AI Governance Won't Be Driven by Regulators Alone

Posted by jgilligan On June 2, 2026

By: Jennifer Gilligan, IntegraMSP President

For the last two years, the conversation around artificial intelligence has focused largely on capability. Businesses wanted to know what AI could do, how quickly it could be deployed, and whether it could help improve productivity. Increasingly, however, a different conversation is emerging.

Business leaders are beginning to ask questions about governance, accountability, risk management, and compliance. They want to understand what happens when AI gains access to business systems, sensitive information, customer data, and operational workflows. In many ways, this shift signals that AI is moving from experimentation into operational reality. What makes this particularly interesting is that the pressure for governance is not coming solely from regulators. Insurance carriers are asking questions. Vendors are updating contractual language. Clients are evaluating third-party risk. Industry frameworks are evolving. The market itself is beginning to establish expectations around responsible AI adoption. This is a familiar pattern.

Cybersecurity followed a similar path. Long before formal regulations dictated security standards for most organizations, cyber insurance providers, contractual obligations, and customer expectations encouraged businesses to adopt controls such as multi-factor authentication, endpoint protection, security awareness training, and incident response planning. AI appears to be following a comparable trajectory.

Organizations are rapidly introducing AI into email systems, document repositories, customer communications, business applications, and operational processes. At the same time, many businesses still lack formal policies governing how those tools are approved, what information may be shared, how vendors are evaluated, or what safeguards should be in place before deployment. The result is a growing governance gap.

One of the most common examples is the rise of what many now refer to as "shadow AI"—employees independently adopting AI tools to solve business problems without organizational oversight. Most are not acting maliciously. They are attempting to work more efficiently. Yet without clear guidance, organizations often have little visibility into what tools are being used, what information is being shared, or where that information ultimately resides. For business leaders, this creates an important challenge. The question is no longer whether employees are using AI. In many organizations, that question has already been answered. The more relevant question is whether the organization has established a framework for managing its use.

This is where trusted advisors become increasingly important.

As businesses navigate AI adoption, they will need partners who can help evaluate not only the technology itself, but also the broader implications surrounding governance, compliance, vendor risk, operational processes, and accountability. The organizations that navigate AI most successfully will likely be those that treat governance as a business function rather than a technology function. Ultimately, I believe the future conversation around AI will be less about what the technology can do and more about how responsibly organizations choose to use it.

The businesses that recognize that distinction early will be in a much stronger position as expectations continue to evolve.