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Predictive Maintenance Market worth $47.8 billion by 2029 – Exclusive Report by MarketsandMarkets™

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Real-time analysis and decision-making will be made easier by developments in AI and IoT integration, which will drive the Predictive Maintenance Market in the future. Innovation will be fueled by prognostics, industry-specific solutions, and interoperability, while Predictive Analytics as a Service (PAaaS) models will make advanced predictive maintenance skills more accessible to all.
CHICAGO, March 29, 2024 /PRNewswire/ — The Predictive Maintenance Market is estimated to grow from USD 10.6 billion in 2024 to USD 47.8 billion in 2029, at a CAGR of 35.1% during the forecast period, according to a new report by MarketsandMarkets™. The driving factors for the Predictive Maintenance Market include the widespread adoption of emerging technologies like IoT sensors and data analytics, enabling real-time monitoring of equipment health. The integration of machine learning (ML) and artificial intelligence (AI) algorithms allows for predictive analysis of potential failures, reducing downtime and optimizing asset performance. Organizations are increasingly focused on cost savings and operational efficiency, driving the need for proactive maintenance strategies to minimize unplanned downtime and maximize productivity. Additionally, regulatory requirements and the shift towards predictive analytics-driven decision-making further contribute to the growth of the Predictive Maintenance Market.

Browse in-depth TOC on “Predictive Maintenance Market”
280 – Tables 60 – Figures300 – Pages
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Scope of the Report
Report Metrics
Details
Market size available for years
2019–2029
Base year considered
2023
Forecast period
2024–2019
Forecast units
USD Billion
Segments Covered
Component (Hardware, Solution [Solution by Deployment mode {Cloud (Public, Private, Hybrid) & On-premises}] & Services), Technology (Analytics & Data Management, Artificial Intelligence, IoT Platform, Sensors & Other Devices), Technique (Vibration Analysis, Infrared Thermography, Acoustic Monitoring, Oil Analysis, Motor Circuit Analysis, Other Techniques) Organization size (Large Enterprises, SMEs), Vertical (Energy & Utilities, Manufacturing, Automotive & Transportation, Aerospace & Defense, Construction & Mining, Healthcare, Telecommunications) and Region.
Geographies covered
North America, Europe, Asia Pacific, Middle East & Africa, Latin America
Companies covered
IBM (US), ABB (Switzerland), Schneider Electric (France), AWS (US), Google (US), Microsoft (US), Hitachi (Japan), SAP (Germany), SAS Institute (US), Software AG (Germany), TIBCO Software (US), Altair (US), Oracle (US), Splunk (US), C3.ai (US), Emerson (US), GE (US), Honeywell (US), Siemens (Germany), PTC (US), Dingo (Australia), Uptake (US), Samotics (Netherlands), WaveScan (Singapore), Quadrical Ai (Canada), UpKeep (US), Limble (US), SenseGrow (US), Presage Insights (India), Falcon Labs (India).
By component, the services segment to account for higher CAGR during the forecast period.
The services segment plays a crucial role in the Predictive Maintenance Market, serving as a core component essential for the efficient operation of software solutions. Many companies are turning to intelligent devices, robust AI systems, and Industrial Internet of Things (IIoT) solutions to monitor the health and productivity of critical equipment, aiming to minimize costly production shutdowns. Remote monitoring of machinery and equipment has become a significant priority for organizations grappling with challenges in detecting machinery failures. The adoption of predictive maintenance services, including IoT, has become imperative to mitigate the risks and failures of machines across various industries. Within the services segment, managed and professional services are considered vital for enhancing overall process efficiency.
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By Technique, Vibration Analysis is expected to hold the largest market size for the year 2024.
Vibration analysis is a crucial technique employed primarily for high-speed rotating equipment in predictive maintenance strategies. It enables technicians to monitor the vibrations of machines using handheld analyzers or real-time sensors integrated into the equipment itself. Machines operating optimally exhibit specific vibration patterns, which can be compared against known standards. However, as components like bearings and shafts wear down or develop faults, they generate distinct vibration patterns, signaling potential issues. By continuously monitoring equipment vibrations, trained technicians can identify deviations from normal patterns and diagnose problems early on. The range of issues detectable through vibration analysis is extensive and includes misalignment, bent shafts, unbalanced components, loose mechanical parts, and motor irregularities.
By Vertical, Automotive & Transportation is projected to grow at the highest CAGR during the forecast period.
As automotive technology progresses rapidly, traditional fault detection methods are inadequate for ensuring vehicle smoothness. However, modern automobiles are equipped with various sensors, instruments, and cameras that generate diverse data. Leveraging this data, past service records, and employing AI and ML, predictive maintenance in the automotive & transportation sector emerges as a powerful solution to enhance vehicle performance and minimize downtime. The surge in intelligent technologies has spurred predictive maintenance investments in transportation, particularly accelerated by the Covid-19 crisis, where consumer preferences shifted towards individual mobility due to health and safety concerns, leading to an increased demand for cars. This demand surge, coupled with slowed new vehicle production, is driving the resurgence of the used car market. Predictive maintenance plays a crucial role in reducing the lifespan of used cars and preventing unexpected downtimes. Solutions like IBM’s monitoring for connected vehicles and collaborations between automakers and tech companies like Ford, CARUSO, and HIGH MOBILITY showcase the industry’s commitment to leveraging predictive maintenance for improved operations and customer services.
Middle East & Africa is expected to grow at the second-highest CAGR during the forecast period.
The Middle East & Africa (MEA) lacks technological development as well as primary business growth in many verticals. Slow economic growth and geopolitical conditions are the major hurdles to the growth of the Predictive Maintenance Market in the region. Moreover, it generates the majority of the revenues from natural resources. The government policy in the United Arab Emirates (UAE) is supportive of the industry with the vision to be one of the most technologically advanced nations by 2022. The proliferation of telecom and IT-enabled industry in the African countries is steering the growth of AI-based IoT companies in the region. The major reasons that are said to influence the growth of the Predictive Maintenance Market in the region are the increasing investments in data center infrastructures and the growing number of high-growth start-ups. Only a few countries, such as the UAE, Israel, and Qatar, across the region, are advancing in this market at an economical pace. The UAE, Israel, and Qatar have demonstrated a strong commitment toward the development and implementation of AI and IoT technologies.
Top Key Companies in Predictive Maintenance Market:
The major predictive maintenance hardware, solution and service providers include IBM (US), ABB (Switzerland), Schneider Electric (France), AWS (US), Google (US), Microsoft (US), Hitachi (Japan), SAP (Germany), SAS Institute (US), Software AG (Germany), TIBCO Software (US), Altair (US), Oracle (US), Splunk (US), C3.ai (US), Emerson (US), GE (US), Honeywell (US), Siemens (Germany), PTC (US), Dingo (Australia), Uptake (US), Samotics (Netherlands), WaveScan (Singapore), Quadrical Ai (Canada), UpKeep (US), Limble (US), SenseGrow (US), Presage Insights (India), Falcon Labs (India). These companies have used both organic and inorganic growth strategies such as product launches, acquisitions, and partnerships to strengthen their position in the Predictive Maintenance Market.
Recent Developments:
In January 2024, Siemens and AWS deepened their collaboration to simplify the development and scaling of generative artificial intelligence (AI) applications for businesses across various industries and sizes. This partnership enables domain experts in fields like engineering, manufacturing, logistics, insurance, or banking to leverage advanced generative AI technology to create and enhance applications efficiently.In December 2023, ABB enhanced its ABB Ability Field Information Manager (FIM 3.0) to provide system engineers and maintenance teams with enhanced connectivity and expanded reach across the latest communication protocols.In June 2023, Qatar Airways and Google Cloud partnered to create innovative data and artificial intelligence (AI) solutions tailored for the airline industry. This collaboration will concentrate on enhancing areas like predictive maintenance, passenger experience, and cargo operations, aiming to elevate efficiency and customer satisfaction within the airline sector.In April 2023, TrendMiner launched an updated version of its predictive maintenance software, the Digital Twin Manager. This release includes enhanced support for cloud data sources from AWS and Microsoft, along with interactive search functionality, enabling users to make data-driven decisions more efficiently.In January 2023, AVEVA, a global leader in industrial software, finalized its acquisition by Schneider Electric. AVEVA’s strategic objective is to emerge as the top Software as a Service (SaaS) provider in software and industrial information, transitioning to a subscription-only business model.Inquire Before Buying@ https://www.marketsandmarkets.com/Enquiry_Before_BuyingNew.asp?id=8656856
Predictive Maintenance Market Advantages:
Through proactive equipment maintenance based on data-driven insights, the prevention of expensive unplanned downtime, and the reduction of repair costs, predictive maintenance assists organisations in cutting maintenance costs.Predictive maintenance increases equipment availability and uptime by anticipating possible equipment faults before they happen, guaranteeing continuous operations and maximising output.By locating and resolving underlying problems that may compromise the dependability and efficiency of equipment, predictive maintenance extends the life of assets and lowers the need for untimely replacements.Predictive maintenance reduces the likelihood of mishaps, injuries, and interruptions to operations brought on by malfunctioning equipment by anticipating possible equipment breakdowns.By scheduling maintenance jobs more effectively, predictive maintenance helps businesses minimise interruptions to existing operations and match maintenance duties with production schedules.Using data analytics and machine learning algorithms, predictive maintenance produces actionable insights that help with equipment investments, resource allocation, and maintenance strategy selection.Predictive maintenance ensures continuous functioning and customer satisfaction by proactively addressing equipment concerns, minimising unplanned downtime and production losses.Status-based maintenance techniques, which optimise maintenance resources and cut down on pointless inspections and repairs by triggering maintenance actions based on real-time equipment status data, are made possible by predictive maintenance.Report Objectives
To describe and forecast the Predictive Maintenance Market, in terms of value,by component, technology, technique, organization size, and verticalTo describe and forecast the Predictive Maintenance Market, in terms of value,by region—North America, Europe, Asia Pacific, Middle East & Africa and Latin AmericaTo provide detailed information regarding major factors influencing the market growth (drivers, restraints, opportunities, and challenges)To strategically analyze micromarkets1 with respect to individual growth trends, prospects, and contribution to the overall Predictive Maintenance MarketTo profile key players and comprehensively analyze their market positions in terms of ranking and core competencies2, along with detailing the competitive landscape for market leadersTo analyze competitive developments such as joint ventures, mergers and acquisitions, product developments, and ongoing research and development (R&D) in the Predictive Maintenance MarketTo provide the illustrative segmentation, analysis, and projection of the main regional marketsBrowse Adjacent Markets: Analytics Market Research Reports & Consulting
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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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–  According to a new report published by , titled, “Data Processing Unit Market”, the data processing unit market was valued at D553.96 Million in 2021, and is estimated to reach D5.5 billion by 2031, growing at a CAGR of 26.9% from 2022 to 2031.
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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. 
Download a detailed overview: 
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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: 
https://www.skyquestt.com/speak-with-analyst/industry-4-0-market
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
About Us:
SkyQuest is an IP focused Research and Investment Bank and Accelerator of Technology and assets. We provide access to technologies, markets and finance across sectors viz. Life Sciences, CleanTech, AgriTech, NanoTech and Information & Communication Technology.
We work closely with innovators, inventors, innovation seekers, entrepreneurs, companies and investors alike in leveraging external sources of R&D. Moreover, we help them in optimizing the economic potential of their intellectual assets. Our experiences with innovation management and commercialization has expanded our reach across North America, Europe, ASEAN and Asia Pacific.
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Artificial Intelligence

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

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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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