Rethinking Risk Around AI and Cybersecurity
Key insights
Don’t assume cyber risk starts inside your organization. A customer mistake, vendor gap, or employee shortcut with AI can quickly become your problem.
AI is making threats faster and more convincing. Phishing, impersonation, and credential attacks are easier to scale — so verification and controls matter more than ever.
AI can strengthen your defenses — but only with the right guardrails. Use it to spot anomalies and support response, while keeping strong oversight, policies, and data controls in place.
Treat AI as a business-wide responsibility. Align governance, employee training, and vendor oversight so everyone plays a role in reducing risk.
Using AI? Don’t forget to weigh cybersecurity risks.
Artificial intelligence (AI) has advanced from single-purpose tools to systems that can analyze large volumes of data and automate decisions. As adoption grows, so does the need to understand the cybersecurity risks and establish clear guardrails.
AI risk isn’t all or nothing. Some tech professionals believe AI is an existential threat to humanity, while others think those fears are unfounded and view AI as a strong advantage. Whatever you personally believe, remember AI is still evolving and we must exercise caution and thought when using it.
AI can strengthen threat detection and fraud monitoring — but it also gives bad actors new ways to scale phishing, impersonation, and credential-based attacks. The result is a broader, faster, more dynamic threat environment affecting more than just your internal systems.
Learn what your organization should look out for — and how to increase protection — when it comes to AI.
The impact of AI on cybersecurity
AI and cybersecurity both involve autonomous programs or systems that can perform tasks without human input. While AI is a powerful tool, these agents still depend on how people configure access, permissions, and decision rules.
In practice, AI agents compress the time between request and action. That can improve efficiency, but it also increases risk when approvals, identity controls, or monitoring are unclear or bypassed.
Where AI risk is showing up
For many organizations, the biggest risk now starts outside their walls:
- Direct attacks such as phishing, credential theft, and business email compromise
- Customer or client compromise leading to fraud or reputational impact
- Third-party exposure where vendor controls lag behind expectations
- Employee use of unapproved tools (“shadow AI”) exposing sensitive data or bypassing process
Risk doesn’t stay contained. A customer mistake, vendor weakness, or internal shortcut can quickly become an organizational issue, resulting in fraud losses, disruption, damaged reputation, or compliance exposure.
Program maturity is critical. The prevalence of AI requires organizations to continually strengthen preventive controls, not simply react faster after an incident.
Balancing cybersecurity and human behavior
AI allows criminals to act faster and with more convincing tactics, while human behavior remains a leading source of exposure.
Deepfakes and impersonation, such as cloned executive voices used in payment scams, highlight how easily trust can be exploited. At the same time, everyday actions — clicking a link, approving a request, or sharing information in the wrong tool — continue to open the door to cyber risk.
How AI can strengthen cyber defense
AI is helping organizations detect and respond to cyber threats more effectively. It can:
- Identify unusual patterns in transactions and user behavior
- Support fraud monitoring and alert triage
- Surface anomalies that might be missed by manual review
These capabilities help teams focus attention where it matters most, especially as volumes of activity increase.
Foundational controls still matter. Practices like penetration testing, firewall reviews, and documented security policies remain essential when paired with AI-enabled monitoring and defined human accountability structures.
How IT might incorporate AI in cybersecurity
AI can analyze huge amounts of data much faster than humans, which is invaluable for monitoring and detecting malicious activity. AI systems can be misconfigured or manipulated to bypass intended guardrails, including through data poisoning, which is when false data is purposely added to corrupt machine learning algorithms.
IT professionals should educate themselves on the risks and benefits of AI and consider including it in their acceptable use policies.
AI can be used to help effectively monitor cybersecurity but it’s important to verify the system has controls to protect against potential compromises. Consider system development lifecycle, change management, segregation of duties, and logical security when implementing AI monitoring systems.
Why AI risk requires organization-wide alignment
Treat AI as an enterprise issue, not a niche technology topic. Cybersecurity extends beyond your own network, and resilience depends on a combination of governance, education, discipline, and smart use of technology:
- Incorporate AI-related discussions in your organization’s employee manuals
- Update regulations and governance policies to outline tool usage, data restrictions, and oversight responsibilities
- Clarify and reinforce employee training around shadow AI and data handling
- Ask your third-party vendors how they use AI, what data trains their models, and what safeguards are in place to protect your organization’s information
- Expand awareness and education for customers, partners, and employees, especially around phishing, impersonation, and verification of sensitive requests
How CLA can help reduce cybersecurity risks from AI
Artificial intelligence can bring many benefits to organizations, but cyber criminals have access to the same technology. CLA’s cybersecurity team can evaluate your IT operations and environment and give you a critical analysis of your controls to help maintain a secure and resilient technology infrastructure.
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Tim Dively
Digital Growth Director
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