Artificial intelligence and automation are helping companies across all industries improve their cybersecurity posture — but that doesn’t mean they are one and the same. Shrav Mehta, founder and CEO of Secureframe, explores the differences between AI and automation and how to know which technology is fit for purpose.
Organizations that use security AI and automation extensively have been able to identify and contain a data breach 108 days faster on average and save nearly $1.8 million, compared to organizations that do not use these tools at all.
But AI and automation are not completely interchangeable when it comes to security compliance. Nor can the entire compliance process be automated without the guidance and expertise of human auditors. However, companies may be able to harness the full potential of both AI and automation by using them in the specific areas where each technology can uniquely excel.
The differences between compliance AI and automation
Are AI and automation interchangeable when it comes to compliance? I get this question a lot, and my answer is that they are like apples and oranges. Because automation must be programmed, it requires humans to input explicit rules in order to carry out functions. AI, on the other hand, learns from data inputs and then makes logical decisions based on those data sets.
Today, many companies use automation to gather information for compliance reports, usually in order to receive certifications like SOC 2, ISO 27001, HIPAA and PCI DSS. Many automation tools can integrate with existing services to scan your cloud infrastructure and provide insight into how prepared you are for an audit, which is the first step in receiving any type of security certification.
AI, on the other hand, can be most effective in threat detection because it can learn how to identify real threats and dismiss false positives over time. Generative AI in cybersecurity, specifically, can produce algorithms that automatically scan network traffic for threats and provide insights on the behavior of malicious scripts.
AI & automation for compliance
Automation in compliance is best applied to tasks like evidence collection, centralizing compliance data and monitoring security controls. When put into practice, automation can save hundreds of hours answering requests for proposals and security questionnaires, which can dramatically speed up sales cycles without burning out additional internal resources.
Many compliance automation solutions will also flag issues and controls that are failing so that humans can be proactive in fixing them. This is useful for improving compliance processes and maintaining a strong security posture between audits. But while the system will flag issues, most won’t tell you how to fix them. That’s where AI can step in.
AI can augment human expertise by pulling data from the compliance system to generate tailored remediation guidance based on the organization’s specific configurations and infrastructure, which can dramatically improve test pass rates. AI can also be used very effectively to produce an inherent risk score, a treatment plan and a residual risk score so you can improve your company’s overall risk awareness and response plan.
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While both AI and automation can prove to be great assets, whether it’s automation helping cut down the prep time for a security audit or AI monitoring for regulatory changes, when it comes to defending against security threats, humans are still the most valuable resource.
Security teams bring contextual understanding to incidents because they can interpret the significance of events based on their knowledge of the organization’s infrastructure, business processes and threat history.
These professionals are also critical for instilling a culture of security, which may, paradoxically, be strained by the very presence of AI. A Cyberhaven report last year found that about 11% of the data employees put into ChatGPT was confidential. Your security team can teach employees to use AI tools responsibly, including how to leverage AI and automation without compromising the data privacy or security of the company.
A note on implementation
Every company will have a different system and tech stack, which means AI tools and automation will rarely be used in exactly the same way at every organization. It’s crucial to proceed with caution before jumping right into a subscription for a new security tool. When integrating a new tool, some of the most important areas of consideration should be:
- Compatibility: How the tool fits within your current tech stack.
- Data standardization: How the data within the tool is standardized, stored, processed, and anonymized.
- Performance optimization: How you will get the tool to perform its tasks in the most efficient way possible.
- Monitoring and training: How you will monitor usage of the tool and train employees to use it.
The highest security standards require all 3 components
AI is best suited for remediation and risk assessment, while automation is best applied to evidence collection and centralizing compliance data. Both are powerful tools in detecting threats, preventing cyber attacks and ensuring a company complies with rigorous security standards.
But importantly, skilled security experts are a required part of that equation. No organization can have the highest security standards without all three of these components working together effectively.