As AI agents act autonomously in public spaces, recent incidents highlight the urgent need for strong guardrails, ethical alignment, and human judgment to ensure AI augments society rather than undermines trust, work, and human connection.
As AI agents optimize how they communicate, the shift away from human-readable language underscores why transparency and interpretability are essential for building trust in autonomous systems.
As AI agents gain autonomy and access to sensitive systems, emerging threats like prompt injection worms highlight how human-like security training and governance must evolve to prevent large-scale, opaque cybersecurity breaches driven by agent behavior.
Learn how integrating the Model Context Protocol (MCP) into SAS Retrieval Agent Manager transforms retrieval-augmented generation from a passive information system into a governed, scalable, and action-oriented enterprise AI platform capable of executing real business workflows.
This article was co-written with Sundaresh Sankaran. The Artificial Intelligence (AI) era is here. To prevent harm, ensure proper governance and secure data, we need to trust our AI output. We must demonstrate that it operates in a fair and responsible manner with a high level of efficiency. As builders of
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SAS empowers modern demand planners with AI-driven tools like SAS Visual Forecasting and SAS Intelligent Planning to meet rising customer expectations through accurate, responsive, and scalable demand planning solutions.
