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Automotive Camera Tier2 Suppliers Research Report 2022-2023: Increasing Performance of Automotive CIS Bolsters Adoption

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Dublin, May 02, 2023 (GLOBE NEWSWIRE) — The “Automotive Camera Tier2 Suppliers Research Report, 2022-2023” report has been added to ResearchAndMarkets.com’s offering.

1. The automotive camera market maintains a pattern of ‘one superpower and several great powers’

Automotive cameras are used to focus the light reflected from the target onto the CIS after refraction. From the automotive camera industry chain, it can be seen that main upstream companies are: lens, optical filter, and protective film companies which are committed to processing raw materials and making them into basic hardware such as lenses, optical filters and protective films; main downstream players are: Tier1 suppliers and camera module packaging companies.

At present, the automotive camera module market features a pattern of ‘one superpower and several great powers’, that is, Chinese manufacturer Sunny Optical Technology rules the roost, and Japanese, Korean and other Chinese manufacturers compete in the second echelon.

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‘One superpower’ is Sunny Optical Technology, the automotive camera industry bellwether that has grabbed the biggest share of the global market for many years in a row. The company shipped 67.98 million automotive cameras in 2021, and 78.91 million units in 2022, with a stable market share higher than 30%.

‘Several great powers’ refer to the several leaders in the second echelon, mainly Japanese, Korean and other Chinese manufacturers, commanding 2% to 10% of the market. The traditional ‘great powers’ are led by Japanese, Korean and Taiwanese optics companies, including Maxell (Japan), Nidec Sankyo (Japan), Sekonix (South Korea) and Largan Precision (China Taiwan). Among them, Maxell took an 8% share in the global automotive camera market in 2021.

Meanwhile Chinese companies such as Lianchuang Electronic Technology and OFILM begin to edge into the ‘great powers’ club.

Lianchuang Electronic Technology shipped about 8 to 9 million automotive cameras in 2022, and its major customers were Tier1 suppliers such as Valeo, Continental, Aptiv, ZF and Magna. OFILM set foot in automotive cameras by acquiring Fujifilm in 2018. Up to now, OFILM has mass-produced 5M front view cameras, 3M/8M side view cameras, 1M/2.5M surround view cameras, 2M electronic exterior mirror cameras, and 1M/2M in-cabin DMS/OMS cameras. In 2022, OFILM shipped about 4 million automotive cameras.

In addition, the established optics companies like Phenix Optics and Dongguan Yutong Optical Technology (YTOT) have also made deployments in the automotive market. Among them, Phoenix Optics has launched more than ten types of automotive cameras; YTOT, a leader in the field of security cameras, bought a 20% stake in Jiuzhou Optical in 2022, one of its attempts to step into the automotive camera market. In the future, these old optics companies will take further efforts to seize a share of the automotive camera market.

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2. Automotive CIS offers increasing performance, up to 8M resolution and 140dB HDR

The working process of CIS (CMOS image sensor) generally covers several links: reset, photoelectric conversion, integration, and readout.

In terms of the camera industry chain, the upstream CIS manufacturers include: CIS intellectual property (IP) companies specializing in CIS design and selling IPs to CIS companies; wafer companies providing silicon chips; OSAT companies engaged in cutting and packaging processed wafers. As with the automotive camera industry, downstream manufacturers are Tier 1 suppliers and camera module packaging companies.

In the trend for vehicle intelligence, the increasing camera pixels also pose higher technical requirements for CIS. As automotive cameras tend to be miniaturized and lightweight, pixel size cut and architecture upgrade have become most commonplace.

Take OmniVision’s CIS process iteration as an example: in the iteration of processes like OmniPixel3-HS, OmniBSIT and PureCelPlus, the pixel size has been reduced from 4.2um to 2.1um. By specific products, OX08B40 unveiled by OmniVision in 2021 delivers 8MP resolution and adopts the PureCel Plus-S pixel architecture, a technology that uses a stacked architecture for high resolution with a smaller chip size.

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In addition to resolution, HDR is also one of the key technical parameters of CIS. In type’s term, front/side view cameras have begun to pack 140dB HDR CIS, while rear/surround view cameras are still at the 120dB stage.

As core sensors for advanced AD, front/side view cameras need to quickly recognize details in brightness and darkness in different lighting conditions and accurately capture images when driving at high speeds. 120dB HDR therefore is the basic requirement, and 140dB HDR is the current trend. Some manufacturers have also laid out 140+dB HDR. One example is ONSemiconductor which announced the launch of a 150dB HDR vehicle CIS in October 2022 and planned to start producing it in 2024. In the future, CIS for ADAS may reach 150+dB HDR.

Rear/surround view cameras generally still offer 120dB, and will evolve to 140dB in the future. For example, CIS OX01E20 for surround/rear view, announced by OmniVision in 2023, supports 140dB HDR, 1.3MP resolution, and LED flicker mitigation (LFM).

3. Automotive ISP solutions tend to be diversified, and AI ISP will become a development trend

Among automotive camera component modules, ISP (image signal processor) is a core component for adjusting images. To achieve ideal imaging effects, ISP Tuning is an essential step.

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In addition to conventional ISPs, there are also another two types of mainstream ISP solutions: CIS integrated ISP, and ISP integrated autonomous driving SoC. The solutions become diversified.

The diversity of ISP solutions and the necessity of ISP Tuning make ISP seen in multiple links of the camera industry chain.

The importance of ISP and its low requirement for fixed hardware architecture make itself a high ground leading manufacturers from various fields contend to gain. Players often deploy 1 or 2 solutions.

For example, Fullhan Microelectronics specializes in ISP products; SmartSens has launched several ISP-integrated CIS products; OmniVision makes layout of ‘ISP + ISP-integrated CIS’; NXP and Nextchip deploy ‘ISP + ISP-integrated autonomous driving SoC’. Moreover, autonomous driving SoC companies like Mobileye, Nvidia and Black Sesame Technologies have also rolled out ISP-integrated autonomous driving chips.

Besides diversity of solutions, AI ISP is also an important development direction of ISP.

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ISP covers dozens of image signal processing algorithms, but the coordination of so many algorithms requires a lot of debugging efforts. At present, the development of visual ADAS systems still relies on manual ISP Tuning. OEMs like Tesla and NIO are still recruiting a large number of image quality tuning engineers. Yet manual tuning takes a long time and requires very specialist ISP Tuning engineers.

In recent years, using AI for image enhancement has gradually become a new research hotspot in the industry, having made remarkable progress. Applying AI for real-time tuning, especially the efficient implementation of AI ISP functions in the computing environment on the terminal side, can achieve better results than conventional ISP Tuning.

For example, Ambarella announced an artificial intelligence image signal processor (AISP). Ambarella’s new AI based ISP architecture uses neural networks to augment the image processing done by the hardware ISP integrated into its SoCs. This approach enables color imaging with low light at very low lux levels and minimal noise, a 10 to 100X improvement over state-of-the-art traditional ISPs, and new levels of high dynamic range (HDR) processing with more natural color reproduction and higher dynamic range.

Ambarella’s CV3 AI domain controller family already packs AISP, with up to 500 eTOPS of AI compute. The ISP can simultaneously support more than 20 cameras connected through MIPI VC, and can meet the requirements for high-performance stereo and dense optical-flow engines.

Key Topics Covered:

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1 Automotive Camera and Automotive Camera Industry Chain
1.1 Overview of Automotive Camera
1.2 Automotive Camera Industry Chain

2 Development Trends of Automotive Camera Industry Chain

3 Summary of Automotive Camera Industry Chain Companies and Products
3.1 Summary of Companies
3.2 Summary of Products

4 Automotive Camera Companies

5 Automotive CIS and ISP Companies

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6 Tier3 Companies in Camera Industry Chain

Companies Mentioned

  • Maxell
  • Nidec Sankyo
  • Sekonix
  • Sunny Optical Technology
  • OFILM
  • Lianchuang Electronic Technology
  • Dongguan Yutong Jiuzhou Optical
  • Phenix Optics
  • Largan Precision
  • ON Semiconductor
  • Sony
  • NXP
  • Nextchip
  • OmniVision
  • SmartSens
  • Fullhan Microelectronics
  • TI
  • Ambarella
  • Mobileye
  • Black Sesame Technologies
  • Horizon Robotics
  • Arm
  • Gowin Semiconductor
  • VeriSilicon

For more information about this report visit https://www.researchandmarkets.com/r/4a4efh

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Artificial Intelligence

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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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: 
https://www.skyquestt.com/sample-request/industry-4-0-market
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.
View report summary and Table of Contents (TOC): 
https://www.skyquestt.com/report/industry-4-0-market
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.
Contact: Mr. Jagraj SinghSkyQuest Technology1 Apache Way,Westford,Massachusetts 01886USA (+1) 351-333-4748Email: [email protected] Our Website: https://www.skyquestt.com/
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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.

Browse in-depth TOC on “Generative AI cybersecurity Market”
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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