SAS Viya platform is getting agentic AI features, including SAS Viya Copilot that embeds AI assistants into analytics workflows to assist with data exploration, model development, and decision-making, all under strong governance controls.

Data governance and auditability are fundamental design principles across Viya-based data management, aiming to enable scalable, trusted AI across enterprises.

A refreshed SAS Data Management portfolio, cloud-native and built on Viya, is rolled out to help organizations prepare, govern, and activate data for analytics, automation, and AI.

The MCP server and agentic AI toolkit are closing the gap with peers and are valuable for SAS's current customer base, reinforcing a governance-focused approach.

SpeedyStore and industry-specific copilots are highlighted as important steps to bridge SAS analytics with modern data lakehouse architectures.

New tools include the Agentic AI Accelerator framework for building and managing agents, and the Model Context Protocol server to connect models with an organization's data for autonomous actions.

The strategy emphasizes analytics where the data resides, with SpeedyStore as a cloud-native analytics data platform that reduces data movement while preserving lineage and auditability.

Key capabilities include governance-by-design, AI-ready data management, agentic AI and copilots, and cloud-native analytics acceleration, illustrated by SpeedyStore and Data Accelerator to minimize data movement and latency.

IDC/SAS research notes data governance and centralized/cloud data environments as AI barriers, while Gartner says 60% of AI initiatives fail without AI-ready data.

Industry-focused agents, such as supply chain, asset and liability management, and health clinical data discovery copilots, come with governance tools like AI Navigator to inventory and govern AI usage.

Analysts say SAS’s measured, production-oriented approach meets customer needs for trustworthy AI, though some see it as more focused on incumbents than broad user expansion.

Industry AI agents, including the SAS Supply Chain Agent, aim to automate and optimize processes with conversational interfaces and near real-time scenario simulations.