Taking Shadow AI Out of the Darkness: The Hidden Risks of GenAI-based App Adoption

Taking Shadow AI Out of the Darkness: The Hidden Risks of GenAI-based App Adoption 

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The GenAI revolution is quickly changing the very nature of how business is conducted around the world. According to a PwC survey, 54% of companies surveyed have implemented GenAI in some areas of their business. With numerous tools touting increased productivity, shorter time-to-value and heightened efficiency, both managers and employees drive the adoption of these GenAI-based applications to enhance their workflows. Looking ahead, knowing how to rapidly adopt these tools and leverage them for business productivity will be crucial, and companies will feel pressured to do so or be left behind. Employees seek out tools to help streamline their workflows and improve efficiency. ChatGPT and similar productivity tools are gaining popularity and their SaaS model is easily adopted by anyone, without requiring security approval.

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As with any new and rapidly adopted technology, GenAI presents challenges that must be addressed - among them, the unsanctioned, unmanaged and ungoverned use of GenAI models, or “Shadow AI”. The forward-thinking security leader knows better than to restrict GenAI use altogether to manage these risks as that would obstruct innovation and negatively impact the company’s competitive advantage. Understanding and mapping the risks of Shadow AI is crucial in order to mitigate them. 

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The Risks Lurk in the Shadows

The inherent complexity and unpredictability of GenAI tools, coupled with their need to train on your datasets to improve their performance, increase this risk. There are unintended consequences and risks associated with the widespread adoption of GenAI-based applications without thorough security scrutiny and oversight, turning them into Shadow AI. Common tools this occurs with include ChatGPT and other chatbots, Github copilot and other copilots, Midjourney, Grammarly and other 3rd party apps widely used across the enterprise.

LLM tools work best when they have the most detailed data to work with, which is usually taken from elsewhere and pasted into the model. Without security oversight, employees can easily provide these tools access to corporate data - or any other type of sensitive data - risking its exposure. Such acute data risks can lead to legal, HR, compliance or regulatory consequences, loss of customer trust and a significant blow to the company’s reputation. There are also risks associated with malicious outputs and compliance violations.

Shine a Light on Shadow AI

The knee-jerk reaction to security risks may be to obstruct adoption and restrict use, but in the age of GenAI, these types of mitigation techniques are outdated and ineffective. Employees will workarounds to allow them to use GenAI tools without security approval, leading to a lack of trust and making security teams irrelevant. There are ways to shine a light on Shadow AI, mitigate its risks and allow the organizational use of this technology without compromising security. 

First - visibility. Most security teams have no idea what types of GenAI tools are being used in their organization, when, where and how - including what data is uploaded and what type of outputs are produced. Without visibility into GenAI use, decision-making around governing its use is impossible. Security teams must produce a comprehensive inventory of all GenAI applications used in their organization, assessing which of these applications are able to store and learn on company data. These insights into GenAI use are not only valuable for security but can augment business decisions and provide illuminating data for the company as a whole. 

Once Shadow AI is discovered, security teams should design and implement effective organization-wide security policies to address these tools and their use. These guardrails will ensure employee compliance across all types of GenAI use and tools - chatbots, enterprise assistants and applications that leverage GenAI technology. 

Using secure alternatives to these applications is another risk-reduction strategy. Secure internal enterprise GenAI apps can be built with enhanced security guardrails, ensure compliance with data and privacy regulations and prevent malicious outputs and other risks. 

Getting Out of the Shadows

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Adopting GenAI is a crucial business imperative, but must be coupled with security oversight and control. The result of such governance won’t be just more secure interactions with GenAI tools, but overall improvement in the use, productivity and outputs of these tools - with enhanced business and security insights. Shadow AI should be a thing of the past in modern organizations, with security leaders becoming GenAI champions, paving the way for secure and safe use of this groundbreaking technology - out of the shadows and into the light.

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Aim: Unleash the power of Generative-AI without compromising security

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