For many organizations, SAS 9 is more than just an analytics platform. It’s an integral part of how critical decisions are made every day, from banks managing credit risk and detecting fraud, to insurance companies analyzing claims and pricing, to healthcare organizations identifying fraud, waste, and abuse, to government agencies improving public programs, and manufacturers using data to improve operations and safety.
SAS 9 is trusted because teams rely on its consistency, accuracy, and management to make important decisions. It’s familiar because users know how to work with it and it’s deeply integrated into workflows, reports, and processes that turn data into insights.
SAS Viya is the next generation of the SAS platform. It helps organizations evolve beyond SAS 9 by modernizing the data and AI lifecycle, from data management and analytics to AI development, deployment, and operational decision making. Teams can work faster, collaborate more easily, and move analytics to production with less friction. They also have the flexibility to deploy across cloud, hybrid, and on-premises environments while maintaining the governance and analytical accuracy they value from SAS.
The question many SAS 9 customers ask is not whether or not to update, but where to start and how to do it in a way that builds on the SAS software, data pipelines, reports, and user experience that already exists.
Update with purpose
Updating SAS Viya doesn’t have to be an all-or-nothing decision. It can start with specific business needs, such as accelerating an AI use case, scaling high-value analytics workflows, or helping SAS, Python, and R users collaborate more easily in a single, managed environment.
Four areas emerge where Viya can make this difference: assistive AI that helps people act faster, agent AI that connects vision to action, open collaboration across SAS, Python, and R, and scalability to meet data and AI demands.
1. Working with AI across data and the AI lifecycle
SAS Viya Copilot helps make analytics easier and more productive by bringing natural language assistance to the way people already work. Users can ask questions, get contextual guidance, and move from data to insight without relying on each step being manual or highly specialized. For example, Copilot can help users code, explore data, create interpretations, determine next steps, and complete common tasks more efficiently.
This is important for teams trying to do more with limited time and resources. At Viya, Copilot connects to the data and AI lifecycle, so users can work faster, build trust, and stay within a controlled SAS environment rather than moving work to disconnected tools.
2. Move from insight to controlled action with agentic AI
Artificial Intelligence is evolving from systems that generate answers to systems that can help analyse, decide, and act within business workflows. In SAS Viya, agentic AI can connect data, analytics, decision-making, and governance so that AI-powered actions are transparent, controlled, and aligned with business rules.
This can help teams go beyond recommendations to action, such as prioritizing a fraud alert, launching the next best offer, directing a service issue, or enforcing a policy decision, while keeping humans on top of what matters for governance and accountability. For organizations, the value is not just in automation. It’s reliable automation, with oversight where it matters.
3. Bring the SAS, Python, and R teams together
Modern analytics teams rarely use a single language or tool. SAS, Python, and R users often need to work on the same problems, such as preparing data, testing models, comparing methods, or sharing results, even when they start from different tools and workflows.
SAS Viya brings together ways of working in a single managed environment. Teams can use familiar tools, reuse existing SAS assets, collaborate on shared data and models, and move work from experimentation to production with greater consistency, control, and scale.
4. Scale confidently as data and AI requirements grow
Analytics workloads rarely stay the same. Data volumes are growing; More users need access to insights and AI projects can require significant computational operations. SAS Viya gives organizations the flexibility to scale analytics as demand changes, rather than being limited to environments that weren’t designed to handle today’s data and AI workloads.
With Viya, teams can support more users, run more workloads and choose deployment options that fit their environment, including cloud, hybrid, and on-premises. For example, organizations can expand model training capacity, support seasonal increases in demand and give more teams access to shared analytics resources.
SAS Managed Cloud Services can also help reduce the operational burden of platform management, giving teams another way to modernize with a greater focus on analytics results rather than infrastructure management.
What this means for SAS 9 customers
Together, these areas point to a larger shift. Instead of treating analytics as a set of discrete tasks, organizations can manage data, AI, and decisions as a connected, governed lifecycle. AI assistance, agent AI, open collaboration, and cloud scale support every transformation by helping teams work faster, move from vision to action, collaborate more easily, and make room for future growth and innovation. The opportunity is to make modernization focused, achievable and linked to business value. Start with the most important work, and then go from there.
Are you ready to explore your Viya path?
If your team is already delivering value with SAS 9, Viya can help you build on that foundation. Start with the most important opportunity, whether that’s faster AI development, smoother collaboration, easier deployment, or greater scale. Contact us To start the conversation.
Additional resources
To dig deeper, explore these resources:
- SAS FIA co-pilot: Learn how natural language assistance can help users work faster across the data and AI lifecycle.
- Amnesty International agent: Discover how AI agents can support controlled decisions and actions.
- Open source SAS integration: Learn how SAS, Python, and R users can work together in a single managed environment.
- SAS Viya workbench: On-demand computing power and self-service flexibility for fast SAS, Python or R coding.
- Go to the SAS Viya webinar series: On-demand sessions featuring clear migration paths, step-by-step product walkthroughs, and demos from the SAS Enterprise Guide® and SAS Analytics Pro moving into data integration, visual analytics, and modeling.
- SAS Managed Cloud Services: Learn how managed services can reduce operational complexity.
