세계의 IoT 분석 시장 규모는 2024년에 272억 8,000만 달러로 평가되었으며, 예측 기간 동안 CAGR 24.36%로 2030년에는 1,018억 2,000만 달러에 달할 것으로 예측됩니다.
| 시장 개요 | |
|---|---|
| 예측 기간 | 2026-2030년 |
| 시장 규모 : 2024년 | 272억 8,000만 달러 |
| 시장 규모 : 2030년 | 1,018억 2,000만 달러 |
| CAGR : 2025-2030년 | 24.36% |
| 급성장 부문 | 전문 서비스 |
| 최대 시장 | 북미 |
사물인터넷 분석 시장은 일반적으로 IoT 분석 시장으로 불리며, 다양한 산업의 커넥티드 디바이스, 센서, IoT 시스템에서 생성되는 방대한 양의 데이터를 수집, 처리, 분석하는 것을 포괄합니다. IoT 애널리틱스를 통해 기업은 스마트 기기의 원시 데이터를 실행 가능한 인사이트로 전환하여 의사결정 개선, 업무 효율화, 예지보전, 고객 경험 향상을 지원할 수 있습니다. 이 시장은 데이터 관리, 분석 소프트웨어, 전용 애플리케이션 등의 플랫폼과 매니지드 분석, 컨설팅, 시스템 통합 등의 서비스 등 다양한 솔루션을 포괄하고 있습니다.
IoT 분석의 구축 모델은 온프레미스, 클라우드, 하이브리드 인프라를 아우르며 기업의 다양한 요구에 유연하게 대응할 수 있습니다. 이 시장은 몇 가지 요인에 의해 성장이 가속화되고 있습니다. 인더스트리 4.0, 스마트 제조, 커넥티드 인더스트리얼 오퍼레이션의 도입이 증가함에 따라 방대한 양의 데이터가 생성되고, 생산 최적화, 다운타임 감소, 품질 관리 향상을 위해 고도의 분석이 요구되고 있습니다. 마찬가지로 헬스케어 분야에서는 환자 모니터링, 예측 진단, 운영 관리에 IoT 애널리틱스를 활용하고, 에너지 및 유틸리티 분야에서는 그리드 관리 및 에너지 효율성 강화에 애널리틱스를 활용하고 있습니다. 인공지능과 머신러닝을 IoT 분석 플랫폼에 통합함으로써 예측 및 처방 기능을 더욱 강화하여 기업이 장애를 예측하고, 자원 배분을 최적화하며, 자동화된 의사결정을 내릴 수 있도록 돕습니다.
IoT 분석 시장을 주도하는 커넥티드 디바이스의 보급 확대
데이터 보안 및 프라이버시 문제
인공지능과 머신러닝 도입 증가
The Global IoT Analytics Market was valued at USD 27.28 billion in 2024 and is expected to reach USD 101.82 billion by 2030 with a CAGR of 24.36% during the forecast period.
| Market Overview | |
|---|---|
| Forecast Period | 2026-2030 |
| Market Size 2024 | USD 27.28 Billion |
| Market Size 2030 | USD 101.82 Billion |
| CAGR 2025-2030 | 24.36% |
| Fastest Growing Segment | Professional Services |
| Largest Market | North America |
The Internet of Things Analytics Market, commonly referred to as the IoT Analytics Market, encompasses the collection, processing, and analysis of vast volumes of data generated by connected devices, sensors, and IoT systems across multiple industries. IoT analytics enables organizations to transform raw data from smart devices into actionable insights, supporting improved decision-making, operational efficiency, predictive maintenance, and enhanced customer experiences. The market covers a wide array of solutions, including platforms for data management, analytics software, and specialized applications, as well as services such as managed analytics, consulting, and system integration.
Deployment models for IoT analytics span on-premise, cloud, and hybrid infrastructures, providing flexibility for diverse enterprise needs. The market is witnessing accelerated growth driven by several factors. Increasing adoption of Industry 4.0 practices, smart manufacturing, and connected industrial operations is generating immense volumes of data that require sophisticated analytics to optimize production, reduce downtime, and improve quality control. Similarly, sectors such as healthcare are leveraging IoT analytics for patient monitoring, predictive diagnostics, and operational management, while energy and utilities are using analytics to enhance grid management and energy efficiency. The integration of artificial intelligence and machine learning with IoT analytics platforms is further enhancing predictive and prescriptive capabilities, enabling businesses to anticipate failures, optimize resource allocation, and implement automated decision-making.
Key Market Drivers
Proliferation of Connected Devices Driving the IoT Analytics Market
In the contemporary business landscape, the exponential proliferation of connected devices stands as a pivotal force propelling the IoT Analytics Market forward, enabling organizations to harness vast streams of data for strategic decision-making and operational efficiency. As enterprises across sectors such as manufacturing, healthcare, transportation, and retail increasingly integrate Internet of Things ecosystems into their core operations, the sheer volume of generated data necessitates sophisticated analytics solutions to derive actionable insights, mitigate risks, and optimize resource allocation.
This driver is underpinned by the seamless interconnectivity facilitated by advancements in sensor technologies and wireless communication protocols, which allow for real-time data capture from diverse endpoints, ranging from industrial machinery to consumer wearables. Businesses are leveraging this connectivity to enhance predictive maintenance capabilities, where analytics platforms process device-generated data to forecast equipment failures, thereby reducing downtime and extending asset lifespans. Furthermore, in supply chain management, the integration of connected devices enables granular tracking of goods, improving inventory accuracy and minimizing losses through data-driven visibility. The IoT Analytics Market benefits immensely from this trend, as companies seek to transform raw data into competitive advantages, such as personalized customer experiences in retail through behavioral analysis or energy optimization in smart buildings via consumption patterns.
Regulatory pressures for sustainability also amplify this driver, compelling firms to utilize analytics for monitoring environmental impacts, like carbon emissions from fleets of connected vehicles. Economically, the cost reductions achieved through proactive interventions-such as averting costly breakdowns-translate into higher profitability margins, making investments in analytics infrastructure a strategic imperative. Moreover, the convergence with emerging technologies like 5G networks accelerates data transmission speeds, allowing for more complex analytics models that incorporate machine learning algorithms to identify anomalies and trends in large datasets.
This not only fosters innovation but also opens new revenue streams, such as data monetization services where aggregated insights are sold to third parties. Challenges such as data silos and interoperability issues are being addressed through standardized protocols, ensuring that the proliferation of devices does not overwhelm analytics capabilities but rather enhances them. In healthcare, for instance, connected medical devices provide continuous patient monitoring, with analytics enabling early detection of health deteriorations, thus improving outcomes and reducing hospitalization costs.
According to the Organisation for Economic Co-operation and Development (OECD) on measuring the Internet of Things, the total number of IoT connections reached 11.7 billion globally in 2020, with projections estimating 29.3 billion networked devices by 2023, of which 14.7 billion are machine-to-machine connections representing 50 percent of the total. Additionally, machine-to-machine SIM card subscriptions in the OECD area stood at 385 million as of June 2021, up from 132 million in 2015, highlighting a significant adoption surge. The report also notes that low-power wide-area connections for machine-to-machine grew to 223 million in 2018, expected to reach 1.9 billion by 2023, comprising 14 percent of all devices. This proliferation contributes to an economic impact of 0.99 percent annual average addition to gross domestic product growth from 2018 to 2030, equating to approximately 849 billion United States dollars per year in 2018 prices.
Key Market Challenges
Data Security and Privacy Concerns
One of the most significant challenges facing the Internet of Things Analytics Market is ensuring data security and privacy. IoT systems generate enormous volumes of sensitive information across multiple sectors, including healthcare, financial services, manufacturing, energy, and government operations. This data often includes personally identifiable information, operational metrics, and strategic business insights, all of which require robust protection. Cybersecurity breaches, unauthorized access, and data leaks can result in substantial financial losses, reputational damage, and regulatory penalties for organizations. As IoT devices proliferate, the attack surface expands, making it increasingly difficult for enterprises to maintain comprehensive security across all connected devices and networks.
The complexity of securing IoT analytics platforms is compounded by the diverse and heterogeneous nature of devices, communication protocols, and data formats. Many IoT devices are designed for functionality and cost-effectiveness rather than security, leaving them vulnerable to hacking or malware attacks. Additionally, data is frequently transmitted and stored across cloud-based infrastructures, creating potential exposure points. Organizations must invest in advanced encryption techniques, secure authentication mechanisms, and continuous monitoring systems to mitigate risks. Furthermore, regulatory compliance adds another layer of complexity. Different regions enforce varying data protection regulations, such as the General Data Protection Regulation in Europe, which imposes strict requirements on data collection, storage, and processing. Enterprises operating across multiple regions must navigate these regulatory frameworks while ensuring seamless analytics operations.
Addressing security and privacy concerns is not merely a technological challenge but also a strategic and operational consideration. Companies must balance the need for real-time data processing and actionable insights with the imperative to safeguard sensitive information. The development and adoption of comprehensive security frameworks, including data anonymization, end-to-end encryption, and secure device management, are critical to sustaining trust and long-term growth in the Internet of Things Analytics Market. Failure to address these concerns may slow market adoption, particularly in sectors such as healthcare and financial services, where data sensitivity is paramount. As cyber threats evolve and the volume of IoT-generated data continues to expand exponentially, maintaining robust security and privacy standards will remain a persistent and pressing challenge for stakeholders in the market.
Key Market Trends
Increasing Adoption of Artificial Intelligence and Machine Learning
A significant trend shaping the Internet of Things Analytics Market is the increasing integration of artificial intelligence and machine learning technologies into analytics platforms. Organizations across sectors are leveraging these technologies to process massive volumes of data generated by connected devices and transform it into actionable insights. Traditional analytics methods are often insufficient for handling the high velocity, variety, and volume of data in modern IoT ecosystems. Artificial intelligence and machine learning enable predictive and prescriptive analytics, allowing enterprises to anticipate failures, optimize operations, and make proactive business decisions.
In industrial sectors, predictive maintenance powered by machine learning models allows manufacturers to detect anomalies in equipment before they lead to costly downtime, thereby enhancing operational efficiency and reducing maintenance costs. Similarly, in healthcare, artificial intelligence-driven analytics enable real-time monitoring of patient health, early detection of critical conditions, and optimization of treatment plans. The financial sector is also benefiting, with artificial intelligence algorithms analyzing transaction data to detect fraud, assess credit risk, and enhance customer experience. Furthermore, the combination of IoT analytics with machine learning accelerates decision-making in smart cities, enabling efficient traffic management, energy optimization, and resource allocation.
Enterprises are increasingly investing in AI-enabled IoT analytics solutions that support autonomous decision-making and self-learning systems. These capabilities not only improve operational efficiency but also enhance the quality and accuracy of insights, which is critical for strategic planning and risk management. The trend towards integrating artificial intelligence and machine learning within the Internet of Things Analytics Market is expected to continue, driven by the growing demand for intelligent automation, real-time monitoring, and actionable predictive insights. Companies that successfully adopt these technologies will gain competitive advantages by improving operational performance, reducing costs, and delivering superior services to customers, thereby reinforcing the market's rapid growth trajectory.
In this report, the Global IoT Analytics Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
Company Profiles: Detailed analysis of the major companies present in the Global IoT Analytics Market.
Global IoT Analytics Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report: