Insights for CISOs: Challenges and Opportunities of AI-Powered SASE

Secure access service edge (SASE) developers are employing AI to make their cloud zero trust architecture platforms better. This isn't news: Most of the bigger SASE vendors have experimented with integrating AI components into their platforms for five years or more. What is new is that their customers are now reaping the tangible benefits of those efforts. AI has the potential to make SASE services better: to augment SASE security, performance optimization, administration, visibility, configuration, and support.

The CISO empowerment that AI-powered SASE provides compresses the customer value chain. AI in SASE brings new security use cases directly to the customer, enabling security leaders to analyze more data, engage more conveniently with cybersecurity platforms via natural language interfaces, and better control their SASE platforms. This insight examines vendor applications of AI technology in SASE solution delivery: specifically, how AI is making cloud zero trust architecture platforms better.

AI in all its flavors is essential for SASE platform development. It aids in the consumption and analysis of massive stores of data, something crucial for security providers aiming to learn from the collective experience of their customers around the globe. SASE developers use AI to automate mundane tasks, but also for crucial activities such as threat detection, signal analysis, and even security policy development.

AI is also facilitating SASE administration. Its natural language processing capability can translate complex or esoteric capabilities into common vernacular, enabling CISOs or end users to engage with SASE systems via custom queries.

SASE vendors develop AI capabilities into their cloud zero trust architecture platforms in two ways: some build their own large language models and create custom algorithms and intellectual property for AI application in their SASE platforms; others employ and/or extend commercial or open-source generative AI applications to create chatbot services or proprietary AI tools.
Regardless of vendor SASE AI development approach, SASE AI will always be only as good as the material it learns from. Done right, AI in SASE can deliver better enterprise security, optimize connectivity performance, ease configuration, and improve user experience outcomes. Taken together, those added-value benefits mean AI application has the potential to be a significant differentiator for SASE vendors.

Author: Toph Whitmore