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Generative AI (GenAI) has become a transformative technology for enterprise businesses in more ways than one. Its widespread adoption will undeniably impact organisations across many industries, leading to greater productivity and efficiencies. Still, GenAI is a double-edged sword — while it offers significant benefits and convenience, businesses must tread lightly because it doesn’t come without risks, particularly concerning data protection.
One of the biggest concerns? Employees using GenAI to complete day-to-day tasks and unintentionally exposing sensitive data to large language models (LLMs) – which are algorithms that use deep learning techniques and large data sets to understand, summarise, generate, and predict new content. Now, along with many other security concerns enterprises should be mindful of, they face the task of protecting against potential threats posed by this powerful, prolific tool.
Why GenAI use by an enterprise’s staff is risky
Gen AI was one of the hottest topics at Mobile World Congress this year, and we are only at the beginning of where this technology will take us. In a report released by Deloitte in January of this year, 79% of Australian business and technology leaders expect Gen AI to drive substantial transformation within their organisations and industry over the next three years. While 49% say a lack of technical talent and skills is the biggest barrier to adoption, 40% see intellectual property issues as the biggest concern when it comes to Gen AI adoption and only 21% of organisations say they are “highly” or “very highly” prepared to address governance and risk issues.
Let’s take a step back and rehash how these tools work.
What is GenAI?
There are numerous GenAI apps available today, including ChatGPT, Bard, and Hugging Face, and each is similar in that they use a LLM — a type of artificial intelligence (AI) model trained on large amounts of data to understand and generate human-like text. When a question or prompt is submitted into a GenAI app, information is pulled from the LLM and delivered to the user.
GenAI is embraced by enterprises for many things, such as content creation, code writing, customer support, chatbots, and more. And while Australian businesses are moving towards prioritising investment in GenAI, many are doing so without truly understanding the impact it will have on their systems and what potential risks could come about as a result.
What are the Generative AI security risks?
- Unauthorised disclosure of sensitive information
GenAI models often require access to vast amounts of data to function effectively. When enterprise staff use GenAI to do their jobs, there’s always a risk of sensitive business data being exposed or mishandled, leading to breaches of confidentiality. And this risk is only being exacerbated as more employees utilise GenAI to complete daily tasks.
Say, for example, an employee copies and pastes proprietary corporate information into these systems to generate a presentation. Now, because LLMs are continuing to learn from the internet and information they receive, anything plugged into a GenAI tool could show up in response to another person’s request, exposing that information to unauthorised persons.
- Copyright infringement
Copyright infringement is a huge concern for businesses. In fact, in late 2023, the federal government set up a ‘reference group’ that will tackle copyright challenges stemming from AI use. Because it’s trained on material found on the internet, much of that information could be copyrighted, leading to a host of legal problems for businesses.
For example, a national newspaper is in the middle of a copyright infringement lawsuit, claiming a popular GenAI system used millions of existing articles to train its language models. If this is the case, any information from those articles could now be showing up in responses to users everywhere and potentially reused without proper citing or reference.
- Ethical implications and bias
Bias is seemingly everywhere, and GenAI apps are no exception. These algorithms might unintentionally reinforce biases inherent in the data they’re trained on, potentially resulting in unfair or discriminatory outcomes. Using these biased AI systems can result in ethical dilemmas and damage to a business’ reputation.
How does a zero trust GenAI data loss prevention solution address these risks?
Despite the looming threat of robots coming for organisations’ intellectual property, effective strategies can be employed to minimise these risks and ensure it stays in the hands of trusted individuals.
Establishing a robust security strategy is crucial to defend against known and unknown threats in the future. With security solutions such as generative AI data loss prevention, companies can safely allow GenAI use company-wide without risking their data or integrity, by implementing Generative AI isolation.
This solution provides true zero trust protection by allowing employees access to GenAI apps through isolated cloud containers — all virtually unnoticed by the user. This offers user entry protection, effectively preventing employees from inputting personally identifiable information (PII) or other sensitive data into the GenAI application or from copying and pasting information to/from the GenAI system. By doing so, it protects companies from potential liabilities while ensuring the security of their intellectual property.
To take it a step further, GenAI isolation can also protect user devices and enterprise networks from any malware generated by a GenAI tool or passed on from a malicious source.
Generative AI Data Loss Prevention, based on Zero Trust principles, allows employees to access GenAI apps through isolated cloud containers, virtually without the user noticing. Businesses can set policies that prevent users from entering personally identifiable information (PII) or other sensitive data into the app and disable copy-and-paste functionality to protect intellectual property and data loss. In addition, with the GenAI isolation feature, user devices and corporate networks are protected from malware generated by a GenAI tool or transmitted by a malicious source.
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