AI has introduced a new set of security risks reflecting its integration into daily workflows. Adoption has been rapid, decentralized, and often invisible to IT security. Employees are experimenting with AI applications without oversight, SaaS vendors are embedding large language models (LLMs) into their platforms, and sensitive corporate data is being shared with systems with no transparency. For CISOs and security leaders, the challenge is clear: how do you enable the promise of AI while ensuring security?
Unsanctioned AI tools
Employees are adopting AI-powered tools on their own, often as free chatbots, content generators, or transcription services. These applications frequently request access to corporate data.
Without centralized oversight, these tools create shadow AI, mirroring the same challenges as with shadow IT. This introduces uncontrolled data flows, unmonitored access permissions, and unclear vendor accountability.
Embedded AI
Many enterprise SaaS vendors have quietly integrated AI features into their platforms. These additions often expand the permissions that applications request, allow deeper integrations through APIs, or store data for model training. Security teams may not even realize when a new AI feature is added. The result is an expansion of the attack surface.
Supply Chain Vulnerabilities
The AI ecosystem operates through a complex network of models, APIs, and third-party data sources. Each connection introduces a dependency that can be exploited. A compromised AI model or vendor could serve as a bridge into critical systems.
Traditional supply chain risk management is not equipped to assess how AI models are trained, what datasets they use, or how they process enterprise data.
Data Governance Challenges
AI systems thrive on data. The more they ingest, the more powerful they become. However, without strong data governance, that same data can create compliance violations, privacy breaches, and regulatory risk.
The line between internal and external data has blurred. Sensitive corporate knowledge, intellectual property, and customer information are now at risk of being stored or processed outside the organization’s control.
What AI Governance Really Means
AI governance is the establishment of order, accountability, and security within an AI-rich ecosystem.
For CISOs, governance must include the following pillars:
1. Visibility
You cannot govern what you cannot see. The first step in AI security is discovering every AI-powered tool and integration within your organization. This includes sanctioned tools, embedded AI within SaaS, and shadow AI adopted by employees.
Continuous discovery provides a real-time inventory of where AI is active, what data it accesses, and which users interact with it.
2. Risk Assessment
Not all AI tools present equal risk. Governance requires contextual understanding—evaluating each application based on its data handling, permissions, vendor practices, and compliance posture.
3. Policy and Control
Once visibility is established, organizations need enforceable policies that define acceptable AI use. Policies must be supported by automated enforcement. Manual oversight cannot keep pace with the speed of AI adoption.
4. Monitoring and Auditability
Governance is not a one-time event. AI tools evolve continuously, introducing new features and data interactions. Ongoing monitoring ensures that changes in permissions, APIs, or embedded models are immediately detected.
5. Education and Culture
AI security is not just a technology challenge, it is a human one. Employees often adopt AI tools with good intentions, seeking productivity or creativity gains. Clear communication, training, and engagement are essential to build awareness and promote responsible AI use across the organization.
The Business Case for AI Governance
AI governance is not only a defensive measure; it is a strategic enabler. By bringing order to AI chaos, enterprises can innovate faster, operate more confidently, and earn stakeholder trust.
Protecting Data Integrity
Strong governance ensures that sensitive information is never exposed to unauthorized systems. This protects intellectual property, customer data, and assets that are crucial to an organization’s competitive edge.
Reducing Supply Chain Risk
By treating AI tools as part of the digital supply chain, organizations can proactively identify weak links, evaluate vendor security, and ensure compliance with regulations. An AI-centric security platform will also alert IT security of relevant breaches to connected apps in their stack.
Enhancing Compliance Readiness
Auditors and regulators are increasingly focused on AI. Governance frameworks simplify the audit process by providing clear visibility into AI usage, risk assessments, and access controls. This reduces the cost and complexity of demonstrating compliance.
Building Trust in AI Adoption
Transparency builds confidence. Stakeholders, customers, and employees are more likely to embrace AI when they know its use is governed by strong security and ethical standards.
How to Regain Control
Wing Security was built to help organizations maintain visibility, control, and safety into all AI and SaaS applications.
As enterprises adopt AI at scale, Wing extends its capabilities to encompass AI. Wing continuously discovers every AI-powered application, identifies embedded AI features within existing tools, and monitors how they interact with corporate data.
Through its advanced analytics and continuous monitoring, Wing enables security leaders to:
- Detect shadow AI across the organization
- Assess the risk level of each AI tool based on data access and vendor policies
- Receive real-time alerts when new AI capabilities are introduced
- Enforce governance policies to restrict unsafe tools or respond to compromised apps
AI has become a cornerstone of digital transformation, but its rapid, decentralized adoption has created new risks that traditional security controls cannot manage. CISOs and security leaders must establish governance frameworks that deliver continuous visibility, adaptive control, and real accountability.
Wing Security helps organizations achieve exactly that. By uncovering shadow AI, mapping embedded AI within SaaS, and enforcing real-time governance, Wing brings order to AI chaos, empowering enterprises to innovate securely, confidently, and responsibly.
Ready to see what’s hiding in your stack? Wing’s got you covered.