AI security risks are a growing concern as businesses adopt artificial intelligence across operations. From data breaches and system vulnerabilities to regulatory and ethical challenges, organizations face multiple threats when implementing AI. The ISO 42001 standard helps mitigate these risks, providing a framework for stronger security, compliance, and responsible AI governance.
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The Biggest AI Risks that ISO 42001 Mitigates
Artificial intelligence (AI) and machine learning (ML) tools have reshaped almost every industry since breaking containment in 2022-2023. But with the great processing and automation power they bring come risks related to misuse or mismanagement. The ISO 42001 standard was published to help organizations with the great responsibility of managing these kinds of risks.
In particular, the biggest impacts of ISO 42001 are felt across risks like:
- Data compromise situations stemming from careless uses of AI tools
- Security oversights and errors arising from over-reliance on automation
- Regulatory compliance complications and non-compliance penalties
- Ethical grey areas and reputational damage from perceived slights
Working with a compliance advisor well versed in AI technology and ISO 42001 in particular is the best way to take full advantage of this powerful technology while avoiding its inherent risks.
Risk #1: Data Compromise and Privacy Concerns
This is maybe the most straightforward risk of AI use. Exposing information to algorithmic processing has the potential to compromise its privacy. There are several ways it can happen, and there are different stakes and scenarios that impact the severity of the risk. But it is always present, in one form or another. Poor management of AI systems can result in a lack of strict parameters on the types of data they collect, where and how they collect it, how they use the information, and whether or how they store and expose it.
These factors mean that AI tools can access information that nobody should be able to; they can do things to that information (i.e., read, edit, or delete it) that should require permission and/or its subject’s consent; and they can store or otherwise output that information (or any derivations thereof) to locations or situations that further compromise its security and privacy.
The ISO 42001 standard addresses these and all other AI concerns from the perspective of effective management, or what it calls AI management systems (AIMS). Its controls require accountability and transparency, such that organizations can (and must) exert granular control over all of these variables. With an ISO 42001 implementation in place, AI systems should not compromise data unless they are instructed or designed to do so. It removes the accident quotient from the risk and makes leaders fully in control of—and responsible for—privacy.
Risk #2: Security Oversight from Ineffective AI Use
A less obvious risk of AI use that relates directly to security is the potential for cyberdefense and general IT infrastructure to lapse in terms of updates and other quality control measures. If an organization relies too heavily on automation for its daily maintenance and upkeep, without enough human oversight as a final buffer, then updates—or red flags—could be missed.
Imagine the following scenario, which could happen at any organization:
- An algorithm is set up to scan all data in a given location for a set of known threat indicators. If a known threat is detected, security teams are notified immediately.
- After a prolonged period without a threat emerging, human oversight becomes lax; eventually, stakeholders begin manually confirming security weekly rather than daily.
- An attacker launches a new vector unknown to the algorithm, infecting several files undetected. The automation fails to send any notice because it can’t detect the problem.
- When the responsible party manually checks the system, they discover that all files have been compromised and that the infection may now be spreading to other systems.
Again, this is a case of poor AI use and/or poor AI management leading to a security issue.
ISO 42001 was designed to solve these exact problems. The framework dedicates critical parts to accountability, resource allocation, awareness-building, and restricting levels of automation to prevent situations like this from occurring.
Risk #3: Regulatory Compliance Complications
The potential for oversight is especially impactful when it interacts with legally or otherwise mandatory regulatory compliance. If your organization is subject to one or more regulatory frameworks, you need to be extra careful about the ways in which you use AI and ML tools.
For example, consider these compliance contexts that are complicated by the use of AI:
- Industry-based – If your organization contracts with the US military, you’ll need to comply with the Cybersecurity Maturity Model Certification (CMMC). CMMC 2.0 has no explicit requirements related to AI, but the rapid data processing that AI makes possible could make it hard to meet requirements for access restriction by the least functionality.
- Operations-based – If your organization processes credit card information, you likely need to comply with the Payment Card Industry (PCI) Data Security Standard (DSS). AI restrictions are not presently a part of PCI DSS v4.0 compliance, but, similar to CMMC cybersecurity, PCI requires access restriction by “business need to know,” which could be hard to justify for AI tools that scrape cardholder data for nondescript reasons.
ISO 42001 itself is not yet a legally mandated standard in any global jurisdiction.
However, as AI regulations continue to evolve, national and localized governments are working on laws that may mirror or align with ISO 42001 guidelines. For instance, regulations like the EU AI Act and GDPR are already setting legal requirements around transparency, accountability, and AI governance. Organizations use ISO 42001 to proactively implement these best practices, preparing themselves to meet emerging regulatory requirements now and in the future.
Risk #4: Reputational Damage from Ethical Concerns
Finally, AI and ML tools carry ethical baggage in the potential for piracy and intellectual property theft. The training process of generative AI models can lead individuals to feel (rightly or wrongly) that their unique ideas have been stolen or that a model’s output closely matches their own. Regardless of the validity of these claims, they can damage an organization’s reputation if they gain enough public attention. The effect can be similar to that of a non-compliance violation: it becomes something associated with your team.
While this may not seem directly related to security, it can stir up motivation for a retaliatory cyberattack by an impacted stakeholder working either independently or with cybercriminals.
An insider attack from a disgruntled current or former employee is one of the most insidious threats to any organization, as they tend to be harder to identify until attackers have already established a strong position within your networks. Maintaining AI ethics is sound business practice because failing to do so could put a large and hard-to-remove target on your back.
ISO 42001 provides a framework for implementing ethical AI practices, ensuring transparency and fairness in AI decision-making, which can significantly reduce the risk of reputational damage and prevent insider threats. Effective management, per ISO 42001, ensures AI tools collect information in defensible ways and, importantly, prevents any secrecy about its collection or processing from data subjects. It makes it so that you have nothing to hide.
Protect Yourself from AI Risks Today
Despite the risks it can bring, there are good reasons organizations all around the world are constantly looking for new ways to leverage AI. It can be a wellspring of efficiency when used effectively, and firms that make good use of it are setting themselves up for success. The best way to reap the benefits of AI technology without falling victim to its downsides is to implement ISO 42001. And the best way to do that is to work with a quality advisor, like RSI Security.
RSI Security has helped countless organizations implement regulatory frameworks like ISO 42001 to safeguard their systems. We believe the right way is the only way to protect your data, and the same thing applies to AI system management. We’ll help you rethink and optimize your AI governance to ensure that you’re getting the most out of this groundbreaking technology.
To learn more about our ISO 42001 advisory services, contact RSI Security today!