We are in the middle of an AI gold rush. Generative AI (Gen AI) has exploded from research labs into everyday business workflows at breakneck speed. Marketing, software development, customer support, HR, companies across industries deploy Gen AI tools to boost efficiency, automate tasks, and gain an edge.
But security trails behind.
In the rush to innovate, organizations chase speed and visibility, leaving risk management behind. The benefits of Gen AI are real, but so are the risks, and many only now come into focus. Security has become an afterthought again. This oversight could prove costly.
What Makes Gen AI Risky?
Generative AI introduces new risks beyond those of traditional software. Data privacy, decentralized IT, intellectual property, BYOD security, and decision integrity top the list.
The biggest threat is AI data exposure. Gen AI systems ingest and generate data based on prompts, often containing sensitive or proprietary information. When employees feed confidential data into public models like ChatGPT or Copilot without clear rules, that data leaves the organization’s control, intentionally or not.
Using generalized AI models in highly regulated industries like law, healthcare, or finance without domain-specific tuning or expert oversight is also dangerous. These models lack context, nuance, and accountability. They hallucinate facts, misread ambiguous input, and deliver false information, there is no AI compliance.
The risk isn’t just what goes in. It’s also what comes out. When businesses rely on Gen AI to generate customer messages, marketing content, or code, they risk spreading inaccuracies, bias, or copyright violations. This exposure can damage a company’s brand and trigger legal trouble.
Decentralized IT, BYOD, and Shadow AI: The Perfect Storm
Today’s hybrid work environments are complex and distributed. Add Bring Your Own Device (BYOD) policies and easy access to personal AI subscriptions, and you get a perfect storm for Shadow AI, where employees use Gen AI tools outside IT’s watch.
This decentralization makes it nearly impossible to track where sensitive data is entered, stored, or generated. Employees copy and paste corporate data into AI tools on personal phones or laptops, with no logging, no oversight, and no guarantee data is deleted.
Many employees don’t see the risk. To them, AI is just another productivity tool. But for security teams, it’s a growing blind spot.
As security expert Dhamankar warns, Gen AI's convenience masks danger. A simple drag-and-drop might send confidential data into an external model’s training set- or worse, into a competitor’s hands.
Compliance Pitfalls and Regulatory Blind Spots
Strict data protection laws govern many industries: HIPAA, GDPR, PCI-DSS, among others. When employees use Gen AI tools outside approved infrastructure, they risk violating these rules.
For example, entering patient data into a public AI model breaches HIPAA. Sharing EU customer info with a tool hosted in a non-compliant country breaks GDPR. Copying payment details or source code into AI systems risks exposing intellectual property or sensitive financial data.
These risks are real. Regulators are paying attention. The EU AI Act, California’s CPRA amendments, and proposed U.S. federal laws signal rising compliance scrutiny around AI.
Organizations without clear visibility and control over AI use risk fines, reputational damage, and lost customer trust.
Generative AI Security to Rein in Risks
Managing Gen AI risks demands a proactive, layered approach. Security teams should adopt these five strategies:
Establish Gen AI Usage Policies: Define which AI tools are approved, what data can be shared, and under what conditions. Publish and enforce clear guidelines to curb shadow IT and uninformed use.
Implement Data Loss Prevention (DLP) Controls: Deploy DLP tools to detect and block sensitive data leaving secure environments (browsers, endpoints, or cloud apps).
Monitor AI Activity: Use solutions like Tripwire to gain visibility into AI tool usage. Continuous monitoring and file integrity tracking flag anomalies and enforce compliance.
Train Employees on AI Risks: Awareness is critical. Mandatory training must cover security risks and Gen AI’s limitations. Employees need to know when to distrust AI output and escalate to human experts.
Secure the Development Pipeline: When building AI models, embed security throughout, from data sourcing and model training to deployment and monitoring. Validate inputs, sanitize outputs, and guard against adversarial attacks or model extraction.
Gen AI Security Must Be Built in from Day One
Gen AI innovation won’t slow. Security can’t be an afterthought or bolt-on. It must be part of the foundation.
AI projects should start with a threat model. What data is accessed? What compliance rules apply? Who accesses the models? How are prompts and responses logged, audited, and reviewed?
Security teams must join AI development and deployment from the start, not just after breaches or violations.
CISOs must sit alongside innovation leads and data scientists. Tools from Fortra play a vital role. With real-time monitoring, policy enforcement, and integrity management, organizations gain the visibility needed to move fast without breaking things.
Fortra: Proactive Risk Management for the Gen AI Era
As organizations embrace Gen AI and other transformative tech, maintaining control across decentralized, fast-changing environments is critical. Fortra excels here.
For decades, Fortra Integrity and Compliance Monitoring has helped enterprises secure systems with integrity and compliance monitoring, configuration management, and real-time threat detection.
In Gen AI adoption, Fortra provides foundational controls to monitor system use, detect unauthorized changes, and enforce policy compliance across on-premises, cloud, and hybrid setups. Its continuous integrity assessments, security automation, and alerts make it essential when AI tools open new paths for data leaks and misuse.
Want to learn about the vast range of technologies we offer to help protect organizations like yours? Contact us today.
