Balancing Speed and Security: The AI Conundrum

As AI continues to advance at a rapid pace, CISOs and CIOs are faced with a crucial challenge: how to leverage the transformative power of AI while upholding the necessary human oversight and strategic thinking that security demands. The emergence of agentic AI is revolutionizing security operations, but achieving success requires a delicate balance between automation and accountability.

The Efficiency Paradox: Striking the Right Balance

The push to adopt AI in organizations is strong, with the aim of reducing workforce or reallocating resources to AI-driven projects. The potential benefits are significant, with AI capable of reducing investigation times from 60 minutes to just 5 minutes, leading to a tenfold increase in productivity for security analysts. However, the key question is not whether AI can automate tasks, but rather which tasks should be automated and where human judgment remains essential. While AI excels at accelerating investigative workflows, tasks such as remediation and response actions still require human validation. Making critical decisions autonomously could have unintended consequences, emphasizing the need for human involvement in these processes.

The Trust Deficit: Ensuring Transparency

Although confidence in AI’s ability to enhance efficiency is high, skepticism regarding the quality of AI-driven decisions remains prevalent. Security teams require more than just AI-generated conclusions; they need transparency into the decision-making process behind those conclusions. This transparency helps build trust in AI recommendations, allows for validation of AI logic, and fosters opportunities for continuous improvement. Ultimately, maintaining a human-in-the-loop for complex judgment calls is crucial, considering factors like business context, compliance requirements, and potential impacts.

The Adversarial Advantage: Using AI Defensively

AI offers both advantages and challenges in security, with attackers benefiting from lower barriers to entry due to AI tools. Defenders must exercise caution in implementing AI defensively to prevent vulnerabilities. Learning from attackers’ techniques while maintaining safeguards against AI becoming a vulnerability is essential. The recent rise of malicious MCP supply chain attacks highlights the speed at which adversaries exploit new AI infrastructure.

The Skills Dilemma: Balancing Automation and Skill Development

As AI takes on more routine investigative tasks, concerns arise about the potential atrophy of security professionals’ core skills. Organizations must implement strategies to balance AI-enabled efficiency with programs that uphold core competencies. This includes ongoing training, manual investigation exercises, and career development paths that evolve roles rather than eliminate them. Both employers and employees share the responsibility of ensuring that AI augments human expertise rather than replaces it.

The Identity Crisis: Managing the Agent Explosion

Identity and access management in an agentic AI environment pose significant challenges, with the projected increase in agents requiring robust governance frameworks. Overly permissive agents can introduce risks, highlighting the need for tool-based access control and careful governance strategies. Ensuring that agents have only the necessary permissions is crucial to prevent potential security breaches.

The Path Forward: Leveraging AI for Compliance and Reporting

Amid these challenges, leveraging AI for continuous compliance and risk reporting presents a high-impact opportunity. AI’s ability to process extensive documentation, interpret complex requirements, and generate concise reports can significantly enhance efficiency in security operations. This serves as a low-risk entry point for AI adoption in security.

The Data Foundation: Supporting AI-Powered SOC

Addressing fundamental data challenges is essential for the success of AI capabilities in security operations. A deliberate data strategy that prioritizes accessibility, quality, and unified data contexts is necessary. Security-relevant data should be readily available to AI agents, properly governed, and enriched with metadata to provide crucial business context.

Closing Thoughts: Embracing Innovation Intentionally

The autonomous SOC is not a one-time switch but an ongoing evolutionary journey that requires continuous adaptation. Success lies in embracing AI’s efficiency gains while upholding human judgment, strategic thinking, and ethical oversight. Rather than replacing security teams, the goal is to build collaborative multi-agent systems where human expertise guides AI toward optimal outcomes. This collaborative approach represents the promise of the agentic AI era, emphasizing the importance of intentional progress.

The article was authored by Tanya Faddoul, VP Product, Customer Strategy, and Chief of Staff for Splunk, a Cisco Company, and Michael Fanning, Chief Information Security Officer for Splunk, a Cisco Company. Cisco Data Fabric, powered by the Splunk Platform, offers a comprehensive data architecture to unlock the full potential of AI and SOC capabilities.

In conclusion, the journey towards an AI-powered security environment requires a thoughtful approach that integrates AI seamlessly while preserving human expertise. By embracing AI’s transformative potential and maintaining human oversight, organizations can enhance their security operations effectively.