The integration of AI with IT compliance continues to present significant challenges in 2025, as organizations navigate an increasingly complex regulatory landscape while trying to leverage AI’s benefits. On top of this, software developers are racing to prove that AI is an easy replacement for compliance expertise — at their own peril. While “AI” seems like the marketing buzzword de jour that fits compliance perfectly, practical application has yet to yield anything trustworthy or thorough enough to entrust with an organization’s security and reputation.
Several key issues surrounding the intersection of AI and compliance remain at the forefront:
Regulatory Fragmentation
The regulatory environment for AI remains highly fragmented in 2025, creating compliance headaches for organizations. The EU AI Act is setting standards in Europe, while the U.S. has developed a patchwork of state-level legislation with at least 15 states having enacted AI-related laws. This fragmentation requires organizations to develop sophisticated compliance strategies that can adapt to varying requirements across different jurisdictions.
Data Privacy and Security Challenges
AI systems process vast amounts of sensitive data, creating significant privacy and security concerns:
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Organizations must implement strict data protection measures including encryption and secure storage to prevent breaches.
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AI-specific data security needs have outpaced traditional data protection practices.
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The intersection of AI with regulations like GDPR creates unique compliance pressure points, particularly around data minimization and purpose limitation.
Third-Party Risk Management
As more organizations purchase rather than build AI systems, third-party risk has become a major concern:
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Companies face challenges managing relationships with external AI providers. This is no small consideration when dealing with security.
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The widespread integration of AI tools (like Grammarly, Canva, DocuSign) creates complex third-party risk landscapes.
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70% of organizations lack ongoing monitoring and controls for AI risk management despite 47% having risk frameworks in place.
Emerging AI-Specific Threats
Of course, AI is being used just as readily by the aggressors as it is by the defenders. New security threats specifically targeting AI have emerged:
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Cybercriminals are leveraging AI to create more sophisticated attacks including automated phishing, deepfake impersonation, and AI-powered malware.
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AI models face unique vulnerabilities like prompt injections and model hallucinations.
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Organizations must work closely with AI providers to fortify the supply chain. More users should be concerned about how to maintain compliance while using AI, rather than how to use AI to simplify or sidestep compliance requirements.
Resource and Expertise Limitations
Many organizations already struggle with resource constraints in their compliance programs — if they have such a program at all. On the surface, it may seem like integrating AI can alleviate these resources costs, it can actually add new layers to the risk profile and complicate matters.
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Compliance programs face budgetary and staffing challenges that are expected to escalate.
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The growing complexity of AI governance requires specialized expertise that many organizations lack.
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Effective AI compliance requires coordination across multiple teams including legal, data governance, and technical development.
- AI is still unable to produce security programs and policies that don’t need to be checked and modified by human experts, so the idea of replacing compliance expertise with AI is not yet feasible.
- Achieving compliance — at least in a way that actually increases an organization’s security posture — is a collaborative endeavor that requires at least some knowledge of the organization in question. Current AI tools simply can’t understand a business’ operations and needs at the level required to fortify it.
As AI becomes more deeply embedded in business operations throughout 2025, organizations must develop more sophisticated governance frameworks, not simpler ones that merely lean on AI to generate policies and strategies. To do the latter would be a serious step in the wrong direction, placing too much faith in “checkbox compliance” and robbing organizations of the opportunity to truly and effectively address their cybersecurity concerns.