Introduction
The rise of Generative AI has brought about a transformative shift in the cybersecurity landscape, enabling new levels of automation, scalability, and efficiency in threat management. Statistics show that the security market in India grew from USD 1.98 billion in 2019 to USD 6.06 billion in 2023. However, despite its potential to enhance security, the integration of Generative AI into cybersecurity strategies presents a unique set of challenges. Risks such as data exposure, AI misuse, privacy violations, ethical concerns, and inherent biases in AI models can significantly undermine the effectiveness of security frameworks. In light of this, the Data Security Council of India released the report "Reimagining Security: A New Era Powered by Generative AI" (Report) on December 16, 2024, offering insights into emerging trends, challenges, and strategies for businesses navigating this evolving landscape.
This blog extracts the key findings of the Report and outlines essential compliance steps for businesses to effectively navigate the integration of Generative AI into their cybersecurity strategies.
Rise of Data Breaches & AI Solutions
As per the Report, the cybersecurity landscape is facing significant challenges, with the global cost of a data breach reaching $4.88 million in 2024. The Report highlights that in India alone, breach costs have surged by 39% from 2020 to 2024, totaling around $2.3 million. Moreover, a staggering 88% of breaches are attributed to human error, highlighting the urgent need for advanced security measures and comprehensive employee training.
The Report indicates that almost 35-40% of security providers have integrated Generative AI within two years, automating tasks like alert triaging, incident response, and data loss prevention. They are also using Generative AI for security by:
- enabling advanced threat detection, real-time incident response, and vulnerability assessments;
- enhancing data analysis, automation, and customer service;
- collaborating with industry partners, academia, and tech providers to access resources for AI implementation and developing in-house capabilities; and
- forming partnerships with system integrators and startups to support the integration of Generative AI into security systems.
Have a look at the table below to see real-life examples of how Generative AI has transformed cybersecurity across different industries and companies:
|
Company/Industry
|
Generative AI Application
|
Impact/Results
|
| Digital Payments |
AI-driven platform enabled 24/7 monitoring and threat detection. |
72% faster threat detection, 64% quicker response times, improved alert accuracy and reduced false positives. Enhanced overall security posture. |
| Quick Heal Technologies (Cybersecurity solution provider) |
Generative AI integrated into its XDR platform to automate incident triage, summarize threats, and provide real-time, context-specific insights. |
70% reduction in incident resolution time, enhanced threat-hunting capabilities, reduced backlog, and improved productivity on repetitive tasks. |
| Tech Mahindra (Vulnerability Management) |
Generative AI was applied to:
- assess the client's vulnerability management against NIST CSF;
- enhance reporting KPIs;
- automate workflows to conduct server scans;
- generate daily vulnerability dashboards;
- cross-reference CVE and NVD for insights; and
- document SOPs for threat, vulnerability, and patch management.
|
70% reduction in incident resolution time, improved visibility with AI-driven dashboards, and enhanced efficiency. |
Compliance Actions for Businesses Integrating Generative AI in Cybersecurity & How Securiti Can Help
To integrate Generative AI securely and effectively into cybersecurity frameworks, businesses must adopt structured compliance actions. The blog builds on the Report's recommendations by providing additional steps to suggest the following best practices to help businesses prevent breaches and cybersecurity incidents:
1. Develop an AI Integration Strategy
Developing a robust AI integration strategy is essential. In this regard, businesses should undertake the following recommendations:
- Architecture Design and Implementation: Create a high-level framework that outlines the overall security strategy and detailed technical specifications for individual components. Customized solutions should be designed to address the specific risk profile, followed by a comprehensive implementation plan.
- Align with Strategic Priorities: Based on organizational needs, prioritize AI applications such as threat detection, vulnerability assessment, and automated incident response.
- Plan for Scalability: Ensure the AI systems can scale to handle increased data loads or evolving threat landscapes without compromising performance.
Securiti's AI Security & Governance solution ensures safe and ethical AI operations by managing data security, privacy, and compliance.
2. Enhance Security Controls for Generative AI Systems
To enhance security control for Generative AI systems, businesses should consider the following recommendations:
- Detailed Risk Assessments and Testing: Regularly evaluate the potential risks associated with Generative AI, including data privacy breaches, model bias, and system vulnerabilities.
- Real-Time Threat Monitoring: Use AI-enabled tools to detect and respond to anomalies in real-time, such as unauthorized access or data exfiltration attempts.
- Automated Protocol Updates: Implement automated updates to AI models and security protocols to adapt to emerging threats and vulnerabilities.
- Integrate Role-Based AI Use: Restrict AI usage based on employee roles to ensure appropriate and ethical deployment.
- Continuous Model Testing: Perform regular testing of AI models, such as penetration testing, vulnerability scanning, and code reviews, to identify and address potential inaccuracies and weaknesses and ensure alignment with security benchmarks.
- Regular Audits: Conduct frequent audits of AI systems to ensure compliance with privacy laws or industry-specific frameworks. This also ensures completeness, accuracy, and security of data, which is essential for data used to train AI models.
- Monitor Output Accuracy: Validate AI outputs through human oversight and cross-verification with other trusted systems.
- Data Anonymization Techniques: Before integrating AI, anonymize sensitive datasets to protect against potential misuse or breaches.
- Access Controls: Enforce strict access control policies, including multi-factor authentication, to limit who can access AI-generated outputs and training datasets.
Securiti’s Data Security Posture Management empowers organizations to mitigate data breach risks, safeguard data sharing, and enhance compliance while minimizing the cost and complexity of implementing data controls.
Securiti’s Assessment solution helps organizations evaluate their internal protocols, ensuring the necessary technical and organizational measures are in place to prevent human errors.
3. Bolster Employee Preparedness
Employee preparedness is paramount. In this regard, businesses should implement the following recommendations:
- Specialized AI Training Programs: Provide targeted training for employees on Generative AI’s capabilities, risks, and ethical implications.
- Scenario-Based Drills: Conduct simulations using AI-generated scenarios to prepare teams for real-world incidents, such as phishing or ransomware attacks.
4. Design Comprehensive Incident Response Plans
To create comprehensive incident response plans, businesses should establish the following recommendations:
- AI-Specific Playbooks: Develop incident response protocols tailored to AI-specific threats, such as data manipulation or adversarial attacks.
- Automate Detection and Response: Leverage AI to prioritize incidents, predict vulnerabilities, and provide automated enforcement of security measures. Moreover, by implementing recovery measures, clients can minimize downtime and maintain business continuity even in the face of significant incidents.
Securiti’s Breach Management solution automates breach notifications and compliance actions, providing incident response workflows that help organizations respond to privacy incidents promptly and effectively.
5. Ensure Regulatory Compliance
Regulatory compliance may be achieved through the following recommendations:
- Compliance Mapping: Map AI applications to relevant regulatory requirements, ensuring adherence to data protection and cybersecurity laws.
- Maintaining Documentation: Record all AI system activities, including data use, model changes, and decision-making processes, to demonstrate compliance during audits.
Securiti’s Data Privacy solution automates compliance with evolving global privacy regulations and principles.
6. Increase Collaboration with Key Players
Businesses should engage in partnerships with tech providers, academic institutions, and industry coalitions to adopt cutting-edge solutions and share threat intelligence.
The following table presents the Report’s recommended framework for using Generative AI in cybersecurity for businesses:
|
Element
|
Focus Area
|
| Monitor |
Continuous surveillance of vulnerabilities, access points, and security gaps. |
| Generate |
Scenario modeling to simulate various threat levels for proactive readiness. |
| Develop Threat & Risk Cognition |
Building insights through threat pattern recognition and contextual visualization. |
| Protect |
Implementing integrity checks, automated enforcements, access controls, and privacy methods. |
| Seek Conformance |
Aligning with security standards, accuracy, and transparency benchmarks. |
| Adapt |
Evolving with threat dynamics and environmental shifts. |
Conclusion
Thus, as businesses navigate an increasingly complex threat landscape, the integration of AI, particularly Generative AI, emerges as a pivotal strategy for safeguarding their digital future. The ability to automate threat detection, enhance incident response, and adapt to evolving risks makes AI an invaluable tool for building resilient security systems. With nearly all organizations planning to increase cybersecurity investments, it’s clear that AI-driven solutions are not just an option—they’re a necessity if businesses want to stay ahead of sophisticated cyber threats, protect critical assets, and foster trust with stakeholders. Consequently, it's no longer just about security; it’s about enabling growth, innovation, and long-term success.
Securiti is the pioneer of the Data + AI Command Center, a centralized platform that enables the safe use of data and GenAI. It provides unified data intelligence, controls and orchestration across hybrid multicloud environments. Large global enterprises rely on Securiti's Data Command Center for data security, privacy, governance, and compliance.
Securiti Gencore AI enables organizations to safely connect to hundreds of data systems while preserving data controls and governance as data flows into modern GenAI systems. It is powered by a unique knowledge graph that maintains granular contextual insights about data and AI systems.
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