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Global Machine to Machine (M2M) Healthcare Market Set to Reach USD 35.30 Billion by 2030, with a Healthy CAGR of 4.79% | Infinium Global Research

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PUNE, India, Oct. 12, 2023 /PRNewswire/ — Infinium Global Research, a reputable market research firm, has recently released an extensive report on the Machine to Machine (M2M) Healthcare Market. This comprehensive report not only delves into the analysis of various market segments and sub-segments but also explores the impact of drivers, restraints, and macro indicators on both the global and regional Machine to Machine (M2M) healthcare market. Providing a comprehensive presentation of trends, forecasts, and financial values, this report sheds light on the promising future of the global Machine to Machine (M2M) healthcare market. The global Machine to Machine (M2M) healthcare market, valued at USD 23.00 billion in 2022, is on an upward trajectory, projected to achieve USD 35.30 billion by 2030. This journey is fuelled by a robust compound annual growth rate (CAGR) of 4.79% during the forecast period from 2023 to 2030.

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Revolutionizing Healthcare through M2M Technology
Machine-to-machine (M2M) healthcare signifies the convergence of interconnected devices and sensors within the healthcare sector, facilitating the seamless collection, transmission, and analysis of data without the need for direct human intervention. This transformative technology fosters the fluid exchange of information among medical devices, patient monitoring systems, and healthcare providers. Consequently, it leads to elevated patient care standards, reduced errors, and heightened operational efficiency. M2M healthcare’s potential is expansive and holds immense promise. It empowers real-time remote patient monitoring, ensuring timely interventions and the formulation of personalized treatment plans. M2M technology plays a pivotal role in chronic disease management, tracking medication adherence, and preventive care, thus contributing to improved patient outcomes. Moreover, it acts as a catalyst for the development of predictive analytics and artificial intelligence applications, assisting healthcare professionals in making data-driven decisions. Furthermore, M2M enhances healthcare logistics and inventory management, optimizing resource allocation while simultaneously curtailing costs.
Key Drivers Propelling M2M Healthcare
The surging demand for remote patient monitoring and heightened healthcare operational efficiency underpins the machine-to-machine (M2M) healthcare market’s expansion. This demand is propelled by technological advancements that enable seamless data exchange and the provision of real-time healthcare solutions. Ultimately, these innovations enhance both patient care and the overall effectiveness of healthcare systems. Moreover, the escalating prevalence of chronic diseases such as diabetes, heart conditions, and cancer acts as a pivotal driver for the growth of the M2M healthcare market. M2M technology facilitates continuous monitoring and timely interventions, thereby improving the management and outcomes of chronic illnesses. This, in turn, contributes significantly to the market’s expansion.
However, the cost of installation may present a hindrance to the adoption of M2M technology in healthcare settings. Implementing M2M technology often necessitates substantial upfront investments, potentially limiting its adoption, especially among smaller healthcare providers or resource-constrained settings. This is despite the myriad benefits it offers. Nonetheless, the rapid advancement of wireless technologies presents substantial opportunities for the machine-to-machine (M2M) healthcare market. These innovations enable seamless data transmission, remote monitoring, and real-time communication, thereby enhancing the efficiency and effectiveness of healthcare services and fostering the growth of M2M solutions in the healthcare sector.
Global Domination and Accelerated Growth in Asia-Pacific
North America currently boasts the largest market share in the machine-to-machine (M2M) healthcare market. This supremacy is attributed to its robust healthcare infrastructure, technological advancements, and a proactive regulatory environment that encourages the integration of M2M technologies into healthcare systems. The United States, in particular, stands at the forefront of M2M healthcare solutions. The nation is witnessing a rising trend of healthcare providers and institutions adopting Internet of Things (IoT)-powered devices and platforms to enhance patient care and optimize operational processes.
Furthermore, the Asia-Pacific region is emerging as the fastest-growing market for M2M healthcare solutions. Factors contributing to this rapid growth include an expanding middle class, increased healthcare expenditure, and a growing aging population. As governments in countries such as China and India prioritize healthcare modernization, M2M technologies are leveraged to improve healthcare accessibility and delivery. The region’s potential for exponential growth presents ample opportunities for M2M healthcare providers to tap into a burgeoning market.
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Comprehensive Market Segmentation
The global Machine to Machine (M2M) healthcare market is meticulously segmented across various key parameters:
Application:Remote Health MonitoringClinical MonitoringFitness and WellnessOthersComponent:Connectivity ServicesM2M Platforms and ApplicationsM2M ModulesCompetitive Landscape
The report provides profiles of the companies in the market such as Cradlepoint, Inc., AirStrip Technologies, Inc, BL Healthcare, Inc, Sierra Wireless, Thales, Deutsche Telekom AG, Allscripts/Veradigm, PharmaSecure, Stanley Black & Decker, Inc., and Ingenious Med.
As machine-to-machine (M2M) technology continues its transformative journey in healthcare, it promises to reshape the landscape, ushering in an era of heightened efficiency, innovation, and personalized healthcare. For in-depth insights into specific market segments, emerging trends, competitive dynamics, and future growth prospects, please refer to the complete research report.
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Table of Content
Chapter 1. Preface
1.1. Report Description
1.2. Research Methods
1.3. Research Approaches 
Chapter 2. Executive Summary
2.1. Machine to Machine (M2M) Healthcare Market Highlights
2.2. Machine to Machine (M2M) Healthcare Market Projection
2.3. Machine to Machine (M2M) Healthcare Market Regional Highlights 
Chapter 3. Global Machine to Machine (M2M) Healthcare Market Overview
3.1. Introduction
3.2. Market Dynamics
3.2.1. Drivers
3.2.2. Restraints
3.2.3. Opportunities
3.3. Porter`s Five Forces Analysis
3.4. IGR-Growth Matrix Analysis
3.4.1. IGR-Growth Matrix Analysis by Application
3.4.2. IGR-Growth Matrix Analysis by Component
3.4.3. IGR-Growth Matrix Analysis by Region
3.5. Value Chain Analysis of Machine to Machine (M2M) Healthcare Market
Chapter 4. Machine to Machine (M2M) Healthcare Market Macro Indicator Analysis 
Chapter 5. Company Profiles and Competitive Landscape
5.1. Competitive Landscape in the Global Machine to Machine (M2M) Healthcare Market
5.2. Companies Profiles
5.2.1. Cradlepoint, Inc.
5.2.2. AirStrip Technologies, Inc
5.2.3. BL Healthcare, Inc
5.2.4. Sierra Wireless
5.2.5. Thales
5.2.6. Deutsche Telekom AG
5.2.7. Allscripts/Veradigm
5.2.8. PharmaSecure
5.2.9. Stanley Black & Decker, Inc.
5.2.10. Ingenious Med
Chapter 6. Global Machine to Machine (M2M) Healthcare Market by Application
6.1. Remote Health Monitoring
6.2. Clinical Monitoring
6.3. Fitness and Wellness
6.4. Others
Chapter 7. Global Machine to Machine (M2M) Healthcare Market by Component
7.1. Connectivity Services
7.2. M2M Platforms and Application
7.3. M2M Modules
Chapter 8. Global Machine to Machine (M2M) Healthcare Market by Region 2023-2030
8.1. North America
8.1.1. North America Machine to Machine (M2M) Healthcare Market by Application
8.1.2. North America Machine to Machine (M2M) Healthcare Market by Component
8.1.3. North America Machine to Machine (M2M) Healthcare Market by Country
8.1.3.1. The U.S. Machine to Machine (M2M) Healthcare Market
8.1.3.1.1. The U.S. Machine to Machine (M2M) Healthcare Market by Application
8.1.3.1.2. The U.S. Machine to Machine (M2M) Healthcare Market by Component
8.1.3.2. Canada Machine to Machine (M2M) Healthcare Market
8.1.3.2.1. Canada Machine to Machine (M2M) Healthcare Market by Application
8.1.3.2.2. Canada Machine to Machine (M2M) Healthcare Market by Component
8.1.3.3. Mexico Machine to Machine (M2M) Healthcare Market
8.1.3.3.1. Mexico Machine to Machine (M2M) Healthcare Market by Application
8.1.3.3.2. Mexico Machine to Machine (M2M) Healthcare Market by Component
8.2. Europe
8.2.1. Europe Machine to Machine (M2M) Healthcare Market by Application
8.2.2. Europe Machine to Machine (M2M) Healthcare Market by Component
8.2.3. Europe Machine to Machine (M2M) Healthcare Market by Country
8.2.3.1. Germany Machine to Machine (M2M) Healthcare Market
8.2.3.1.1. Germany Machine to Machine (M2M) Healthcare Market by Application
8.2.3.1.2. Germany Machine to Machine (M2M) Healthcare Market by Component
8.2.3.2. United Kingdom Machine to Machine (M2M) Healthcare Market
8.2.3.2.1. United Kingdom Machine to Machine (M2M) Healthcare Market by Application
8.2.3.2.2. United Kingdom Machine to Machine (M2M) Healthcare Market by Component
8.2.3.3. France Machine to Machine (M2M) Healthcare Market
8.2.3.3.1. France Machine to Machine (M2M) Healthcare Market by Application
8.2.3.3.2. France Machine to Machine (M2M) Healthcare Market by Component
8.2.3.4. Italy Machine to Machine (M2M) Healthcare Market
8.2.3.4.1. Italy Machine to Machine (M2M) Healthcare Market by Application
8.2.3.4.2. Italy Machine to Machine (M2M) Healthcare Market by Component
8.2.3.5. Rest of Europe Machine to Machine (M2M) Healthcare Market
8.2.3.5.1. Rest of Europe Machine to Machine (M2M) Healthcare Market by Application
8.2.3.5.2. Rest of Europe Machine to Machine (M2M) Healthcare Market by Component
8.3. Asia Pacific
8.3.1. Asia Pacific Machine to Machine (M2M) Healthcare Market by Application
8.3.2. Asia Pacific Machine to Machine (M2M) Healthcare Market by Component
8.3.3. Asia Pacific Machine to Machine (M2M) Healthcare Market by Country
8.3.3.1. China Machine to Machine (M2M) Healthcare Market
8.3.3.1.1. China Machine to Machine (M2M) Healthcare Market by Application
8.3.3.1.2. China Machine to Machine (M2M) Healthcare Market by Component
8.3.3.2. Japan Machine to Machine (M2M) Healthcare Market
8.3.3.2.1. Japan Machine to Machine (M2M) Healthcare Market by Application
8.3.3.2.2. Japan Machine to Machine (M2M) Healthcare Market by Component
8.3.3.3. India Machine to Machine (M2M) Healthcare Market
8.3.3.3.1. India Machine to Machine (M2M) Healthcare Market by Application
8.3.3.3.2. India Machine to Machine (M2M) Healthcare Market by Component
8.3.3.4. South Korea Machine to Machine (M2M) Healthcare Market
8.3.3.4.1. South Korea Machine to Machine (M2M) Healthcare Market by Application
8.3.3.4.2. South Korea Machine to Machine (M2M) Healthcare Market by Component
8.3.3.5. Australia Machine to Machine (M2M) Healthcare Market
8.3.3.5.1. Australia Machine to Machine (M2M) Healthcare Market by Application
8.3.3.5.2. Australia Machine to Machine (M2M) Healthcare Market by Component
8.3.3.6. Rest of Asia-Pacific Machine to Machine (M2M) Healthcare Market
8.3.3.6.1. Rest of Asia-Pacific Machine to Machine (M2M) Healthcare Market by Application
8.3.3.6.2. Rest of Asia-Pacific Machine to Machine (M2M) Healthcare Market by Component
8.4. RoW
8.4.1. RoW Machine to Machine (M2M) Healthcare Market by Application
8.4.2. RoW Machine to Machine (M2M) Healthcare Market by Component
8.4.3. RoW Machine to Machine (M2M) Healthcare Market by Sub-region
8.4.3.1. Latin America Machine to Machine (M2M) Healthcare Market
8.4.3.1.1. Latin America Machine to Machine (M2M) Healthcare Market by Application
8.4.3.1.2. Latin America Machine to Machine (M2M) Healthcare Market by Component
8.4.3.2. Middle East Machine to Machine (M2M) Healthcare Market
8.4.3.2.1. Middle East Machine to Machine (M2M) Healthcare Market by Application
8.4.3.2.2. Middle East Machine to Machine (M2M) Healthcare Market by Component
8.4.3.3. Africa Machine to Machine (M2M) Healthcare Market
8.4.3.3.1. Africa Machine to Machine (M2M) Healthcare Market by Application
8.4.3.3.2. Africa Machine to Machine (M2M) Healthcare Market by Component
Browse Complete Report@ https://www.infiniumglobalresearch.com/market-reports/global-machine-to-machine-m2m-healthcare-market
Reasons to Buy this Report:
=> Comprehensive analysis of global as well as regional markets of machine to machine (m2m) healthcare.
=> Complete coverage of all the product types and application segments to analyze the trends, developments, and forecast of market size up to 2030.
=> Comprehensive analysis of the companies operating in this market. The company profile includes an analysis of the product portfolio, revenue, SWOT analysis, and the latest developments of the company. 
 => Infinium Global Research- Growth Matrix presents an analysis of the product segments and geographies that market players should focus on to invest, consolidate, expand, and/or diversify.
About Infinium Global Research:
Infinium Global Research is a business consulting and market research firm; a group of experts that caters to fulfilling business and market research needs of leading companies in various industry verticals and business segments. The company also serves government bodies, institutes, and non-profit/non-government organizations to meet their knowledge and information needs.
Through our information services and solutions, we assist our clients to improve their performance and assess the market conditions to achieve their organizational goals. Our team of experts and analysts are engaged in continuously monitoring and assessing the market conditions to provide knowledge support to our clients. To help our clients and to stay updated with the advances and inventions in technology, business processes, regulations, and the environment, Infinium often conducts regular meets with industry experts and opinion leaders. Our key opinion leaders are involved in monitoring and assessing the progress in the business environment, so as to offer the best opinion to our clients.
Contact:Infinium Global Research2nd Floor, Ganadish Empire,Rahatani Chowk, Pimple Saudagar,Pimpri-Chinchwad, Maharashtra 411027Phone: +918999930634Email: [email protected] Website: www.infiniumglobalresearch.com
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Data Center Chip Market Size was Valued at USD 11.7 Billion in 2022 and is Expected to Reach USD 45.3 Billion by 2032 at a CAGR of 14.6% | Valuates Reports

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BANGALORE, India, July 26, 2024 /PRNewswire/ — Data Center Chip Market By Chip Type (GPU, ASIC, FPGA, CPU, Others), By Data Center Size (Small and Medium Size, Large Size), By Industry Verticals (BFSI, Manufacturing, Government, IT and Telecom, Retail, Transportation, Energy and Utilities, Others): Global Opportunity Analysis and Industry Forecast, 2023-2032.

The Data Center Chip Market was valued at USD 11.7 Billion in 2022, and is estimated to reach USD 45.3 Billion by 2032, growing at a CAGR of 14.6% from 2023 to 2032.
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Major Factors Driving the Growth of Data Center Chip Market
Because of the growing need for data processing and storage solutions brought about by the quick development of cloud computing, artificial intelligence, and big data analytics, the data center chip market is expanding significantly. High-performance chips are necessary for data centers to process massive volumes of data quickly and efficiently. As a result, advances in chip technology, including CPUs, GPUs, and specialist AI processors, have been made. The need for more resilient and scalable data center infrastructure is fueled in part by the expansion of digital services and Internet of Things (IoT) devices. The market is expanding due to key areas including Asia-Pacific, with its investments in technology and fast digital transformation, and North America, with its top tech businesses and vast data center networks.
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TRENDS INFLUENCING THE GROWTH OF THE DATA CENTER CHIP MARKET:
In data centers, Graphics Processing Units (GPUs) are essential for speeding up computing operations and data processing. They are perfect for managing workloads related to artificial intelligence (AI), machine learning, and large-scale data analytics because of their parallel processing capabilities. The need for GPUs in data centers is growing as these technologies become increasingly essential to corporate operations. Businesses are purchasing GPUs in order to increase the effectiveness of their data processing, lower latency, and boost overall performance. The need for data center chips is being driven by the increasing reliance on GPUs for sophisticated computing activities, which is considerably contributing to the market’s rise. This need is further increased by the growing use of AI and machine learning in a variety of sectors, which puts GPUs at the forefront of the data center semiconductor industry.
Compared to general-purpose chips, Application Specific Integrated Circuits (ASICs) provide better performance and efficiency since they are designed specifically for a given application. ASICs are extensively utilized in data centers for specific tasks including networking, data compression, and encryption. ASICs are becoming more and more common as a result of the growth of cloud computing, big data analytics, and blockchain technology, which has increased demand for high-performance, energy-efficient processors. Their capacity to provide tailored performance for certain applications aids data centers in better workload management, power conservation, and operating expense reduction. The market is expanding as a result of the increased preference for ASICs in data centers, which is fueling the need for specialized data center chips.
Large data centers are important users of data center chips; they are run by well-known IT firms and cloud service providers. To manage enormous volumes of data and provide a wide range of services, these facilities need a great deal of processing power and sophisticated computing skills. High-performance data center chips are becoming more and more necessary as a result of the growth of massive data centers and the rising demand for online streaming, cloud services, and digital transactions. These chips are necessary to ensure effective data management, processing, and storage, which helps big data centers fulfill the increasing expectations of its clientele. Large data center proliferation is anticipated to considerably boost the data center chip industry as the digital economy continues to grow.
Data centers are becoming more and more important to the Banking, Financial Services, and Insurance (BFSI) industry as a means of safely and effectively managing high transaction volumes, consumer data, and financial records. The need for sophisticated data center processors is being driven by the sector’s requirement for real-time data processing, high-performance computing, and strong security measures. BFSI organizations may improve their operational efficiency, guarantee data integrity, and deliver superior client services by utilizing data centers fitted with robust chips. The BFSI sector’s need for data center chips is being driven by the increasing use of online banking, digital banking, and financial analytics tools, all of which increase the requirement for sophisticated data center infrastructure.
The market for data center chips is significantly influenced by the cloud computing industry’s explosive growth. There is a growing need for scalable, effective, and high-performance data center infrastructure as more companies move their operations to the cloud. In order to handle enormous volumes of data, facilitate virtualization, and guarantee flawless service delivery, cloud service providers need sophisticated data center chips. Sturdy data center chips are becoming more and more necessary as cloud-based solutions become more and more popular. Benefits like cost savings, flexibility, and scalability are driving this trend. In places like North America and Europe, where cloud adoption rates are high and data center chip demand is rising rapidly, this tendency is especially significant.
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DATA CENTER CHIP MARKET SHARE
In 2022, North America gained a sizable portion of the market.
In 2022, the GPU made up the largest portion of the market share.
Throughout the projection period, large data centers are expected to gain a significant portion.
The BFSI market is anticipated to be one of the most profitable markets.
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Key Companies:
Advanced Micro Devices IncTaiwan Semiconductor Manufacturing Company LimitedBroadcomHuawei Technologies Co LtdIntel CorporationNVidia CorporationSamsung Electronics Co LtdQualcomm Technologies IncGlobalFoundriesARM LIMITED (SOFTBANK GROUP CORP.)Purchase Chapters @ https://reports.valuates.com/request/chaptercost/ALLI-Auto-2B326/Data_Center_Chip_Market
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DISCOVER MORE INSIGHTS: EXPLORE SIMILAR REPORTS!
–  The global modular data center market size was valued at USD 14,952 Million in 2019 and is projected to reach USD 59,971 Million by 2027, registering a CAGR of 18.7% from 2020 to 2027.
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–  According to a new report published by , titled, “Big Data Analytics in Semiconductor & Electronics Market,” The big data analytics in semiconductor & electronics market was valued at D18.7 billion in 2021, and is estimated to reach D47.2 billion by 2031, growing at a CAGR of 9.9% from 2022 to 2031.
–  IoT market was valued at USD 34250 Million in 2023 and is anticipated to reach USD 74630 Million by 2030, witnessing a CAGR of 11.6% during the forecast period 2024-2030.
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Industry 4.0 Market to Surpass USD 513.89 Billion by 2031 with Automation Surge | SkyQuest Technology

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WESTFORD, Mass., July 26, 2024 /PRNewswire/ — According to SkyQuest, the global Industry 4.0 Market size was valued at USD 133.05 billion in 2022 and is poised to grow from USD 154.6 billion in 2023 to USD 513.89 billion by 2031, growing at a CAGR of 16.2% during the forecast period (2024-2031).

Industry 4.0 or the fourth industrial revolution emphasizes the use of automation and interconnectivity. Employment of advanced technologies such as artificial intelligence, machine learning, robotics, and connected devices to improve the productivity and efficiency of industries. Rapid digitization and advancements in technology are forecasted to bolster the Industry 4.0 market growth over the coming years. The global Industry 4.0 market is segmented into technology, industry vertical, and region. 
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Industry 4.0 Market Overview:
Report Coverage
Details
Market Revenue in 2023
$ 154.6 billion
Estimated Value by 2031
$ 513.89 billion
Growth Rate
Poised to grow at a CAGR of 16.2%
Forecast Period
2024–2031
Forecast Units
Value (USD Billion)
Report Coverage
Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
Segments Covered
Technology, Industry and Region
Geographies Covered
North America, Europe, Asia Pacific, Latin America, and Middle East and Africa.
Report Highlights
Internet of Things (IoT) technology takes centerstage for Industry 4.0 adoption
Key Market Opportunities
Adoption of smart manufacturing and additive manufacturing practices
Key Market Drivers
Rising demand for automation across all industry verticals
Segments covered in Industry 4.0 Market are as follows:
TechnologyRobots (Traditional Industrial Robots {Articulated robots, Cartesian Robots, Selective Compliance Assembly Robot Arm (SCARA), Cylindrical Robots, Others}, Collaborative Robots), Blockchain in Manufacturing, Industrial Sensors (Level Sensors, Temperature Sensors, Flow Sensors, Position Sensors, Pressure Sensors, Force Sensors, Humidity & Moisture Sensors, Gas Sensors), Industrial 3D Printing, Machine Vision (Camera {Digital Camera, Smart Camera}, Frame Grabbers, Optics, and LED Lighting, Processor and Software), HMI (Offering {Hardware [Basic HMI, Advanced Panel-based HMI, Advanced PC-based HMI, Others], Software [On-premises HMI, Cloud-based HMI], Services}), Configuration ({Embedded HMI, Standalone HMI}, Technology {Motion HMI, Bionic HMI, Tactile HMI, Acoustic HMI}, End-user Industry {Process industries [Oil & Gas, Food & beverages, Pharmaceuticals, Chemicals, Energy & power, Metals & mining, Water & wastewater, Others], Discrete industry [Automotive, Aerospace & defense, Packaging, Medical devices, Semiconductor & electronics, Others]}), AI In Manufacturing (Offering {Hardware [Processor MPU, GPU, FPGA, ASIC, Memory, Network], Software [AI solutions- | On-premises, Cloud |, AI platform- | Machine learning framework, Application program interface |], Services [Deployment & integration, Support & maintenance]}, Technology {Machine learning [Deep learning, Supervised learning, Reinforcement learning, Reinforcement learning, Others], Natural language processing [Context-aware computing, Computer vision]}, Application {Predictive maintenance and machinery inspection, Material movement, Production planning, Field services, Quality control, Cybersecurity, Industrial robots, Reclamation}, Digital Twin {Technology [Internet of Things (IOT), Blockchain, Artificial intelligence & machine learning, Artificial intelligence & machine learning, Big data analytics, 5G], Usage Type [Product digital twin, Process digital twin, System digital twin], Application [Product design & development, Performance monitoring, Predictive maintenance, Inventory management, Business optimization, Others]}, Automated Guided Vehicles (AGV) {Type [Tow vehicles, Unit load carriers, Pallet trucks, Assembly line vehicles, Forklift trucks, Others], Navigation Technology [Laser guidance, Magnetic guidance, Inductive guidance, Optical tape guidance, Vision guidance, Others]}, Machine Condition Monitoring {Monitoring Technique [Vibration monitoring, Embedded systems, Vibration analyzers and meters, Thermography, Oil analysis, Corrosion monitoring, Ultrasound emission, Motor current analysis], Offering [Hardware – Vibration sensors, Accelerometers, Tachometers, Infrared sensors, Spectrometers, Ultrasound detectors, Spectrum analyzers, Corrosion probes], Software [Data integration, Diagnostic reporting, Order tracking analysis, Parameter calculation], Deployment Type [On-premises deployment, Cloud deployment], Monitoring Process [Online condition monitoring, Portable condition monitoring]})IndustryManufacturing, Automotive, Energy, Medical, Semiconductor & Electronics, Food & Beverage, Oil & Gas, Aerospace, Metals & Mining, Chemicals, and OthersRequest Free Customization of this report: 
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Internet of Things (IoT) Technology to Remain Indispensable for Industry 4.0
Internet of Things (IoT) remains the most crucial technology in global Industry 4.0 market growth owing to its role in interconnectivity and automation across different verticals. Advancements in connectivity technologies and rising use of automation in different industry verticals are also estimated to help this sub-segment gain an impressive market share. Surging demand for predictive maintenance will also boost the adoption of IoT technology in the long run.
Advanced robotic technologies are also slated to gain traction in the Industry 4.0 market. Growing acceptance of robots and high investments in advancements of robotic technologies are also slated to create new opportunities for providers of advanced robotics in the Industry 4.0 market. The low margin of error and the immense scope of automation are key benefits of robotics that help this sub-segment flourish.
Artificial intelligence (AI) will be another popular technology in the Industry 4.0 world going forward. Increasing demand for continuous monitoring, real-time analytics, and predictive maintenance are slated to help the demand for artificial intelligence in the future. The rising use of IoT devices will also boost the demand for cloud computing technology in the long run.
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Manufacturing Vertical to Spearhead Industry 4.0 Market Development
The manufacturing vertical is estimated to be at the forefront when it comes to Industry 4.0 adoption. The surge in use of robotics, advanced technologies, and smart manufacturing practices sets the tone for Industry 4.0 in this industry vertical. High emphasis on improving manufacturing efficiency, reducing downtime, and maximizing profits are all contributing to the high market share of this sub-segment.
The automotive industry is another vertical where Industry 4.0 market players could invest to get good returns. The high adoption of advanced robotics and other smart manufacturing technologies to maximize production allows this sub-segment to become a crucial one for Industry 4.0 providers. The aerospace and defense industry vertical also shows a lot of promise for Industry 4.0 companies going forward. Growing demand for advanced manufacturing techniques and technologies to create complex aerospace components is helping Industry 4.0 market growth via this segment.
The oil & gas industry is also estimated to embrace Industry 4.0 trend with open hands as they try to improve their operations and promote better resource utilization. High demand for predictive maintenance to reduce downtime and the growing adoption of digital oilfield solutions are estimated to bolster Industry 4.0 market development in the long run.
To sum it up, the application scope for Industry 4.0 is endless as automation and digitization pick up pace around the world. High investments in development of IoT and AI technologies will create better opportunities for Industry 4.0 companies in the future. The manufacturing industry will remain the top revenue generating sub-segment and more opportunities for aerospace, automotive, and oil & gas verticals will be seen over the coming years.
Related Report:
Digital Twin Market
Cyber Security Market
Artificial Intelligence (AI) Market
Internet Of Things (IoT) Market
Machine Learning Market
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Artificial Intelligence

Generative AI Cybersecurity Market worth $40.1 billion by 2030 – Exclusive Report by MarketsandMarkets™

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generative-ai-cybersecurity-market-worth-$40.1-billion-by-2030-–-exclusive-report-by-marketsandmarkets™

CHICAGO, July 26, 2024 /PRNewswire/ — The Generative AI cybersecurity Market is anticipated to experience substantial expansion, ascending from a value of USD 7.1 billion in 2024 to a substantial worth of USD 40.1 billion by the year 2030, according to a new report by MarketsandMarkets™. This growth trajectory reflects a robust compound annual growth rate (CAGR) of 33.4% over the forecast period.

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350 – Tables 60 – Figures450 – Pages
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Scope of the Report
Report Metrics
Details
Market size available for years
2019–2030
Base year considered
2023
Forecast period
2024–2030
Forecast units
USD (Million)
Segments Covered
Offering, Generative AI-based Cybersecurity, Cybersecurity for Generative AI, Security Type, End-user, and Region
Geographies covered
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
Companies covered
Microsoft (US), IBM (US), Google (US), SentinelOne (US), AWS (US), NVIDIA (US), Cisco (US), CrowdStrike (US), Fortinet (US), Zscaler (US), Trend Micro (Japan), Palo Alto Networks (US), BlackBerry (Canada), Darktrace (UK), F5 (US), Okta (US), Sangfor (China), SecurityScorecard (US), Sophos (UK), Broadcom (US), Trellix (US), Veracode (US), LexisNexis (US), Abnormal Security (US), Adversa AI (Israel), Aquasec (US), BigID (US), Checkmarx (US), Cohesity (US), Credo AI (US), Cybereason (US), DeepKeep (Israel), Elastic NV (US), Flashpoint (US), Lakera (US), MOSTLY AI (Austria), Recorded Future (US), Secureframe (US), Skyflow (US), SlashNext (US), Snyk (US), Tenable (US), TrojAI (Canada), VirusTotal (Spain), XenonStack (UAE), and Zerofox (US).
This dramatic surge is being fueled by a number of causes. The primary growth driver is the enhancement of existing cybersecurity tools through generative AI algorithms by improving anomaly detection, automating threat hunting and penetration testing, and providing complex simulations for security testing purposes. These techniques enable various cyber-attack scenarios that can be simulated using the Generative Adversarial Networks (GANs), thus enabling the development of better preparedness and response strategies. On the other hand, it requires special cyber security tools to protect generative AI workloads against unique vulnerabilities such as adversarial attacks, model inversions and LLM poisoning. These tools include differential privacy and secure multi-party computation that are integrated into AI systems for training and deployment data protection purposes.
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Generative AI apps security segment will account for largest market share during the forecast period.
The cybersecurity landscape is rapidly changing for generative AI apps, which are already making their way into chatbots, content creation tools like word processors, and personalized recommendation systems. According to McAfee, 55% of these programs have had security breaches. This highlights the dire need for stronger protective measures from unauthorized access. Several generative AI applications that use adversarial techniques to force the desired reaction out of intelligent machines.
Therefore, there is a pressing demand in the number of developers who ensure that such machines are made more robust through techniques like adversarially trained models and resistant architectures. Finally, the usage of secure enclaves plus hardware-based security measures is growing off late, mainly aimed at safeguarding vulnerable AI computations from being tampered with. For instance, OpenAI has very strict security rules meant to protect GPT models thereby ensuring data integrity and user privacy.
By end-user, government & defense sector is poised to account for larger market share in 2024.
Government as well as defense industries are increasingly resorting to generative AI for cyber security purposes due to the urgency of protecting sensitive information and national security. According to a recent CSIS report, AI is being integrated into the cybersecurity framework of 43% of government agencies which resultantly improves their ability to identify and counter threats. As an example, the United States Department of Defense has started using artificial intelligence (AI) based security solutions backed by generative AI that can create fictitious cyber-attacks, thereby providing them with enhanced preparedness against advanced types of threats.
This technology also helps these sectors handle and analyze large volumes of data more effectively, giving valuable insights that will enable them prevent or mitigate cyber threats. This trend demonstrates an increasing reliance on generative AI in fortifying cyber security measures so as to ensure that critical infrastructure and sensitive data remain secure in today’s intricate digital landscape.
By region, North America to hold the largest share by market value in 2024.
In 2024, North America will be the leading region based on market share due to its excellent technology infrastructure, substantial investments in AI-enabled cybersecurity and the presence of key players. Major cyber security research universities and tech companies such as Google, AWS, CrowdStrike, SentinelOne and IBM are present in this area, pushing them on the forefront of potent risk management technologies and generative AI tools for threat detection. For example, IBM’s security platform powered by AI has improved detection rates for threats up by 40%, thus proving the relevance of AI technology to enhancing cybersecurity.
Moreover, legislative instruments such as Cybersecurity Information Sharing Act (CISA) are being put in place to promote advanced cybersecurity technologies. As internet attacks continue getting more complicated, North American enterprises prefer generative artificial intelligence (AI), so as to enhance their safety measures pertaining to personal data and digital infrastructure.
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Top Key Companies in Generative AI cybersecurity Market:
The major players in the generative AI cybersecurity market include Palo Alto Networks (US), AWS (US), CrowdStrike (US), SentinelOne (US), and Google (US), along with SMEs and startups such as MOSTLY AI (Austria), XenonStack (UAE), BigID (US), Abnormal Security (US), and Adversa AI (Israel).
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Artificial Intelligence in Cybersecurity Market – Global Forecast to 2028
Explainable AI Market – Global Forecast to 2028
Artificial Intelligence (AI) Toolkit Market – Global Forecast to 2028
Get access to the latest updates on Generative AI cybersecurity Companies and Generative AI cybersecurity Industry
About MarketsandMarkets™
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MarketsandMarkets™ is a blue ocean alternative in growth consulting and program management, leveraging a man-machine offering to drive supernormal growth for progressive organizations in the B2B space. We have the widest lens on emerging technologies, making us proficient in co-creating supernormal growth for clients.
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Built on the ‘GIVE Growth’ principle, we work with several Forbes Global 2000 B2B companies – helping them stay relevant in a disruptive ecosystem. Our insights and strategies are molded by our industry experts, cutting-edge AI-powered Market Intelligence Cloud, and years of research. The KnowledgeStore™ (our Market Intelligence Cloud) integrates our research, facilitates an analysis of interconnections through a set of applications, helping clients look at the entire ecosystem and understand the revenue shifts happening in their industry.
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