At the SAS Innovate event held this week in Orlando, Florida, that I am attending, the business intelligence (BI) and data science giant SAS unveiled a series of releases aimed at harnessing AI.
Enhancing the SAS Viya data and AI platform
The SAS Viya platform has added the following features:
- SAS Data Maker is a secure synthetic data generator that helps organizations tackle data privacy and scarcity challenges, while simplifying processes and conserving resources. It incorporates technology from the recent acquisition of synthetic data pioneer Hazy. It will be generally available in the third quarter of 2025.
- SAS Viya Intelligent Decisioning facilitates building and deploying AI agents that balance AI autonomy and human involvement. It is available now.
- SAS Managed Cloud Services: SAS Viya Essentials packages select SAS Viya products for small and midsize businesses to reduce the barrier to entry by delivering SAS Viya in a small, out-of-the box hosted managed service.
- SAS Viya Copilot is an AI-driven conversational assistant embedded directly into the SAS Viya platform. It gives developers, data scientists, and business users a personal assistant that accelerates model development and provides code assistance for analytical, business, and industry tasks. General availability is coming in the third quarter of 2025.
SEE: SAS Innovate Keynote: SAS Says ‘Goodbye, GenAI; Hello, Agentic AI’
Embedding governance into enterprise AI
“SAS is evolving its strategy and portfolio to embrace a broader ecosystem of user personas, preferences, and technologies within an enterprise’s AI technology stack,” said Kathy Lange, research director for AI Software at IDC. “SAS continues to develop offerings that streamline and automate the AI life cycle and enable organizations to make better business decisions faster.”
- AI Governance Map helps organizations assess their current AI governance maturity across four areas to chart the path forward. This is a growing area of AI. As organizations implement AI – and some employees mis-implement it by exposing confidential data to outside eyes – they are realizing the need to set policy, guidelines, and a secure and compliant framework for GenAI in particular.
“Every large organization is dealing with the reality that AI is being embedded into their operations but without proper oversight so governance is becoming a big deal,” said Reggie Townsend, vice president, SAS Data Ethics Practice. “Policy is needed with clear lines existing for decision making as well as remediation actions laid out if things go wrong.”
Expanding industry application through modeling and simulation
SAS is investing in sector-specific models and immersive simulations to help organizations improve operational performance using AI-enhance tools.
- Digital twins from SAS have been enhanced with AI and GenAI technology and combined with Unreal Engine (UE) from Epic Games to add more detailed simulations in 3D via Epic RealityScan, a mobile app developed by Epic, to capture photorealistic renderings of environments and import them into UE.
- AI models address a specific labor- and time-intensive process that can drag business down. These packaged models come either ready-to-go or are intended to tailor and accelerate model training on customer data. Those currently available include:
- Document Analysis.
- Health Care: Medication Adherence Risk.
- Manufacturing: Strategic Supply Chain Optimization.
- Public Sector: Payment Integrity for Food Assistance.
- Tax Compliance for Sales Tax.
- Cross-Industry: AI-Driven Entity Resolution.
Building trustworthy AI agents at scale
SAS is aligning its platform strategy around agentic AI, focusing on the creation of AI agents that operate reliably and within clear ethical boundaries.
- SAS Intelligent Decisioning empowers organizations to design, deploy, and scale AI agents on the SAS Viya platform. Deterministic analytics work in conjunction with large language models (LLMs) to build AI agents with more precise and reliable outcomes. The appropriate level of AI autonomy can be set based on task complexity, risk, and business goals. Some AI agents can operate autonomously in routine, data-driven tasks while humans provide oversight, ethical judgment, and strategic direction. A built-in governance framework provides adherence to ethical and compliance standards, maintains data privacy, and aligns with business values.
“As organizations evolve toward open, interoperable AI ecosystems across multi-cloud and hybrid environments, trust and explainability in AI governance are emerging as key differentiators among tech vendors,” said Tiffany McCormick, research director, Digital Business Models and Monetization at IDC. “SAS is taking industry-leading steps to address the growing demand for agentic AI, with a clear commitment to ethical rigor and differentiated execution in AI decisioning.”
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