IoT Analytics Market Size, Share & Industry Analysis By Component (Solution and Services), By Deployment (On-premises and Cloud), By Analytics Type (Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, and Prescriptive Analytics), By Enterprise Type (Large Enterprises and SMEs), By Application (Predictive Maintenance, Energy Management, Asset Management, Inventory Management, and Others), By Industry (Manufacturing, IT & Telecom, Energy & Utilities, Retail & E-commerce, Healthcare, and Others), and Regional Forecast, 2025 – 2032

The global IoT analytics market size was valued at USD 35.51 billion in 2024 and is projected to grow from USD 42.22 billion in 2025 to USD 154.03 billion by 2032, exhibiting a CAGR of 20.3% during the forecast period. North America dominated the IoT analytics market, accounting for a 38.52% market share in 2024. 

This market growth is driven by rapid adoption of Internet of Things (IoT) devices across industrial, commercial, and public-sector environments. Organizations increasingly rely on IoT analytics platforms to transform high-volume sensor data into actionable insights that improve operational efficiency, reduce downtime, and enable data-driven decision-making.

IoT analytics refers to the use of advanced data analytics, AI, and machine learning technologies to develop actionable insights from the large volumes of data generated by Internet of Things (IoT) devices, such as cameras, sensors, wearables, machines, vehicles, and industrial equipment. The integration of AI and ML algorithms into IoT data streams enhances the accuracy of anomaly detection and forecasting, which plays a crucial role in driving market growth.

The IoT analytics industry benefits from rising investments in smart manufacturing, connected infrastructure, and digital transformation initiatives. Enterprises deploy analytics solutions to monitor equipment performance, optimize energy consumption, and manage distributed assets in real time. Advancements in cloud computing, edge analytics, and artificial intelligence (AI) enhance scalability and enable low-latency data processing. These capabilities support use cases ranging from predictive maintenance and asset tracking to supply-chain optimization and energy management.

Large enterprises lead market share due to complex IoT deployments and strong analytics maturity. However, SMEs increasingly adopt cloud-based IoT analytics solutions as subscription pricing models reduce entry barriers. Integration with enterprise resource planning (ERP), manufacturing execution systems (MES), and data lakes improves cross-functional visibility and operational alignment.

Government and smart infrastructure initiatives are accelerating the adoption of IoT analytics by embedding data-driven systems into national digital transformation agendas. Large-scale programs, such as intelligent transportation networks, smart city projects, and utility modernization initiatives, require real-time monitoring and predictive analytics to enhance energy efficiency, optimize traffic flow, and improve public safety. This factor is further driving market growth worldwide.

The market is dominated by established key players, such as Microsoft Corporation, Amazon Web Services, Inc., Google LLC, IBM Corporation, and Oracle Corporation. These players are integrating IoT device management, data analytics, and AI capabilities into unified platforms to offer end-to-end, interoperable solutions. This ecosystem-driven approach streamlines deployment, lowers integration costs, and enhances customer retention through seamless scalability and cross-service compatibility.

IMPACT OF GENERATIVE AI

Emergence of Generative AI Enhances Efficiency and Innovation Across IoT Analytics Ecosystems

Generative AI is transforming the market by allowing automated data interpretation, model generation, and natural-language querying of complex sensor datasets. It fuels the development of predictive and prescriptive models, allowing enterprises to rapidly simulate scenarios and enhance asset performance using digital twins. GenAI-powered assistants simplify analytics workflows by translating human prompts into queries, dashboards, and anomaly reports, democratizing access to insights. Additionally, it improves edge intelligence by generating adaptive models that continuously learn from real-time IoT data streams. Overall, Generative AI is shifting internet of things analytics from traditional monitoring to autonomous decision-making and self-optimizing systems, significantly improving efficiency and innovation speed. For instance,

• In October 2024, Honeywell partnered with Google to integrate Google’s Gemini generative AI into Honeywell’s Forge industrial data platform, aiming to enable autonomous operations and smart maintenance workflows.

MARKET DYNAMICS

Market Drivers

Growing Emphasis on Digital Transformation and Industry 4.0 is Driving Market Growth

The growing emphasis on digital transformation and Industry 4.0 is a major driving factor for propelling IoT analytics market growth as organizations increasingly integrate connected sensors, automation, and AI into their operations. Industrial enterprises are leveraging internet of things analytics to enhance production efficiency, monitor equipment health, and reduce downtime through predictive insights. Smart factories and connected supply chains are majorly dependent on analytics to manage complex data flows and ensure real-time decision-making.

IoT analytics adoption accelerates as organizations deploy connected sensors, machines, and devices across operations. The volume, velocity, and variety of IoT data require advanced analytics platforms capable of real-time processing and insight generation. Manufacturing companies use IoT analytics to improve equipment reliability, reduce unplanned downtime, and enhance production efficiency. Energy and utilities organizations deploy analytics to monitor grids, optimize energy usage, and improve outage response.

Digital transformation initiatives further drive demand. Enterprises seek data-driven insights to improve decision-making and operational agility. Cloud adoption enables scalable analytics processing without heavy infrastructure investment. Edge analytics reduces latency and supports mission-critical applications in industrial environments.

Moreover, governments and enterprises globally are investing in digital infrastructure and industrial automation initiatives, further accelerating adoption. This shift toward data-driven, intelligent manufacturing ecosystems is strengthening internet of things analytics as a core enabler of next-generation industrial competitiveness. For instance,

• January 2025, Digi International launched Digi X-ON, an edge-to-cloud IoT solution designed to boost digital transformation by unifying device connectivity, analytics, and orchestration.

Market Restraints

Data Privacy and Security Concerns Across Diverse IoT Ecosystems May Hinder Market Growth

Data privacy and security concerns pose a significant restraint to the market as billions of connected devices continuously transmit sensitive operational and personal data. Breaches or unauthorized access to this data can lead to severe financial and reputational risks for organizations, especially in critical sectors such as healthcare, utilities, and manufacturing. The absence of unified global security standards and inconsistent data governance policies across regions further complicates secure IoT analytics deployments. This factor is expected to restrict the market growth in the coming years.

High implementation complexity remains a key restraint. Integrating IoT analytics platforms with heterogeneous devices, legacy systems, and data sources requires specialized expertise. Data quality issues, including incomplete or noisy sensor data, reduce analytics accuracy and value realization.

Security and privacy concerns also limit adoption. IoT environments expand attack surfaces, increasing risk of data breaches and system compromise. Compliance with data protection regulations adds operational complexity, particularly for multinational deployments.

Market Opportunities

Rapid Adoption of Edge Computing and 5G Connectivity Creates Lucrative Opportunity for Market Growth

The growing adoption of edge computing and 5G connectivity is enabling faster, real time data processing closer to the source, which fuels the market growth. Edge analytics reduces latency, minimizes bandwidth usage, and allows instant decision-making in mission-critical applications such as autonomous vehicles, industrial automation, and smart healthcare.

Moreover, 5G networks provide the high-speed, low-latency connectivity required to support massive IoT deployments and continuous data streams. Together, these technologies enhance the scalability and responsiveness of IoT analytics tools, unlocking new use cases across industries. For instance,

• In October 2025, Cavli Wireless launched its new ultra-low latency 5G NR IoT modules CQM212 & CQM215. These modules are built for targeting high-throughput industrial and IoT use cases powered by 5G analytics.

Healthcare adoption grows as connected medical devices generate real-time patient data. Retailers leverage IoT analytics for inventory optimization, customer behavior analysis, and supply-chain visibility. Transportation and logistics sectors adopt analytics to optimize fleet performance and reduce fuel costs.

SMEs represent a growing opportunity as cloud-based IoT analytics solutions become more affordable. Emerging markets adopting smart infrastructure create new demand. Vendors offering integrated security, edge capabilities, and AI-driven insights gain competitive advantage.

IoT Analytics Market Trends

Rise in Popularity of Sustainability Analytics is Fueling Market Growth

The growing adoption of sustainability analytics is transforming how businesses use IoT data to achieve energy efficiency and carbon reduction targets. IoT sensors embedded in buildings, factories, and utilities continuously collect data on energy consumption, emissions, and equipment performance. This real-time data is analyzed through analytics platforms to identify inefficiencies, optimize resource usage, and support ESG reporting. Governments and corporations are increasingly mandating carbon transparency, driving demand for analytics-driven sustainability dashboards. For instance,

• July 2025, Bivocom launched an IoT-driven energy management solutions for smart buildings, industrial automation, and hybrid energy systems to help clients minimize waste and emissions.

Edge analytics emerges as a major trend. Processing data closer to devices reduces latency, bandwidth usage, and cloud costs. AI-driven analytics enable anomaly detection, forecasting, and autonomous decision-making. Vendors integrate machine learning models directly into IoT platforms.

Digital twins gain traction as organizations simulate physical assets using real-time data. These models support optimization, predictive maintenance, and scenario analysis. Cloud-native analytics architectures enable elastic scaling and multi-tenant deployments.

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SEGMENTATION ANALYSIS

By Component

Growing Adoption of Integrated IoT Platforms Drives Dominance of Solution Segment

Based on component, the market is bifurcated into solution and services.

Solution captured the largest market share in 2024, estimated at USD 23.77 billion for 2024. This is due to enterprises increasingly adopting integrated IoT analytics platforms combining data management, visualization, and AI-driven insights. The growing demand for scalable, cloud-based analytics solutions from sectors including manufacturing, energy, and logistics further strengthened this segment’s dominance.

IoT analytics solutions form the core of the market. These platforms ingest, process, and analyze data generated by connected devices and sensors. Solutions include data management, real-time analytics, visualization, and AI-driven insight generation. Enterprises adopt solutions to gain visibility into operations, automate responses, and support predictive decision-making. Demand increases as organizations scale IoT deployments across assets and facilities.

Services are anticipated to grow at the highest CAGR of 23.4% during the forecast period, owing to rising demand for system integration, managed analytics, and consulting support to customize and optimize internet of things analytics deployments.

Services include consulting, integration, deployment, and managed analytics services. Organizations rely on services to design analytics architectures, integrate devices, and maintain platforms. Managed services support continuous optimization and reduce operational burden. SMEs and organizations with limited analytics expertise drive service demand.

By Deployment 

Rising Enterprise Preference for Cloud-Based Analytics Boosts Segment Growth

Based on deployment, the market is categorized into on-premises and cloud.

Cloud captured the largest market share and accounted for USD 24.17 billion in 2024. Also, it is expected to grow at the highest CAGR of 21.8% during the forecast period. This is owing to its scalability, flexibility, and cost-efficiency in handling massive IoT data volumes. Also, the growing preference for cloud-based analytics by enterprises enabled seamless integration of AI, ML, and edge systems for real-time insights and remote monitoring.

Cloud deployment dominates market share due to scalability, flexibility, and cost efficiency. Cloud-based IoT analytics platforms enable rapid deployment, elastic processing, and global accessibility. SMEs prefer cloud models due to subscription pricing and minimal infrastructure requirements. Hybrid architectures combine cloud scalability with edge processing.

On-premises is expected to grow at a moderate CAGR during the forecast period. This is due to continued adoption in highly regulated industries that prioritize data security, control, and compliance over scalability. On-premises deployment remains relevant for organizations requiring strict data control and low-latency processing. Manufacturing plants, utilities, and government agencies deploy on-premises analytics to maintain security and operational reliability. These deployments support integration with legacy systems but require higher upfront investment.

By Analytics Type 

Ease of Implementation and Broad Applicability Propel Descriptive Analytics Growth

Based on analytics type, the market is divided into descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics.

Descriptive analytics captured the largest market share in 2024, estimated at USD 16.22 billion for 2024. This is due to it serving as the foundational layer for IoT data visualization, monitoring, and reporting across industries. Furthermore, its ease of implementation and critical role in converting raw sensor data into operational insights make it the most widely adopted analytics type.

Descriptive analytics summarizes historical IoT data to provide visibility into operational performance. Dashboards, reports, and visualizations support monitoring and benchmarking. This analytics type forms the foundation for more advanced insights.

Diagnostic analytics identifies root causes of anomalies and performance issues. Organizations use diagnostic tools to understand why failures occur or efficiency declines. This capability supports troubleshooting and continuous improvement initiatives.

Predictive analytics forecasts future outcomes using historical and real-time data. Machine learning models predict equipment failures, energy demand, and inventory needs. Predictive analytics adoption grows rapidly as organizations pursue proactive strategies.

Prescriptive analytics is expected to grow at the highest CAGR during the forecast period. This is due to enterprises increasingly adopting AI-driven decision automation and digital twin technologies to enable real-time optimization and autonomous operations.

Prescriptive analytics recommends actions to optimize outcomes. These tools use optimization algorithms and AI to suggest maintenance schedules, energy adjustments, or process changes. Prescriptive analytics represents an advanced, high-value segment.

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By Enterprise Type 

Strong IT Infrastructure and Capital Investments Strengthen Large Enterprise Dominance

Based on enterprise type, the market is bifurcated into large enterprises and SMEs.

Large enterprises captured the largest market share and accounted for USD 21.54 billion in 2024, owing to their substantial budgets, advanced IT infrastructure, and early adoption of IoT analytics for large-scale digital transformation. Their focus on operational efficiency, predictive maintenance, and enterprise-wide data integration further reinforced their dominance in the market.

Large enterprises lead adoption due to complex IoT ecosystems and strong analytics capabilities. They deploy multi-site analytics platforms integrated with ERP, MES, and supply-chain systems. Large enterprises prioritize scalability, customization, and advanced AI capabilities.

SMEs are anticipated to grow at the highest CAGR of 22.4% during the forecast period, due to increasing adoption of affordable, cloud-based analytics solutions that allow data-driven decision-making without heavy infrastructure investment. SMEs adopt IoT analytics to improve efficiency and competitiveness. Cloud-based platforms enable affordable access to advanced analytics. SMEs focus on targeted use cases such as equipment monitoring and energy optimization.

By Application

Rising Focus on Equipment Uptime Drives Predictive Maintenance Adoption

Based on application, the market is classified into predictive maintenance, energy management, asset management, inventory management, and others (remote monitoring, etc.).

Predictive maintenance captured the largest market share in 2024, estimated at USD 11.74 billion for 2024. Industries are increasingly leveraging IoT analytics to minimize equipment downtime and optimize asset performance. The ability to forecast failures, reduce maintenance costs, and extend machinery lifespan made it the most widely adopted application across manufacturing, energy, and transportation sectors.

Predictive maintenance represents the largest application segment. Organizations monitor equipment health to prevent failures and reduce downtime. Analytics platforms analyze vibration, temperature, and usage data to forecast maintenance needs.

Energy management applications optimize consumption, reduce costs, and support sustainability goals. Utilities and industrial users deploy analytics to manage demand, monitor grids, and integrate renewable energy.

Asset Management is projected to grow at the highest CAGR of 22.4% during the forecast period, due to increasing adoption of IoT-enabled tracking and analytics solutions that enhance asset visibility, utilization, and lifecycle optimization across industries. Asset management applications track location, condition, and utilization of assets. Analytics improve lifecycle management and capital planning across industries.

Inventory management analytics optimize stock levels and reduce waste. Retailers and manufacturers use IoT data to improve forecasting and supply-chain visibility.

By Industry 

Industry 4.0 Adoption Drives IoT Analytics Demand in Manufacturing

Based on industry, the market is categorized into BFSI, IT & telecom, manufacturing, retail & e-commerce, healthcare, and others (media & entertainment, etc.).

Manufacturing accounted for the largest market share of USD 9.96 billion in 2024, owing to the widespread adoption of IoT analytics for process optimization, quality control, and predictive maintenance. The rise of Industry 4.0 and smart factory initiatives further accelerated the deployment of analytics-driven production systems to enhance efficiency and reduce downtime. Manufacturing leads market adoption due to Industry 4.0 initiatives. IoT analytics improves productivity, quality control, and maintenance planning.

IT and telecom organizations deploy analytics to manage networks, optimize performance, and support 5G-enabled services. Utilities use analytics for smart grid management, outage prediction, and energy optimization. Retailers adopt IoT analytics for inventory optimization, customer insights, and store operations.

Healthcare is projected to grow at the highest CAGR of 23.2% during the forecast period, owing to increasing adoption of IoT-enabled medical devices and analytics platforms for remote patient monitoring, predictive diagnostics, and real-time health data management. Healthcare organizations use analytics to monitor medical devices, improve patient outcomes, and optimize operations.

REGIONAL INSIGHTS

By geography, the market is categorized into North America, Europe, Asia Pacific, South America, and the Middle East & Africa.

NORTH AMERICA IoT ANALYTICS MARKET ANALYSIS

North America held the largest IoT analytics market share in 2023, valued at USD 11.76 billion, and also maintained the leading share in 2024, with USD 13.68 billion. The factors behind the regional growth include, enterprises increasingly integrated AI-powered analytics into large-scale industrial and infrastructure operations, particularly in manufacturing, energy, and logistics. Additionally, major investments by hyperscalers, including AWS, Microsoft Azure, and Google Cloud, in localized data centers and AI-driven operational intelligence platforms further strengthened North America’s dominance. For instance,

• In April 2024, AWS invested USD 11 billion to build a new data center campus in Indiana, U.S. Through this investment, the company aims to strengthen its localized cloud infrastructure for AI and IoT workloads in the U.S.

Also North America leads the IoT analytics market due to advanced digital infrastructure and strong adoption of smart manufacturing and cloud technologies. Enterprises invest heavily in predictive analytics and edge computing. The presence of major technology vendors and early adoption of AI-driven analytics accelerate regional market growth.

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In 2025, the U.S. market is estimated to reach USD 11.32 billion. The large-scale adoption of IoT analytics across manufacturing, logistics, and energy sectors, supported by strong digital infrastructure and enterprise focus on predictive maintenance and automation. Additionally, government-backed initiatives promoting smart manufacturing and AI integration, along with significant investments from cloud hyperscalers and industrial IoT vendors, are accelerating the country’s leadership in internet of things analytics deployment.

The United States dominates regional market share with widespread IoT deployments across manufacturing, healthcare, and utilities. Strong cloud adoption and investment in AI accelerate analytics innovation. Enterprises prioritize predictive maintenance and energy optimization, driving sustained market expansion.

EUROPE IoT ANALYTICS MARKET ANALYSIS

Europe is anticipated to witness a moderate growth in the coming years. During the forecast period, the European region is anticipated to record a growth rate of 18.0%, which is the fourth highest among all the regions, and touch the valuation of USD 9.31 billion in 2025. This is primarily due to strong regulatory support for industrial digitalization, sustainability, and energy efficiency, particularly under the European Union’s Digital Europe and Green Deal initiatives.

Europe experiences steady growth driven by Industry 4.0 initiatives and smart energy programs. Regulatory focus on sustainability supports energy analytics adoption. Germany, the UK, and France lead regional deployment across manufacturing and utilities.

Moreover, widespread adoption of Industrial IoT (IIoT) across manufacturing hubs in Germany, the U.K., and the Nordics, coupled with growing investments in edge AI and smart infrastructure, is driving demand for advanced analytics platforms across the region. Backed by these factors, countries including the U.K. are expected to record the valuation of USD 1.80 billion, Germany to record USD 1.72 billion, and France to record USD 1.52 billion in 2025.

Germany’s market benefits from strong industrial automation and digital manufacturing. Enterprises deploy IoT analytics to improve efficiency and quality. Industry 4.0 programs and energy optimization initiatives drive continued adoption.

The UK market grows due to smart infrastructure projects and digital transformation across industries. IoT analytics supports utilities, transportation, and retail sectors. Cloud-based platforms gain traction among SMEs.

ASIA PACIFIC IoT ANALYTICS MARKET ANALYSIS

The market in the Asia Pacific is estimated to reach USD 11.40 billion in 2025, and it is expected to grow at the highest CAGR of 24.6% during the forecast period. The regional growth is fueled by rapid industrialization and large-scale smart city projects in countries such as China, Japan, India, and South Korea. Also, expanding manufacturing base, coupled with increasing investments in 5G, edge analytics, and AI-powered IoT platforms, is enabling enterprises to enhance operational efficiency and adopt predictive analytics at scale. In the region, India and China both are estimated to reach USD 1.60 billion and USD 2.36 billion, respectively, in 2025.

Asia-Pacific represents the fastest-growing region due to rapid industrialization and smart city initiatives. China, Japan, and India lead adoption. Expanding manufacturing and energy sectors drive strong analytics demand. Japan adopts IoT analytics to support advanced manufacturing, robotics, and smart infrastructure. Enterprises invest in predictive maintenance and quality optimization. Government initiatives promote connected technologies. China market expands rapidly due to large-scale industrial IoT deployments and smart city projects. Manufacturing and utilities drive adoption. Government support accelerates analytics integration.

SOUTH AMERICA IoT ANALYTICS MARKET ANALYSIS

South America is expected to witness significant growth in this market. The South American market in 2025 is set to record USD 2.37 billion, driven by increasing adoption of IoT analytics in the energy, utilities, and manufacturing sectors, driven by regional digitalization efforts and rising demand for operational efficiency and asset monitoring.

MIDDLE EAST & AFRICA IoT ANALYTICS MARKET ANALYSIS

The Middle East & Africa is estimated to reach USD 3.17 billion in 2025 and is expected to grow at a prominent growth rate in the coming years, owing to expanding smart city and infrastructure projects, particularly in the GCC countries, alongside increasing investments in industrial IoT and energy analytics to support economic diversification and sustainability goals. In the region, GCC is set to attain the value of USD 0.98 billion in 2025. For instance,

• October 2025, Moro Hub, a subsidiary of Dubai Electricity and Water Authority, signed an MoU with Univers to deploy AI + IoT for advanced energy management and sustainability solutions across industrial and commercial operations

MEA adoption grows as smart infrastructure and energy projects expand. Utilities and government sectors drive demand. Cloud and edge analytics support deployment in remote environments.

Competitive Landscape

Growing Focus of Key Market Players on Innovation and New Launches Leads to their Dominating Market Positions

The global market is highly fragmented, with numerous players competing across different regions. Key companies include Microsoft Corporation, Amazon Web Services, Inc., Google LLC, IBM Corporation, Oracle Corporation, and other significant companies. These organizations focus on strategies such as new product launches, mergers and acquisitions, technological advancements, and investments in cloud-based analytics solutions to enhance their market presence.

The IoT analytics market features global technology providers, cloud hyperscalers, and specialized analytics vendors. Leading players compete through scalable platforms, AI-driven analytics, and deep integration with IoT ecosystems.

Cloud providers leverage elastic infrastructure and advanced machine learning services. Industrial automation vendors integrate analytics into operational technology environments. Niche players offer specialized solutions for predictive maintenance and energy management.

Strategic partnerships between IoT platform providers, device manufacturers, and system integrators strengthen market reach. Vendors invest in edge analytics, digital twins, and low-code tools to enhance differentiation. Competition centers on scalability, analytics depth, and ease of integration.

List of Top IoT Analytics Companies Studied:

• Microsoft Corporation (U.S.)
• Amazon Web Services, Inc. (U.S.)
• Google LLC (U.S.)
• IBM Corporation (U.S.)
• Oracle Corporation (U.S.)
• Cisco Systems, Inc. (U.S.)
• Siemens AG (Germany)
• Hitachi Ltd. (Japan)
• PTC Inc. (U.S.)
• Software AG (Germany)
• SAP SE (Germany)
• General Electric (U.S.)
• Teradata Corporation (U.S.)
• Schneider Electric SE (France)
• Bosch GmbH (Germany)
• SAS Institute Inc. (U.S.)
• Hewlett Packard Enterprise (U.S.)
• Intel Corporation (U.S.)
• Dell Inc. (U.S.)
• Open Text Corporation (Canada) 

KEY INDUSTRY DEVELOPMENTS

• October 2025: Wiliot announced a collaboration with Walmart to deploy ambient IoT sensors across Walmart’s supply chain to feed AI/analytics systems for improved inventory and cold chain management.
• October 2025: AT&T and Ericsson launched a cloud-based IoT Marketplace to simplify IoT service provisioning, billing, and device management.
• June 2025: Siemens and NVIDIA expanded their partnership to integrate accelerated AI computing with Siemens’ Xcelerator platform, aiming to bolster industrial AI analytics capabilities across manufacturing.
• January 2025: Microsoft introduced advanced IoT analytics integrations within Azure, combining digital twins, machine learning automation, and real-time streaming analytics for enterprise deployments.
• January 2025: AWS plans to invest USD 11 billion in data center infrastructure in Georgia with the aim of supporting future AI, cloud, and IoT analytics capabilities.
• October 2024: IBM launched enhanced prescriptive analytics features for its IoT platform, leveraging AI optimization engines to improve asset and energy management outcomes.
• August 2024: Oracle announced a collaboration with AT&T to embed AT&T IoT connectivity and network APIs into its Enterprise Cloud Apps, facilitating near-real-time data collection from IoT devices via Oracle’s cloud infrastructure.

REPORT COVERAGE

The report provides a detailed analysis of the market and focuses on key aspects such as leading companies, product types, and leading applications of the product. Besides, the report offers insights into the market trends and highlights key industry developments. In addition to the factors above, the report encompasses several factors that contributed to the growth of the market in recent years.

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