Coming out of the dark: Shadow AI usage surges in enterprise IT

Shadow AI is emerging as a major enterprise risk, with new research revealing 90% of IT leaders express concerns about employees using unauthorized AI tools in the workplace. The adoption of generative AI in business environments is creating significant data security challenges, as organizations report financial losses and reputation damage from unregulated AI use. This represents a growing tension between embracing AI innovation and implementing proper governance frameworks to protect sensitive corporate information.

The big picture: Unauthorized AI tool usage is creating measurable business damage, according to a new survey from data management firm Komprise that questioned 200 IT directors and executives across U.S. organizations.

• Nearly 80% of IT organizations have already experienced negative consequences from employee use of generative AI, including false results and sensitive data leakage.
• A concerning 13% of respondents reported financial losses, customer fallout, and reputational damage specifically attributed to shadow AI practices.

What they’re saying: Business leaders acknowledge the urgent need for comprehensive AI governance strategies.

• “As enterprises are starting to get real about AI as part of their business strategy, the cracks are starting to show,” said Krishna Subramanian, COO and co-founder of Komprise.
• Subramanian emphasized that “unstructured data management will play a central role by giving users automated tools for data classification, sensitive data management, data workflows and AI data ingestion.”

Where we go from here: Organizations are actively investing in technological solutions to mitigate shadow AI risks while supporting legitimate AI initiatives.

• Three-quarters of surveyed companies plan to implement data management technologies to address these challenges.
• Nearly as many (74%) intend to deploy AI discovery and monitoring tools to gain visibility into AI usage across their organizations.
• IT departments are prioritizing infrastructure investments specifically designed for AI, including specialized storage solutions and enhanced data management capabilities.