Takeaways

• BigID’s Shadow AI Discovery helps organizations find and manage unauthorized AI models (“shadow AI”)—spanning cloud platforms, SaaS tools, developer workflows, and collaboration systems.
• It flags sensitive or regulated data used in AI training and maps who’s using what, where, and how. Teams can then enforce policies, restrict access, or trigger remediation steps directly from the platform.
• The capability emphasizes visibility paired with actionable response to curb data leakage, IP misuse, and compliance gaps.
• Nimrod Vax, BigID’s CPO and Co-Founder: “Security teams can’t just find risky AI – they need to stop it.”
• Shadow AI Discovery extends BigID’s broader mission of combining data classification, compliance, and AI governance in a unified, intelligent platform.

Shadow AI Discovery: Why It’s a Game-Changer

Recognizing this, BigID introduces Shadow AI Discovery, a capability designed to help organizations move beyond simple AI detection and into actionable oversight. It allows teams to detect unauthorized AI models, whether they are running in sanctioned environments like cloud platforms and enterprise SaaS or in unsanctioned spaces such as personal developer tools or informal collaboration channels. This comprehensive detection aims to shine a light on the full AI footprint within an organization.

Recently we covered the company launching the First Managed DSPM Platform Purpose-Built for MSPs and MSSPs. At the time, Dimitri Sirota, CEO and Co-Founder of BigID said, “As enterprises double down on securing sensitive data, preparing for regulation, and managing AI risk, MSPs need a smarter way to deliver outcomes.With this program, partners can connect the dots in data and AI—helping their customers reduce risk, enforce policy, and improve security posture.”

Once models are detected, Shadow AI Discovery can classify and flag sensitive data used in training or inference. This includes personal data, regulated information, and intellectual property. It also maps AI usage by identifying which departments, teams, or individuals are interacting with each model, how they are doing so, and in what environments. These insights equip governance and security teams with the ability to apply policies, restrict risky access, or initiate remediation workflows from within the same platform.

By integrating these functions, BigID shifts the approach to AI governance from passive visibility to proactive control. The result is a closed loop where organizations not only see risks but can also address them immediately.

Context: The Expanding Visibility Gap in AI

The acceleration of AI adoption has introduced a new governance challenge. Models are now embedded into workflows across business units, often without formal approval or security review. This phenomenon, known as shadow AI, is the result of the democratization of AI tools and the ease with which they can be deployed.

Industry studies, including research from MIT CSAIL, have noted that privacy and security remain top concerns for organizations exploring AI. These risks are magnified when models operate outside official channels, as they may access data without appropriate safeguards, bypass audit logging, or inadvertently leak sensitive information. Regulatory scrutiny is also increasing, with new AI compliance standards emerging in multiple jurisdictions.

By delivering visibility into all AI activity, BigID’s Shadow AI Discovery aims to address these gaps. It offers a way for organizations to identify and manage AI usage that might otherwise remain hidden, helping them to avoid costly compliance breaches or data incidents.

The Bigger Picture: BigID’s Unified Platform

Shadow AI Discovery builds on BigID’s broader platform, which combines data security, privacy governance, and AI governance in one environment. Key elements include machine learning-based classification of sensitive and regulated data, data security posture management, data loss prevention, and risk-aware controls.

The platform’s compliance automation and privacy governance capabilities address obligations such as data subject access requests, regulatory reporting, and the enforcement of retention and deletion policies. On the AI side, beyond detecting shadow AI, BigID provides risk assessment tools, AI asset discovery, and the ability to control or restrict model use based on policy.

This integration means organizations can manage AI governance alongside broader data governance efforts, reducing operational complexity and ensuring consistent enforcement across both structured and unstructured data environments.

Industry Implications

Shadow AI Discovery arrives at a time when enterprises are grappling with how to maintain oversight without stifling innovation. Many technology leaders acknowledge that AI experimentation can yield competitive advantage, but unmanaged AI also brings risk. Tools that can both discover and control AI use offer a middle path—allowing innovation to continue while ensuring security and compliance teams have the visibility and authority they need.

By offering not only detection but also policy enforcement and remediation, BigID addresses a critical gap in many AI governance strategies. The ability to respond in real time, rather than after an incident, is increasingly seen as essential for risk management in the AI era.

What It Doesn’t Do

While Shadow AI Discovery strengthens oversight for unauthorized models, it does not offer AI model creation, training, or deployment tools. Its focus is squarely on detection, mapping, classification, and governance. Broader privacy, compliance, and data security functions remain part of BigID’s overall platform but are not the specific scope of this new capability.

For organizations seeking enterprise-wide risk dashboards or in-depth AI performance analytics, additional tools may be required. However, as a targeted solution to uncover and act on shadow AI, it represents a significant step forward in AI governance technology.

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Rich Tehrani serves as CEO of TMC and chairman of ITEXPO #TECHSUPERSHOW Feb 10-12, 2026 and is CEO of RT Advisors and is a Registered Representative (investment banker) with and offering securities through Four Points Capital Partners LLC (Four Points) (Member FINRA/SIPC). He handles capital/debt raises as well as M&A. RT Advisors is not owned by Four Points.

The above is not an endorsement or recommendation to buy/sell any security or sector mentioned. No companies mentioned above are current or past clients of RT Advisors.

The views and opinions expressed above are those of the participants. While believed to be reliable, the information has not been independently verified for accuracy. Any broad, general statements made herein are provided for context only and should not be construed as exhaustive or universally applicable.

Portions of this article may have been developed with the assistance of artificial intelligence, which may have contributed to ideation, content generation, factual review, or editing.