Why SOC 2 Compliance Is Critical in the Age of AI
(This article first appeared in financialexecutivesjournal.com)
The rise of generative AI has ushered in an era of extraordinary opportunity, and equally significant uncertainty. Financial executives are now tasked with walking a tightrope: enabling innovation while protecting against emerging risks. Amid the buzz around productivity gains, automation, and competitive edge, it’s easy to overlook the core governance structures that quietly enable responsible AI adoption.
But we can’t afford to forget them.
As AI becomes more deeply integrated into customer-facing platforms and decision-making tools, frameworks like SOC 2 are more important than ever. Not just for IT teams or compliance departments—but for executives such as CFOs, COOs, and other risk leaders who are ultimately accountable for organizational integrity, financial stability, and reputational trust.
Artificial Intelligence is built on data, and data is one of your company’s most valuable assets. With that comes responsibility: how it’s collected, secured, used, and shared. Whether your organization is developing AI in-house or adopting third-party AI tools, managing the risks—to customer data, privacy, system reliability, and operational resilience—is a shared responsibility. But finance leaders play a critical role in overseeing these efforts and ensuring the right controls are in place to protect the organization’s long-term value and the trust of its stakeholders.
This is where SOC 2 comes in. Developed by the American Institute of CPAs (AICPA), SOC 2 was designed to ensure that systems handling sensitive and confidential customer data operate securely, reliably, and ethically. SOC2 evaluates up to five key trust service principles: security, availability, processing integrity, confidentiality, and privacy.
In a financial context, these principles map directly to risk exposure:
If AI is becoming central to how your business operates, SOC 2 is central to how you protect it.
Organizational responsibilities for privacy and security under the GLBA (Gramm-Leach-Bliley Act) have been implemented by financial services organizations for some time, but it has become apparent that even for organizations that are subject to the GLBA, SOC 2 is that extra internal organizational control framework an organization needs to align with GLBA and to ensure that customer data protection and responsible AI adoption is a foremost priority in its security information program.
Too often, SOC 2 is misunderstood as a technical certification. It is viewed as a box for engineers or DevOps to check off for security purposes or before a major product launch. But at its core, SOC 2 is a company-wide compliance framework that spans multiple leadership domains—covering areas such as procurement and expenses, vendor management (including those leveraging AI), organizational governance and structure, hiring practices, policies and procedures, and internal and external communications. It’s a comprehensive initiative that must be supported and championed at the leadership level. It signals organizational maturity, strategic foresight, and a willingness to be held accountable by independent auditors.
In addition, from an AI adoption perspective, SOC 2 is key because SOC 2 controls require organizations to adopt AI use policies and risk frameworks, which include such tools as AI Risk Assessments to evaluate security, privacy, intellectual property and customer data risks before AI software can be approved for use.
Finance leaders should view SOC 2 the way they view GAAP or other internal controls. They should view it not just as a requirement, but as a reflection of how seriously a business takes its responsibilities to customers, investors, and the broader market.
When done right, SOC 2 can serve as a financial safeguard in three key ways:
In this moment of exponential innovation, financial executives have a crucial role to play. Financial executives are the stewards of not just balance sheets, but enterprise risk, reputational capital, and future-readiness. That means asking the right questions about how AI is implemented, and ensuring that the frameworks supporting it are robust, scalable, and verifiable.
SOC 2 isn’t a silver bullet, and it is quite the feat to achieve accreditation. But it’s one of the most trusted, widely adopted tools we have to help organizations use AI with integrity. In the months and years ahead, as generative tools become more embedded in critical workflows and customer experiences, the cost of failing to implement guardrails will only grow. In the age of AI, innovation is no longer the only metric of progress. Trust, accountability, the protection of customer data and operational transparency are equally critical. SOC 2 remains one of the clearest ways for finance leaders to signal that all four are being taken seriously.
