The Global AI Trust, Risk And Security Management Market size is expected to reach $8.2 billion by 2031, rising at a market growth of 20.3% CAGR during the forecast period.
Retail & e-commerce companies often employ dynamic pricing algorithms to adjust prices in real time based on factors like demand, competitor pricing, and customer behavior. Thus, the retail & e-commerce segment acquired $242.4 million revenue in 2023. AI trust, risk and security management solutions help retailers ensure the integrity and fairness of their pricing algorithms by detecting and preventing price manipulation attempts, protecting against revenue loss and customer dissatisfaction.
Traditional cybersecurity approaches often cannot keep pace with cyber threats' evolving sophistication. AI-driven threat intelligence systems employ advanced algorithms and machine learning techniques to evaluate large volumes of data, spot trends, and discover abnormalities that could be signs of criminal activity or security breaches. Therefore, increasing demand for AI-driven threat intelligence propels the market's growth.
Additionally, Cybercriminals continually develop more sophisticated attack techniques, including malware, ransomware, phishing, and insider threats. These advanced threats are designed to evade traditional security measures, posing significant risks to organizations' data, systems, and operations. Hence, escalating cybersecurity threats are driving the growth of the market.
However, the deployment of AI technologies often involves complex ecosystems comprising diverse components such as data sources, algorithms, models, and infrastructure. Integrating AI systems with existing IT infrastructure and workflows requires navigating compatibility issues, interoperability challenges, and data silos, which can hinder the seamless integration of AI trust, risk and security management solutions. Thus, complexity and integration challenges are hampering the growth of the market.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Acquisitions, and Partnerships & Collaborations.
Retail & e-commerce companies often employ dynamic pricing algorithms to adjust prices in real time based on factors like demand, competitor pricing, and customer behavior. Thus, the retail & e-commerce segment acquired $242.4 million revenue in 2023. AI trust, risk and security management solutions help retailers ensure the integrity and fairness of their pricing algorithms by detecting and preventing price manipulation attempts, protecting against revenue loss and customer dissatisfaction.
Traditional cybersecurity approaches often cannot keep pace with cyber threats' evolving sophistication. AI-driven threat intelligence systems employ advanced algorithms and machine learning techniques to evaluate large volumes of data, spot trends, and discover abnormalities that could be signs of criminal activity or security breaches. Therefore, increasing demand for AI-driven threat intelligence propels the market's growth.
Additionally, Cybercriminals continually develop more sophisticated attack techniques, including malware, ransomware, phishing, and insider threats. These advanced threats are designed to evade traditional security measures, posing significant risks to organizations' data, systems, and operations. Hence, escalating cybersecurity threats are driving the growth of the market.
However, the deployment of AI technologies often involves complex ecosystems comprising diverse components such as data sources, algorithms, models, and infrastructure. Integrating AI systems with existing IT infrastructure and workflows requires navigating compatibility issues, interoperability challenges, and data silos, which can hinder the seamless integration of AI trust, risk and security management solutions. Thus, complexity and integration challenges are hampering the growth of the market.
The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Acquisitions, and Partnerships & Collaborations.
By End-use Analysis
On the basis of End-use, the market is segmented into telecom & IT, BFSI, manufacturing, retail & ecommerce, healthcare, government, media & entertainment, and others. The IT & telecommunication segment attained 28% revenue share in the market in 2023.By Deployment Mode Analysis
By deployment, the market is divided into on-premises and cloud. The cloud segment procured a remarkable 37% revenue share in the market in 2023. Cloud deployment provides enhanced accessibility and flexibility.By Component Analysis
Based on component, the market is divided into solution and services. In 2023, the solution segment garnered the highest 75.4% revenue share in the market. Solutions offer comprehensive approaches to addressing trust, risk, and security concerns in AI deployments. These solutions typically include a combination of tools, technologies, and frameworks designed to assess, mitigate, and manage risks across the AI lifecycle, from data ingestion and model development to deployment and monitoring.By Application Analysis
Based on application, the market is categorized into governance & compliance, bias detection & mitigation, security & anomaly detection, and privacy management. The bias detection & mitigation segment witnessed a considerable 27% revenue share in the market in 2023. The segment’s growth can be attributed to the growing awareness among organizations about the adverse effects of biased AI, such as unfair discrimination and inaccurate results.By Type Analysis
On the basis of type, the is segmented into explainability, modelOps, data anomaly detection, data protection, and AI application security. The explainability segment recorded the largest 38.2% revenue share in the market in 2023.By Enterprise Size Analysis
Based on enterprise size, the market is divided into large enterprises and small & medium enterprise. In 2023, the small & medium enterprise segment procured a 32% remarkable revenue share in the market.By Regional Analysis
Region-wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America region witnessed 36% revenue share in the market in 2023. North America has stringent regulatory requirements and compliance standards for data privacy, cybersecurity, and financial services, such as the Health Insurance Portability and Accountability Act (HIPAA), the Payment Card Industry Data Security Standard (PCI DSS), and the Sarbanes-Oxley Act (SOX).Recent Strategies Deployed in the Market
- Jan-2024: ServiceNow, Inc. came into partnership with EY, a global professional services network provider. Under this partnership, ServiceNow would offer solutions for generative AI (GenAI) compliance, governance, and risk management. Additionally, the new service would upgrade solutions for generative AI (GenAI) compliance, governance, and risk management and enhance business practices of ethical, transparent, accounts.
- Dec-2023: IBM Corporation partnered with Palo Alto Networks, a global cybersecurity company. Through this acquisition, IBM would allow its clients to reinforce their end-to-end security position and control emerging security threats. Additionally, IBM would reduce the risk of cybersecurity threats that represent a risk to the operating models of the organization by making it important for security leaders to work cooperatively for the best of their clients.
- Nov-2023: IBM Corporation launched the QRadar SIEM product, designed particularly for hybrid cloud speed, scale, and flexibility. With the launch of QRadar, IBM would be able to guide the next generation of security operations designed for hybrid cloud and AI generation.
- Nov-2023: IBM Corporation released watsonx. governance to assist Businesses & Governments control and building trust in Generative AI. Through this product IBM would help businesses by providing them with the tools, they require to automate AI governance processes, to take corrective action, and monitor their models. The product would also have the potential to translate regulations into enforceable policies that would be useful for enterprises as new AI regulations.
- Oct-2023: IBM Corporation introduces the next advancements of its managed detection and response service. Through this service, IBM would increase the security defense potential of the organization from future threats. Additionally, this new service would automatically escalate to 85% of alerts.
List of Key Companies Profiled
- AT&T Inc.
- IBM Corporation
- LogicManager, Inc.
- RSA Security LLC (Symphony Technology Group)
- SAP SE
- SAS Institute, Inc.
- ServiceNow, Inc.
- Hewlett Packard enterprise Company
- Oracle Corporation
- Moody's Analytics, Inc. (Moody’s Corporation)
MarketReport Segmentation
By Deployment Mode
- On-premise
- Cloud
By Component
- Solution
- Services
By Application
- Governance & Compliance
- Bias Detection & Mitigation
- Security & Anomaly Detection
- Privacy Management
By Type
- Explainability
- ModelOps
- Data Anomaly Detection
- Data Protection
- AI Application Security
By Enterprise Size
- Large Enterprise
- Small & Medium Enterprise
By End-use
- Telecom & IT
- Government, Healthcare
- BFSI, Media & Entertainment
- Manufacturing
- Retail & eCommerce
- Others
By Geography
- North America
- US
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- South Korea
- Australia
- Malaysia
- Rest of Asia Pacific
- LAMEA
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market at a Glance
Chapter 3. Market Overview
Chapter 4. Competition Analysis - Global
Chapter 5. Global AI Trust, Risk And Security Management Market by Deployment Mode
Chapter 6. Global AI Trust, Risk And Security Management Market by Component
Chapter 7. Global AI Trust, Risk And Security Management Market by Application
Chapter 8. Global AI Trust, Risk And Security Management Market by Type
Chapter 9. Global AI Trust, Risk And Security Management Market by Enterprise Size
Chapter 10. Global AI Trust, Risk And Security Management Market by End-use
Chapter 11. Global AI Trust, Risk And Security Management Market by Region
Chapter 12. Company Profiles
Companies Mentioned
- AT&T Inc.
- IBM Corporation
- LogicManager, Inc.
- RSA Security LLC (Symphony Technology Group)
- SAP SE
- SAS Institute, Inc.
- ServiceNow, Inc.
- Hewlett Packard enterprise Company
- Oracle Corporation
- Moody's Analytics, Inc. (Moody’s Corporation)
Methodology
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