Enterprise AI usage surges but security worries remain
A new report from Zscaler reveals a 3,000 percent year-on-year growth in enterprise use of AI/ML tools, highlighting the rapid adoption of AI technologies across industries to unlock new levels of productivity, efficiency, and innovation.
This surge in adoption also brings heightened security concerns though. According to the study enterprises blocked 59.9 percent of all AI/ML transactions, indicating awareness around the potential risks associated with AI/ML tools, including data leakage, unauthorized access, and compliance violations.
Threat actors are also increasingly leveraging AI to amplify the sophistication, speed, and impact of attacks -- forcing enterprises to rethink their security strategies.
"As AI transforms industries, it also creates new and unforeseen security challenges," says Deepen Desai, chief security officer at Zscaler. "Data is the gold for AI innovation, but it must be handled securely. The Zscaler Zero Trust Exchange platform, powered by AI with over 500 trillion daily signals, provides real-time insights into threats, data, and access patterns -- ensuring organizations can harness AI's transformative capabilities while mitigating its risks. Zero Trust Everywhere is the key to staying ahead in the rapidly evolving threat landscape as cybercriminals look to leverage AI in scaling their attacks."
Enterprises are sending significant volumes of data to AI tools, totaling 3,624 TB. ChatGPT emerges as the most widely used AI/ML application, driving 45.2 percent of identified global AI/ML transactions in the Zscaler Zero Trust Exchange. However, it's also the most-blocked tool due to enterprises' growing concerns over sensitive data exposure and unsanctioned use. Other frequently-blocked applications include Grammarly, Microsoft Copilot, QuillBot, and Wordtune, showing broad usage patterns for AI-enhanced content creation and productivity improvements.
The US and India account for the highest AI/ML transaction volumes, representing the global shift toward AI-driven innovation. However, these changes aren't occurring in a vacuum, and organizations in these and other geographies are grappling with increasing challenges like stringent compliance requirements, high implementation costs, and shortage of skilled talent.
The Finance and insurance sector accounts for 28.4 percent of all enterprise AI/ML activity, reflecting its widespread adoption, and indicative of the critical functions supported by the industry, such as fraud detection, risk modeling, and customer service automation. Manufacturing is second, accounting for 21.6 percent of transactions, likely driven by innovations in supply chain optimization and robotics automation. Additional sectors, including Services (18.5 percent), Technology (10.1 percent), and Healthcare (9.6 percent), are also increasing reliance on AI.
The full report is available from the Zscaler site.
Image credit: Tongsupatman/Dreamstime.com