As the IT industry continues to experience a surge of excitement around artificial intelligence (AI), concerns are rising regarding the potential risks associated with shadow AI. Shadow AI refers to the unsanctioned use of AI technologies by corporate employees without the oversight of the central IT and risk management functions of an organization. The rapid proliferation of AI tools, along with the emergence of large language model (LLM) algorithms, has led to the widespread adoption of generative AI (GenAI) apps in a variety of business contexts. However, the unsanctioned use of AI poses significant cybersecurity, operational, legal, and resource risks that need to be carefully managed, as highlighted in the following points.
Functional risks arise from the ability of AI tools to function effectively, such as model drift or outdated training data, leading to potentially misleading and useless results. Operational risks endanger a company’s ability to conduct business, as shadow AI could provide bad advice, expose sensitive information, or suffer cyberattacks, potentially leading to serious data privacy and compliance violations. Legal risks are a significant concern, as shadow AI could expose organizations to lawsuits, fines, and penalties due to incorrect advice, use of copyrighted data, or data privacy violations. Finally, resource risks include wasteful and duplicative spending among shadow projects, missed opportunities to invest resources elsewhere, and transition costs associated with the adoption of sanctioned AI tools.
To effectively manage the risks associated with shadow AI, organizations need to take a strategic approach that involves leadership, the CIO, CISO, CEO, CFO, and the head of risk management. Leadership must focus on visibility, risk management, and strategic decision-making, including auditing AI spending and bringing shadow AI projects under the umbrella of institutional risk controls. Additionally, organizations should classify data, create AI acceptable use policies, and educate and train employees on safe and secure GenAI usage to mitigate risks effectively.
Looking to the future, security and risk leaders should anticipate a continued proliferation of shadow AI projects as AI tools become more diverse and cost-accessible. As such, organizations need to remain vigilant in managing shadow AI risks while adapting to the evolving landscape of AI technologies. By taking proactive measures and implementing robust risk management strategies, companies can navigate the complexities of shadow AI and ensure the responsible, safe, effective, and efficient use of AI technologies within their organizations.