The growing use of unauthorized generative AI tools, often referred to as “shadow AI,” is creating a widening gap between corporate policy and employee behavior, according to Channel Insider. The trend is pushing security leaders to look beyond written governance and prioritize technical controls that can identify, monitor and restrict how employees access AI services.
The UK's National Cyber Security Centre (NCSC) has warned that this unmanaged AI usage can lead to sensitive data exposure and security blind spots. Matthias Haas, CTO at IGEL, emphasized that policies are only effective when backed by visibility and technical controls at the point of access, stating that organizations must know which AI services employees are utilizing.
This gap presents an opportunity for MSPs and MSSPs to offer ongoing governance services across endpoints, browsers, and network infrastructure, rather than just one-time policy work. Controls at both the network and endpoint layers are crucial for monitoring AI workloads and the data being transmitted. Secure enterprise browsers are emerging as a key governance layer, enabling tracking, monitoring, and blocking of noncompliant AI prompts. Ultimately, effective AI governance requires a combination of user awareness, endpoint controls, and network-level enforcement to manage risks and ensure compliance, especially in highly regulated industries.
Source: Channel Insider
