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Artificial Intelligence

Generative AI Market worth $136.7 billion by 2030 – Exclusive Report by MarketsandMarkets™

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CHICAGO, April 29, 2024 /PRNewswire/ — Cross-domain applications, personalised content at scale, and increased creativity are what will define the Generative AI Market in the future. Innovation, human-AI cooperation, and ethical concerns will propel its advancement towards more responsible, significant, and adaptable uses in a variety of sectors.

The Generative AI Market is anticipated to experience substantial expansion, ascending from a value of USD 20.9 billion in 2024 to a substantial worth of USD 136.7 billion by the year 2030. This growth trajectory reflects a robust compound annual growth rate (CAGR) of 36.7% over the forecast period, according to a new report by MarketsandMarkets™. The surge in the Generative AI Market is poised to be driven by a confluence of influential factors within the business landscape. Notably, evolution of cloud storage technology simplifying data accessibility, coupled with the emergence of AI and deep learning technologies changing the landscape, stands out as significant contributors to this trend. Additionally, the upswing in content generation and the growing demand for innovative creative applications are playing a pivotal role in propelling the upward trajectory of this market.
Browse in-depth TOC on “Generative AI Market”
450 – Tables 80 – Figures550 – 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 (Billion)
Segments Covered
Offering, Data Modality, Application, Vertical, and Region
Geographies covered
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
Companies covered
IBM (US), NVIDIA (US), Open AI (US), Anthropic (US), Meta (US), Microsoft (US), Google (US), AWS (US), Adobe (US), Accenture (Ireland), Capgemini (France), Insilico Medicine (Hong Kong), Simplified (US), Lumen5 (Canada), AI21 Labs (Israel), Hugging Face (US), Dialpad (US), Persado (US), Copy.ai (US), Synthesis AI (US), Hypernetuse AI (US), Viable (US), Together AI (US), Defog.ai (Singapore), Mistral AI (France), Adept (US), DeepSearch Labs (UK), Stability AI (UK), Lightricks (Israel), Cohere (Canada), Writesonic (US), Colossyan (UK), amberSearch (Germany), Mosaic ML (US), Inflection AI (US), Glean (US), Jasper (US), Runway (US), Inworld AI (US), Typeface (US), Paige.AI (US), Upstage (South Korea), PlayHT (US), Speechify (US), Midjourney (US), Fireflies (US), InstaDeep (UK), Synthesis (UK), Mostly AI (Austria), Forethought (US), Character.ai (US), GFP-GAN (China), Fontjoy (Italy), EtherAI (US), Starry AI (US), Magic Studio (US), Balchuan AI (China), Salesforce (US), Technology Innovation Institute (Abu Dhabi), Abacus.AI (US), and OpenLM (US).
By software type, deep learning to register the largest market share during the forecast period.
Deep learning software type is projected to hold the largest market share in the Generative AI Market during the forecast period due to its unparalleled ability to manage complex and unstructured data. Deep learning algorithms, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), are at the forefront of generating realistic and diverse content, from images to text and audio. One notable trend related to deep learning software in this market is the increasing adoption of pre-trained models and transfer learning techniques, which enable faster deployment and customization of generative AI solutions for specific use cases. This trend streamlines the development process and reduces the need for extensive data labeling, making deep learning software more accessible and attractive to a wider range of industries and applications.
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By data modality, video segment is poised for the fastest growth rate during the forecast period.
Video data modality in the Generative AI Market is poised for the fastest growth rate during the forecast period due to the increasing popularity of video content across industries. Businesses are leveraging videos for marketing, customer engagement, training, and entertainment purposes, creating a massive demand for AI tools that can analyze and generate video content. Trends indicate a shift towards multi-modal generative AI, where systems can process not just text but also images, audio, and video. This trend is driving the development of AI models capable of understanding, editing, and even generating videos, enabling applications such as video synthesis, deepfake detection, and personalized video content creation. The rise of video-centric social media platforms and the integration of AI-driven video analysis into security and surveillance systems are further propelling the growth of the video data modality within the Generative AI Market.
By region, North America accounts for the largest market during forecast period.
The region boasts a robust ecosystem of technology companies, research institutions, and AI startups, fostering innovation and adoption of generative AI across industries. Additionally, North America leads in AI research and development, with major players like Google, Microsoft, and IBM investing heavily in generative AI technologies. Moreover, the region’s advanced infrastructure, favorable government initiatives, and early adoption of AI in sectors such as healthcare, finance, and automotive contribute to its market dominance. Contemporary trends in North America include the increasing use of generative AI in content creation, virtual assistants, and creative applications, driving further market growth and solidifying its position as a frontrunner in the global generative AI landscape.
Top Key Companies in Generative AI Market:
The major players in the Generative AI Market include Microsoft (US), OpenAI (US), Google (US), AWS (US), Adobe (US) along with startups such as Anthropic (US), Paige.AI (US), Midjourney (US), Jasper (US) and Synthesia (UK).
Recent Developments:
In March 2024, Microsoft and Adobe announced plans to bring Adobe Experience Cloud workflows and insights to Microsoft Copilot. The collaboration aims to leverage Microsoft 365 to help marketers overcome application and data silos and more efficiently manage everyday workflows.In March 2024, Adobe and NVIDIA, longstanding R&D partners, announced a new partnership to unlock the power of generative AI to further advance creative workflows. Adobe and NVIDIA will co-develop a new generation of advanced generative AI models with a focus on deep integration into applications the world’s leading creators and marketers use.In February 2024, the GSMA and IBM announced a new collaboration to support the adoption and skills of generative artificial intelligence (AI) in the telecom industry through the launch of GSMA Advance’s AI Training program and the GSMA Foundry Generative AI program.In February 2024, OpenAI announced the introduction of Sora, a text-to-video generative AI model. Sora can generate videos for up to a minute long while maintaining visual quality and adherence to the user’s prompt. This model is not publicly available as of now and limited access has been granted to handful of red teamers, visual artists, designers, and filmmakers.In February 2024, Google unveiled Gemini 1.5, an updated generative AI model that comes with long context understanding across different modalities. In the same month, Google also announced the launch of Gemma, a new family of lightweight open-weight models. Starting with Gemma 2B and Gemma 7B, these new models were “inspired by Gemini” and are available for commercial and research usage.In January 2024, Capgemini and AWS expanded their strategic collaboration to enable broad enterprise generative AI adoption. Through this collaboration, Capgemini and AWS are focusing on helping clients realize the business value of adopting generative AI while navigating challenges, including cost, scale, and trust.In December 2023, Microsoft launched InsightPilot, an automated data exploration system powered by a Generative AI. This innovative system is specifically designed to simplify the data exploration process. InsightPilot incorporates a set of meticulously designed analysis actions to simplify data exploration.In December 2023, Google unveiled an unprecedented Generative AI named VideoPoet, which is multimodal and capable of generating videos. This groundbreaking model introduces video generation functionalities previously unseen in generative AI.In December 2023, Axel Springer and OpenAI announced a global partnership to strengthen independent journalism in the age of artificial intelligence (AI). The initiative will enrich users’ experience with ChatGPT by adding recent and authoritative content on various topics and explicitly values the publisher’s role in contributing to OpenAI’s productsIn November 2023, OpenAI announced the launch of GPT-4 Turbo, a next-generation model of GPT-4. GPT-4 Turbo is more capable and has knowledge of world events up to April 2023. It has a 128k context window to fit the equivalent of more than three hundred pages of text in a single prompt.Inquire Before Buying@ https://www.marketsandmarkets.com/Enquiry_Before_BuyingNew.asp?id=142870584
Generative AI Market Advantages:
Businesses can now create a wide variety of high-quality material automatically, including text, images, videos, and music, thanks to generative AI, which makes it possible to produce creative assets quickly and widely.Personalised and customised content that is based on a person’s interests, behaviours, and demographics may be created thanks to generative AI, which increases consumer happiness and engagement.By streamlining the process of creating content, generative AI helps businesses create content more rapidly and cheaply by eliminating the need for manual labour and traditional production methods.By producing original designs, ideas, and concepts that would not have been investigated using more conventional techniques, generative AI promotes creativity and uniqueness in product development and marketing.In order to meet the changing needs and aspirations of both organisations and consumers, generative AI solutions are incredibly flexible and scalable. They can produce enormous volumes of content for a variety of platforms and formats.By eliminating the mistakes, inconsistencies, and variability that come with manual production, generative AI preserves brand identity and standards while guaranteeing consistency and quality control in content generation.With the use of generative AI, businesses can gain significant insights and possibilities to better understand customer preferences and market trends by analysing and producing insights from unstructured data sources, like text, voice, and images.Report Objectives
To define, describe, and predict the Generative AI Market by offering (software and services), data modality, application, vertical, and regionTo provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growthTo analyze the micro markets with respect to individual growth trends, prospects, and their contribution to the total marketTo analyze the opportunities in the market for stakeholders by identifying the high-growth segments of the Generative AI MarketTo analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leadersTo forecast the market size of segments for five main regions: North America, Europe, Asia Pacific, Middle East Africa, and Latin AmericaTo profile key players and comprehensively analyze their market rankings and core competencies.To analyze competitive developments, such as partnerships, new product launches, and mergers and acquisitions, in the Generative AI MarketTo analyze the impact of recession across all the regions across the Generative AI MarketBrowse Adjacent Markets: Artificial Intelligence (AI) Market Research Reports & Consulting
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Edge AI Software Market – Global Forecast to 2028
Data Fabric Market- Global Forecast to 2027
About MarketsandMarkets™
MarketsandMarkets™ has been recognized as one of America’s best management consulting firms by Forbes, as per their recent report.
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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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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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Artificial Intelligence

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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