (2025) | USD 35.10 Billion |
| Market Size (2030) | USD 89.38 Billion |
| Growth Rate (2025 - 2030) | 20.56% CAGR |
| Fastest Growing Market | North America |
| Largest Market | Asia Pacific |
| Market Concentration | Medium |
Major Players*Disclaimer: Major Players sorted in no particular order Image © Mordor Intelligence. Reuse requires attribution under CC BY 4.0. |
|
Artificial Intelligence Of Things (AIoT) Market Analysis by Mordor Intelligence
The Artificial Intelligence of Things market is valued at USD 35.10 billion in 2025 and is forecast to advance to USD 89.38 billion by 2030, reflecting a 20.56% CAGR. Rapid convergence of AI models with sensor-rich IoT endpoints is shifting deployments from reactive monitoring to autonomous, edge-native intelligence. Volume manufacturing of low-cost AI chipsets, hyperscaler investment in AI-centric cloud services, and rising enterprise demand for predictive operations continue to expand addressable use cases. Semiconductor leaders such as NVIDIA recorded 78% year-over-year revenue growth to USD 39.3 billion in Q4 2025 on the back of AI infrastructure demand. Integration complexity is simultaneously creating a sizable services opportunity as organizations seek specialist partners to knit AI algorithms, networking, and domain workflows into unified solutions. Regulatory frameworks such as the EU AI Act are driving “privacy-by-design” architectures that favor distributed processing and standards-based interoperability.
Key Report Takeaways
- By component, software platforms led with 48.44% revenue share in 2024; services are projected to expand at a 32.40% CAGR to 2030.
- By deployment model, cloud-based solutions held 57.50% of the Artificial Intelligence of Things market share in 2024, while edge implementations are forecast to grow at 38.60% CAGR through 2030.
- By application, video surveillance maintained 24.63% share of the Artificial Intelligence of Things market size in 2024; autonomous mobility is advancing at a 44.10% CAGR to 2030.
- By industry vertical, manufacturing accounted for 28.70% of 2024 revenue, whereas healthcare is the fastest-growing segment at 36.90% CAGR.
- By technology stack, machine learning represented 41.23% share in 2024; natural language processing records the strongest growth at 29.70% CAGR.
- By geography, North America commanded 42.61% revenue share in 2024; APAC is projected to rise at a 28.53% CAGR to 2030.
Global Artificial Intelligence Of Things (AIoT) Market Trends and Insights
Drivers Impact Analysis
| Driver | ( ~ ) % Impact on CAGR Forecast | Geographic Relevance | Impact Timeline |
|---|---|---|---|
| Edge-AI hardware cost declines accelerate adoption | +4.2% | Global, Asia-Pacific manufacturing leads | Medium term (2-4 years) |
| Roll-out of 5G / 6G networks enabling ultra-low latency | +3.8% | North America and EU early, Asia-Pacific mass | Long term (≥ 4 years) |
| Growing enterprise spend on predictive-maintenance AIoT suites | +3.1% | Germany, China, United States | Short term (≤ 2 years) |
| AIoT-ready chipsets embedded in consumer devices | +2.9% | North America, China | Medium term (2-4 years) |
| Low-Earth-Orbit satellite IoT links unlock remote assets | +1.8% | Australia, Canada, Brazil | Long term (≥ 4 years) |
| Government-backed smart-city programs fuel infrastructure modernisation | +1.5% | China, India, GCC states | Medium term (2-4 years) |
Source: Mordor Intelligence
Edge-AI hardware cost declines accelerate adoption
Ongoing price reductions in edge inference silicon are reshaping cost–benefit equations across industrial and consumer deployments. Intel’s 2024 partnership with Qualcomm to co-engineer wireless AI modules exemplifies cross-vendor moves that compress bill-of-materials while boosting on-device processing efficiency.[1]Qualcomm Incorporated, “Qualcomm–Intel Wireless AI Collaboration,” qualcomm.com Manufacturers are now able to execute complex predictive algorithms locally, lowering cloud compute fees and avoiding latency-induced downtime.
Roll-out of 5G / 6G networks enabling ultra-low latency
Telecom operators are layering AI-optimized transport slices onto 5G cores and launching initial 6G research beds, creating the bandwidth and deterministic latency critical for autonomous mobility and remote robotics. Cisco’s AI-powered predictive network automation roadmap underscores how transport upgrades and network intelligence combine to support real-time AIoT workloads.[2]Cisco Systems, “Cisco Networking Cloud and Nexus HyperFabric,” cisco.com
Growing enterprise spend on predictive-maintenance AIoT suites
Industrial majors are scaling sensor networks and analytics bundles to cut unplanned shutdowns. Honeywell’s collaboration with Google Cloud to build autonomous plant agents demonstrates the ROI narrative now driving board-level funding for AI-enabled maintenance programs.[3]Honeywell International, “Honeywell and Google Cloud Expand AI Partnership,” honeywell.com
AIoT-ready chipsets embedded in consumer devices
Device makers increasingly integrate dedicated inference engines into wearables, smart appliances, and in-vehicle infotainment. Qualcomm and Palantir extended their edge analytics partnership in March 2025 to deliver lightweight, on-device AI pipelines that reduce backhaul traffic and preserve user privacy.
Restraints Impact Analysis
| Restraint | ( ~ ) % Impact on CAGR Forecast | Geographic Relevance | Impact Timeline |
|---|---|---|---|
| Scarcity of AIoT-skilled systems integrators | –2.8% | Emerging markets, mid-tier cities | Short term (≤ 2 years) |
| Fragmented edge-cloud standards hinder interoperability | –2.1% | Global multi-vendor sites | Medium term (2-4 years) |
| Rising privacy-preserving-AI compliance costs | –1.9% | EU first, extending to APAC | Long term (≥ 4 years) |
| EU AI Act compliance raises documentation overhead | –1.5% | Europe, exporters to EU | Medium term (2-4 years) |
Source: Mordor Intelligence
Scarcity of AIoT-skilled systems integrators
Deployments require rare combinations of ML engineering, industrial protocols, and domain know-how. Limited talent pools inflate project costs and elongate roll-outs, especially for mid-market manufacturers outside major tech hubs.
Fragmented edge-cloud standards hinder interoperability
ISO/IEC 27402 offers baseline security rules, yet comprehensive interoperability guidance remains patchy. Enterprises often lock into single-vendor stacks early, increasing switching costs and dampening ecosystem experimentation.
Segment Analysis
By Component: Software platforms drive integration complexity
Software accounted for 48.44% revenue in 2024, underpinning orchestration, AI model management, and data integration across distributed assets. Services are tracking a 32.40% CAGR as enterprises outsource end-to-end solution design to bridge IT-OT silos. Hardware price deflation is commoditizing edge nodes, pushing differentiation up-stack into software value layers. The Artificial Intelligence of Things market size for software is expected to widen as algorithm marketplaces and domain-specific model libraries scale commercially. Services growth mirrors client demand for bespoke connectors, security hardening, and lifecycle governance.
Note: Segment shares of all individual segments available upon report purchase
By Deployment Model: Edge computing gains strategic priority
Cloud architectures retained 57.50% of 2024 spending, yet edge deployments lead growth at 38.60% CAGR as latency-sensitive workloads migrate nearer to machines. Enterprises are adopting hybrid blueprints that dynamically split inference between local and central compute based on bandwidth, privacy, and energy constraints. Cisco’s Nexus HyperFabric clusters exemplify converged designs that house GPUs and high-speed Ethernet in the same rack, giving customers optionality to shift workloads without re-architecting estates. This flexibility is steering procurement roadmaps toward composable, vendor-agnostic stacks that decouple data gravity from algorithm performance.
By Application: Autonomous mobility reshapes transportation intelligence
Video surveillance held 24.63% revenue in 2024, benefiting from mature camera ecosystems and incremental AI add-ons. Autonomous mobility posts the fastest expansion at 44.10% CAGR, propelled by regulatory pilots and falling LiDAR costs. Waymo’s scaled robo-taxi operations and Tesla’s in-house full-self-driving stack reveal how mileage accumulation accelerates model refinement. Logistics fleets and municipal transit agencies are extending proof-of-concepts into full production, embedding edge inference units that fuse sensor data for sub-millisecond path planning.
By Industry Vertical: Healthcare digitization accelerates AIoT adoption
Manufacturing contributed 28.70% of 2024 turnover through predictive maintenance, quality analytics, and adaptive robotics. Healthcare, advancing at 36.90% CAGR, is leveraging remote patient monitoring, AI-augmented diagnostics, and hospital asset tracking to alleviate clinician workloads and improve outcomes. Regulatory approvals for software-as-a-medical-device (SaMD) and reimbursement for tele-cardiology services are reinforcing capital allocation into connected care platforms across the Artificial Intelligence of Things market. Energy, utilities, and agriculture sectors continue to introduce sensor-driven optimisation but trail healthcare in relative growth momentum.
Note: Segment shares of all individual segments available upon report purchase
By Technology Stack: Natural language processing enables human-centric interfaces
Machine learning dominated 41.23% of the 2024 stack, underpinning anomaly detection and optimisation logic. Natural language processing now registers the strongest CAGR at 29.70% as conversational interfaces and voice-activated controls democratise access to complex industrial systems. Cisco embedded NLP into network management consoles to simplify policy configuration, allowing operations staff to pose plain-English queries rather than scripting CLI commands. Computer vision and reinforcement learning also deepen penetration in autonomous inspection drones and adaptive supply-chain routing respectively.
Geography Analysis
North America led with 42.61% revenue in 2024, supported by advanced connectivity, a dense venture capital base, and federal AI research incentives. United States manufacturers deploy factory-floor analytics to offset labour shortages, while Canada’s privacy regulations drive early adoption of federated-learning frameworks in healthcare. Mexico’s maquila segment is integrating edge AI nodes to streamline cross-border logistics flows.
APAC is the fastest-growing region at 28.53% CAGR to 2030. China’s extensive industrial parks and Belt and Road trade corridors require predictive visibility across multimodal freight networks, spurring bulk procurement of embedded AI gateways. Japan scales service-robot fleets to assist an ageing population, pairing computer vision with dexterous manipulators in elder-care facilities. India’s Digital India program fast-tracks smart-city tenders that bundle AI traffic management, solid-waste analytics, and e-health kiosks under unified command platforms.
Europe balances innovation with stringent governance. The EU AI Act imposes transparency and risk-management mandates that encourage secure-by-design tooling. Germany’s automotive OEMs deploy GPU-rich edge clusters on shop floors for real-time welding inspection, while the United Kingdom channels industrial strategy funds into AIoT cyber-resilience hubs. Middle East oil producers digitalise upstream assets using satellite backhaul and edge vision processing to improve worker safety and trim carbon footprints.
Competitive Landscape
Competitive intensity remains moderate. Cloud hyperscalers—AWS, Microsoft, Google—bundle AI, device orchestration, and ingestion pipelines into subscription packages, driving platform stickiness. NVIDIA dominates accelerator silicon, prompting alliance strategies among networking and server vendors; Cisco’s Ethernet-based Spectrum-X fabric integrates NVIDIA’s Silicon One ASICs to deliver deterministic AI cluster throughput. Industrial incumbents such as Siemens and GE Digital embed vertical expertise into domain-focused offerings that compete less on raw compute and more on workflow optimisation.
Partnership ecosystems are replacing bilateral vendor lock-ins. SAP embedded generative AI into 50% of 2024 cloud orders, using its ERP install base to propagate AIoT features like asset-centric digital twins and predictive spare-parts logistics. Semiconductor players court software partners to differentiate beyond frames-per-second benchmarks, as shown by STMicroelectronics and Qualcomm co-developing wireless AI reference designs for battery-constrained endpoints. Start-ups target niche gaps: edge-native privacy engines, ultra-low-power inference kernels, or vertical-specific compliance tooling. ISO/IEC 42001 governance certification creates an on-ramp for specialist auditors that help suppliers align lifecycle processes with regulatory expectations.
Artificial Intelligence Of Things (AIoT) Industry Leaders
-
Amazon Web Services
-
Microsoft Corp.
-
Google LLC
-
IBM Corp.
-
Cisco Systems
- *Disclaimer: Major Players sorted in no particular order
Recent Industry Developments
- March 2025: Qualcomm and Palantir extended their collaboration to fuse ontology-based analytics with edge System-on-Chip platforms for factory automation.
- June 2025: Cisco launched AI Canvas and Nexus Dashboard upgrades to streamline secure AIoT fabric deployment across retail and healthcare campuses.
- October 2024: STMicroelectronics and Qualcomm entered a wireless IoT alliance integrating Qualcomm RF IP with ST’s STM32 microcontrollers for industrial and consumer devices.
- August 2024: Advantech and Momenta’s AIoT Ecosystem Fund invested in Axiom Cloud to scale refrigeration digital twins that lower energy consumption in grocery chains.
Global Artificial Intelligence Of Things (AIoT) Market Report Scope
AIoT integrates the connectivity offered by the Internet of Things (IoT) with the insights derived from Artificial Intelligence (AI). This innovative technology relies on incorporating Artificial Intelligence within the IoT framework.
The study tracks the revenue accrued through the sale of Artificial Intelligence of Things (AIoT) solutions and services by various players in the global market. The study also tracks the key market parameters, underlying growth influencers, and major vendors operating in the industry, which supports the market estimations and growth rates over the forecast period. It further analyses the macroeconomic factors on the market. The report’s scope encompasses market sizing and forecasts for the various market segments.
The Artificial Intelligence of Things (AIoT) Market is segmented by component (software, services), by application (video surveillance, inventory management, predictive maintenance, supply chain management, others), by deployment (cloud-based AIoT, edge AIoT), by industry vertical (retail, BFSI, agriculture, healthcare, manufacturing, transportation & logistics, government & defense, others), and by geography (North America, Europe, Asia Pacific, Latin America, Middle East and Africa). The market sizes and forecasts are provided in terms of value (USD) for all the above segments
| By Component | Hardware | |||
| Software | ||||
| Services | ||||
| By Deployment Model | Cloud-based AIoT | |||
| Edge AIoT | ||||
| Hybrid AI-Edge | ||||
| By Application | Video Surveillance and Security | |||
| Predictive Maintenance | ||||
| Inventory and Warehouse Management | ||||
| Supply-Chain and Fleet Optimization | ||||
| Energy and Utilities Management | ||||
| Smart Buildings and Cities | ||||
| Customer Experience and Personalization | ||||
| Autonomous Mobility | ||||
| By Industry Vertical | Manufacturing | |||
| Healthcare | ||||
| Retail and E-commerce | ||||
| BFSI | ||||
| Transportation and Logistics | ||||
| Agriculture | ||||
| Energy and Utilities | ||||
| Smart Cities and Government | ||||
| Aerospace and Defense | ||||
| By Technology Stack | Machine Learning | |||
| Deep Learning | ||||
| Natural Language Processing | ||||
| Computer Vision | ||||
| Reinforcement Learning | ||||
| By Geography | North America | United States | ||
| Canada | ||||
| Mexico | ||||
| South America | Brazil | |||
| Argentina | ||||
| Rest of South America | ||||
| Europe | United Kingdom | |||
| Germany | ||||
| France | ||||
| Italy | ||||
| Spain | ||||
| Russia | ||||
| Rest of Europe | ||||
| Asia-Pacific | China | |||
| Japan | ||||
| India | ||||
| South Korea | ||||
| Australia and New Zealand | ||||
| Rest of Asia-Pacific | ||||
| Middle East and Africa | Middle East | Saudi Arabia | ||
| UAE | ||||
| Turkey | ||||
| Rest of Middle East | ||||
| Africa | South Africa | |||
| Nigeria | ||||
| Kenya | ||||
| Rest of Africa | ||||
| Hardware |
| Software |
| Services |
| Cloud-based AIoT |
| Edge AIoT |
| Hybrid AI-Edge |
| Video Surveillance and Security |
| Predictive Maintenance |
| Inventory and Warehouse Management |
| Supply-Chain and Fleet Optimization |
| Energy and Utilities Management |
| Smart Buildings and Cities |
| Customer Experience and Personalization |
| Autonomous Mobility |
| Manufacturing |
| Healthcare |
| Retail and E-commerce |
| BFSI |
| Transportation and Logistics |
| Agriculture |
| Energy and Utilities |
| Smart Cities and Government |
| Aerospace and Defense |
| Machine Learning |
| Deep Learning |
| Natural Language Processing |
| Computer Vision |
| Reinforcement Learning |
| North America | United States | ||
| Canada | |||
| Mexico | |||
| South America | Brazil | ||
| Argentina | |||
| Rest of South America | |||
| Europe | United Kingdom | ||
| Germany | |||
| France | |||
| Italy | |||
| Spain | |||
| Russia | |||
| Rest of Europe | |||
| Asia-Pacific | China | ||
| Japan | |||
| India | |||
| South Korea | |||
| Australia and New Zealand | |||
| Rest of Asia-Pacific | |||
| Middle East and Africa | Middle East | Saudi Arabia | |
| UAE | |||
| Turkey | |||
| Rest of Middle East | |||
| Africa | South Africa | ||
| Nigeria | |||
| Kenya | |||
| Rest of Africa | |||
Key Questions Answered in the Report
What is the current size of the Artificial Intelligence of Things market?
The market is valued at USD 35.10 billion in 2025 and is projected to reach USD 89.38 billion by 2030, reflecting a 20.56% CAGR.
Which component segment is growing fastest?
Services are expanding at 32.40% CAGR through 2030 as enterprises seek expert partners for complex integration work.
Why is edge deployment gaining traction over cloud-only models?
Edge implementations reduce latency, address data-sovereignty mandates, and cut bandwidth fees, resulting in a 38.60% CAGR outlook for edge architectures.
Which application area shows the highest growth potential?
Autonomous mobility leads with 44.10% CAGR due to rapid advances in computer vision, sensor fusion, and regulatory pilots in urban transport.
Page last updated on: July 3, 2025
