Shadow AI poses risks for organizations' data security

Many organizations are facing a problem called "shadow AI." This refers to the use of unauthorized AI tools by employees. Similar to "shadow IT," where people use unapproved devices or applications, shadow AI can lead to risks for companies. The dangers of shadow AI include leaking sensitive information. For example, if employees upload confidential documents to AI services, the data can become accessible to outsiders. Other risks involve getting incorrect information from unapproved AI, which can result in poor decision-making. To combat shadow AI, companies need better processes and awareness. AI technologies can sometimes provide misleading or false information, a phenomenon known as "hallucination." This can cause serious issues, especially when misleading data enters a company's systems unnoticed. Organizations often lack strong governance for AI usage. Many do not have clear policies about what is acceptable, which contributes to employees using unauthorized tools. While there are governance frameworks available, they often lag behind the rapid advancement of AI capabilities. To tackle shadow AI, businesses can adopt a three-part approach: people, processes, and technology. Implementing technical solutions, like RAG (Retrieval Augmented Generation), can help keep proprietary data secure. Additionally, existing cybersecurity measures can be expanded to monitor unauthorized AI usage. Raising cultural awareness about AI risks is essential. Just as staff receive cyber security training, they should understand the risks of using AI. Employees must learn to treat AI-generated responses as potentially flawed and verify data before acting on it. Developing a strong awareness of data quality is crucial for reducing the risks associated with shadow AI.