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Diabetic Neuropathic Pain Market to Proliferate, Assesses DelveInsight | Key Companies Active in the Domain – AstraZeneca, Eli Lilly and Company, Eisai, Helixmith, Lexicon, NeurogesX, Centrexion, Pure Green Pharmaceuticals

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New York, USA, May 04, 2023 (GLOBE NEWSWIRE) — Diabetic Neuropathic Pain Market to Proliferate, Assesses DelveInsight | Key Companies Active in the Domain – AstraZeneca, Eli Lilly and Company, Eisai, Helixmith, Lexicon, NeurogesX, Centrexion, Pure Green Pharmaceuticals

The increasing prevalence of diabetes patients, rise in screening for pain among diabetics, increase in the geriatric population, and launch of newly approved drugs is likely to fuel the growth of the diabetic neuropathic pain market size during the forecast period (2023–2032).

DelveInsight’s Diabetic Neuropathic Pain Market Insights report includes a comprehensive understanding of current treatment practices, diabetic neuropathic pain emerging drugs, market share of individual therapies, and current and forecasted market size from 2019 to 2032, segmented into 7MM [the United States, the EU-4 (Italy, Spain, France, and Germany), the United Kingdom, and Japan].

Key Takeaways from the Diabetic Neuropathic Pain Market Report

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  • As per DelveInsight analysis, the diabetic neuropathic pain market is expected to grow positively owing to several underline factors during the study period (2019–2032).
  • DelveInsight’s analysis shows that diabetic neuropathic pain cases show an increasing trend in the forecasted period in the 7MM. 
  • Leading diabetic neuropathic pain companies such as AstraZeneca, Centrexion Therapeutics, Aptinyx, Pure Green Pharmaceuticals Inc., Eli Lilly and Company, Regenacy Pharmaceuticals LLC, Helixmith Co., Ltd., Vertex Pharmaceuticals Incorporated, Eisai Inc., NeuroBo Pharmaceuticals Inc., Dong-A ST Co., Ltd., Daiichi Sankyo, Inc., NeurogesX, Lexicon Pharmaceuticals, and others are developing novel diabetic neuropathic pain drugs that can be available in the diabetic neuropathic pain market in the coming years.
  • Some of the key therapies for diabetic neuropathic pain treatment include MEDI 7352, CNTX6016, NYX2925, CBD/PEA, LY3857210, Ricolinostat, Engensis, VX-548, E2007, DA-9801, DS-5565, Capsaicin Dermal Patch, LY3526318, LX9211, and others.
  • Several diabetic neuropathic pain therapies are awaiting approval, while some therapies are in the advanced stages of development. 

Discover which therapies are expected to grab the major diabetic neuropathic pain market share @ Diabetic Neuropathic Pain Market Report

Diabetic Neuropathic Pain Overview

Diabetic neuropathic pain is a well-known diabetes consequence and the leading cause of all neuropathic pain. Diabetic neuropathic pain affects almost one-third of all diabetic patients. It is defined as the presence of signs and symptoms of nerve dysfunction in diabetic individuals after all other explanations have been ruled out. Prolonged high blood sugar levels can harm nerves throughout the body, but diabetic neuropathic pain most impact the legs and feet.

Diabetic neuropathic pain is characterized by tingling, burning, sharp, shooting, lancinating feelings, and electric shocks. It is usually classified as moderate to severe, and it is often worse at night, causing sleep disruption. The discomfort might be persistent and accompanied by cutaneous allodynia, which can significantly impact the patient’s quality of life, limiting their capacity to do everyday tasks and negatively impacting their mood. Pain may also be a cause of withdrawal from recreational and social activities, and it may be linked to depression.

Diabetic Neuropathic Pain Epidemiology Segmentation

The diabetic neuropathic pain epidemiology section provides insights into the historical and current diabetic neuropathic pain patient pool and forecasted trends for the seven individual major countries. It helps recognize the causes of current and forecasted trends by exploring numerous studies and views of key opinion leaders.

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The diabetic neuropathic pain market report proffers epidemiological analysis for the study period 2019–2032 in the 7MM segmented into:

  • Total Diabetic Neuropathic Pain Prevalent Cases
  • Diabetic Neuropathic Pain Diagnosed and Treatable Cases
  • Diabetic Neuropathic Pain Gender-specific Cases  
  • Diabetic Neuropathic Pain Type-specific Cases  

Download the report to understand which factors are driving diabetic neuropathic pain epidemiology trends @ Diabetic Neuropathic Pain Epidemiological Insights

Diabetic Neuropathic Pain Treatment Market 

Current diabetic neuropathic pain treatment has two key goals: to target the underlying pathophysiological processes to avoid nerve fiber loss and reduce the unpleasant symptoms of PDN to normalize physical and psychological functioning. Tricyclic agents (TCAs), serotonin-norepinephrine reuptake inhibitors (SNRIs), or -aminobutyric acid (GABA) analogs (gabapentin or pregabalin) are commonly recommended as first-line medications, followed by opioids and topical therapies. Diabetic neuropathic pain is typically treated with TCAs, SNRIs, and GABA analogs. 

In September 2004, the SNRI duloxetine (Cymbalta, Eli Lilly) was licensed as the first medicine to treat the neuropathic pain associated with diabetic neuropathic pain. Duloxetine inhibits neuronal serotonin and norepinephrine reuptake. Although the specific mechanism of action of the drug’s central pain-inhibitory effect is unknown, it is thought to be connected to the potentiation of serotonergic and noradrenergic activity in the CNS. Blocking norepinephrine reuptake, in particular, has been shown to help with neuropathic pain.

Since the 1960s, traditional anticonvulsants have been utilized to treat neuropathy. However, in 2004, the FDA approved newer anticonvulsants, such as pregabalin, to treat DPN’s neuropathic pain. Because of its effectiveness in lowering pain and pain-related sleep disturbance, AAN guidelines recommend pregabalin as the first-line therapy for diabetic neuropathic pain treatment. Japan’s PMDA approved Mirogabalin for diabetic neuropathic pain treatment in 2019. Daiichi Sankyo is undertaking clinical research for Mirogabalin in the United States, with a planned launch within the study period. 

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To know more about diabetic neuropathic pain treatment, visit @ Diabetic Neuropathic Pain Treatment Drugs 

Key Diabetic Neuropathic Pain Therapies and Companies

  • MEDI 7352: AstraZeneca
  • CNTX6016: Centrexion Therapeutics
  • NYX2925: Aptinyx
  • CBD/PEA: Pure Green Pharmaceuticals Inc.
  • LY3857210: Eli Lilly and Company
  • Ricolinostat: Regenacy Pharmaceuticals LLC
  • Engensis: Helixmith Co., Ltd.
  • VX-548: Vertex Pharmaceuticals Incorporated
  • E2007: Eisai Inc.
  • DA-9801: NeuroBo Pharmaceuticals Inc./Dong-A ST Co., Ltd.
  • DS-5565: Daiichi Sankyo, Inc.
  • Capsaicin Dermal Patch: NeurogesX
  • LY3526318: Eli Lilly and Company
  • LX9211: Lexicon Pharmaceuticals

Learn more about the FDA-approved drugs for diabetic neuropathic pain @ Drugs for Diabetic Neuropathic Pain Treatment 

Diabetic Neuropathic Pain Market Dynamics

The diabetic neuropathic pain market is expected to change in the coming years. One of the primary aspects recognized to influence the growth of the neuropathic pain market is the discovery of new medications for the treatment of neuropathic and chronic pains. Companies are focused on clinical studies to find therapies to treat diabetic neuropathic pain effectively. For example, Eli Lilly produced duloxetine (LY248686) for diabetic peripheral neuropathic pain (DPNP), while Daichi developed mirogabalin for DPNP. Another factor driving the expansion of the diabetic peripheral neuropathic pain market is the development of point-of-care diagnostics to identify and evaluate diabetic peripheral neuropathic pain. DPNCheck by NeuroMetrix, for example, is a rapid, accurate, and quantitative nerve conduction test used to examine nerves to detect, stage, and monitor neuropathy objectively. 

Moreover, the diabetic neuropathic pain pipeline is highly robust; many possible therapies are being studied for diabetic neuropathic pain treatment, and it is safe to assume that the therapeutic space will substantially impact the diabetic neuropathic pain market throughout the forecast period. Furthermore, the expected introduction of emerging therapies with improved efficacy, more awareness initiatives programs, and a further improvement in the diagnosis rate will likely boost the growth of the diabetic neuropathic pain market in the 7MM.

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However, certain factors may affect the growth of the diabetic neuropathic pain market. The diabetic neuropathic pain market growth may be offset by failures and discontinuation of emerging therapies, unaffordable pricing, market access and reimbursement issues, and a shortage of healthcare specialists. In addition, the undiagnosed, unreported cases and the unawareness about the disease may also impact the diabetic neuropathic pain market growth.

Report Metrics Details
Study Period 2019–2032
Coverage 7MM [The United States, the EU-4 (Germany, France, Italy, and Spain), the United Kingdom, and Japan]
Base Year 2019
Key Diabetic Neuropathic Pain Companies AstraZeneca, Centrexion Therapeutics, Aptinyx, Pure Green Pharmaceuticals Inc., Eli Lilly and Company, Regenacy Pharmaceuticals LLC, Helixmith Co., Ltd., Vertex Pharmaceuticals Incorporated, Eisai Inc., NeuroBo Pharmaceuticals Inc., Dong-A ST Co., Ltd., Daiichi Sankyo, Inc., NeurogesX, Lexicon Pharmaceuticals, and others
Key Diabetic Neuropathic Pain Therapies MEDI 7352, CNTX6016, NYX2925, CBD/PEA, LY3857210, Ricolinostat, Engensis, VX-548, E2007, DA-9801, DS-5565, Capsaicin Dermal Patch, LY3526318, LX9211, and others

Scope of the Diabetic Neuropathic Pain Market Report

  • Therapeutic Assessment: Diabetic Neuropathic Pain current marketed and emerging therapies
  • Diabetic Neuropathic Pain Market Dynamics: Attribute Analysis of Emerging Diabetic Neuropathic Pain Drugs
  • Competitive Intelligence Analysis: SWOT analysis and Market entry strategies
  • Unmet Needs, KOL’s views, Analyst’s views, Diabetic Neuropathic Pain Market Access and Reimbursement

Discover more about diabetic neuropathic pain drugs in development @ Diabetic Neuropathic Pain Clinical Trials

Table of Contents

1. Diabetic Neuropathic Pain Market Key Insights
2. Diabetic Neuropathic Pain Market Report Introduction
3. Diabetic Neuropathic Pain Market Overview at a Glance
4. Diabetic Neuropathic Pain Market Executive Summary
5. Disease Background and Overview
6. Diabetic Neuropathic Pain Treatment and Management
7. Diabetic Neuropathic Pain Epidemiology and Patient Population
8. Patient Journey
9. Diabetic Neuropathic Pain Marketed Drugs
10. Diabetic Neuropathic Pain Emerging Drugs
11. Seven Major Diabetic Neuropathic Pain Market Analysis
12. Diabetic Neuropathic Pain Market Outlook
13. Potential of Current and Emerging Therapies
14. KOL Views
15. Unmet Needs
16. SWOT Analysis
17. Appendix
18. DelveInsight Capabilities
19. Disclaimer
20. About DelveInsight

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About DelveInsight

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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!
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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: 
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.
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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.
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Artificial Intelligence

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

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

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

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