Enterprises experience a surge in AI adoption, driven by technological advancements and increasing cybersecurity threats, according to the latest Zscaler report. In a recent report, it was revealed that enterprises have seen a substantial increase in the use of artificial intelligence (AI) and machine learning (ML) technologies. This adoption has been fueled by the need to enhance productivity and efficiency while also addressing rising cybersecurity threats. The Zscaler ThreatLabz 2025 AI Security Report analyzed over 536 billion AI transactions processed through the Zscaler Zero Trust Exchange, highlighting significant trends and challenges.
The report indicates a 30-fold increase in AI and ML usage over the past year, reflecting large-scale integration across diverse industries. Data transmission to AI systems has soared, with enterprises transferring more than 4,500 terabytes of data to leverage AI capabilities. This demonstrates AI’s role in elevating business operations across finance, manufacturing, technology, services, and healthcare sectors.
Despite the advancements, the report underscores notable security concerns. Approximately 60% of AI transactions have been blocked by enterprises due to risks such as data leakage, unauthorized access, and compliance breaches. ChatGPT, the most utilized AI tool with a 47.1% share in global usage, has frequently been blocked owing to sensitivities around data exposure.
Other prominently blocked AI applications include Grammarly, Microsoft Copilot, QuillBot, and Wordtune, all vital tools but fraught with potential security risks. Meanwhile, the surge in AI adoption has correlated with an increase in AI-assisted cybersecurity threats. Advanced technologies like agentic AI and China’s open-source DeepSeek further empower threat actors, creating new vulnerabilities.
From a geographical perspective, the U.S. leads in AI and ML adoption, closely followed by India. The finance and insurance sector represents the largest contributor to enterprise AI traffic, followed by manufacturing, services, technology, and healthcare. These industries harness AI for various functions, notably fraud detection, risk modeling, and customer service enhancement.
Essentially, the transformation driven by AI encapsulates a dual-edged sword. While AI’s potential to innovate is vast, it is matched by evolving cybersecurity risks. Organizations are thus prompted to integrate strong risk management practices and deploy AI-infused security solutions to safeguard against emerging threats.
In conclusion, the AI surge within enterprises has promised remarkable growth, but it has also necessitated established and dynamic security frameworks to mitigate risks. Future consideration must be given to balancing AI’s benefits with appropriate security measures. Enterprises must navigate this complex landscape with vigilance, ensuring cybersecurity strategies evolve in tandem with AI technologies.
