What are AI agents?
AI agents are autonomous software systems that can analyze data, make decisions and take action to achieve specific business goals. Unlike copilots or chat-based assistants, AI agents operate across workflows – connecting data, analytics and decision logic to execute tasks with minimal human intervention.
AI agents need more than LLMs – and SAS delivers
Language models alone do not solve business problems. As AI agents take on greater responsibility across enterprise workflows, they must do more than generate responses – they must employ the necessary and appropriate tools and resources to drive decisions and actions that are accurate, explainable and aligned with business objectives.
This requires more than a model. It requires a complete system that includes:
Governed data
Access to trusted enterprise data to ensure decisions are based on accurate, secure information.
Advanced analytics
Predictive models, optimization and statistical methods to guide decisions.
Decision logic
Business rules and workflows that ensure agents take the right action – not just any action.
Governance & compliance
Explainability, auditability and control across every decision.
How SAS enables trusted AI agents
SAS transforms generative AI from simple chat interfaces into autonomous, accountable enterprise systems. By combining governed data, advanced analytics and decision intelligence, SAS enables AI agents to execute complex workflows – such as fraud detection and supply chain optimization – with reliability, transparency and measurable ROI.
SAS operationalizes this through a unified platform that brings together the core capabilities required for enterprise AI agents:
Data
Data access & integration
Connect AI agents to trusted, governed data across the enterprise – without compromising security or control.
Analytics
Advanced analytics & modeling
Embed predictive models, optimization and statistical analysis directly into agent workflows.
Decisioning
Decision intelligence
Combine analytics with business rules and decision flows so agents don’t just generate insights – they take the right action.
Governance
Governance & compliance
Ensure every decision is explainable, auditable and aligned with regulatory and organizational requirements.
Scale
Enterprise deployment at scale
Build, deploy and manage AI agents across environments with the reliability and performance required for mission-critical operations.
Where AI agents deliver measurable business value
AI agents create the most impact when applied to operational decisions that directly affect performance, cost and risk.
Marketing
AI agents for customer engagement
AI agents help marketing teams design, optimize and execute customer journeys in real time. They analyze behavior, segment audiences and trigger personalized interactions across channels.
Results:
Faster campaign execution, improved targeting and higher engagement and conversion rates.
Financial services: Risk management
AI agents for collections & risk
AI agents analyze customer behavior, sentiment and risk signals to prioritize outreach and recommend next-best actions in collections and servicing workflows.
Results:
Improved recovery rates, reduced operational cost and more consistent decisioning.
Financial services: Compliance
AI agents for sanctions screening
AI agents automate compliance checks against sanctioned entities using machine learning, rules and contextual intelligence. They perform initial triage and generate audit-ready documentation.
Results:
Faster reviews, reduced false positives and stronger regulatory compliance.
Supply chain
Agentic demand forecasting & planning
AI agents continuously monitor demand, supply and inventory signals to detect changes and recommend actions. Planners can interact with the agent to understand what changed, why and how to respond.
Results:
Improved forecast accuracy, faster decisions and reduced risk of shortages or excess inventory.
Health care
AI agents for medication adherence
AI agents monitor patient behavior and intervention signals to identify adherence risks and trigger timely outreach.
Results:
Improved patient outcomes, increased adherence rates and more efficient care management.
Developer productivity
AI agents for code generation
AI agents assist developers by generating, refining and explaining SAS and Python code. They help identify issues, recommend improvements and accelerate development workflows.
Results:
Faster development cycles, improved code quality and increased productivity.
Data management
AI agents for data mapping & integration
AI agents automate data integration and mapping tasks, transforming complex data environments into formats ready for analytics and AI models.
Results:
Reduced manual effort, faster data readiness and improved model performance.
Built for enterprises that can’t afford to get AI agents wrong
Scaling AI agents requires more than experimentation. It demands a foundation built for trust, control and measurable outcomes. Unlike generic AI tools, SAS combines data, analytics, decision intelligence and governance into a unified platform for enterprise AI agents.
With SAS, organizations can scale AI with:
Transparency & explainability
Regulatory compliance
Human oversight
Measurable business impact
Turn AI agents into trusted business outcomes
Whether you're building your first AI agent or scaling across the enterprise, SAS helps you move from experimentation to trusted, governed and outcome-driven AI. SAS enables you to design, connect and scale AI agents into real business workflows – accelerating time-to-value while maintaining control and trust.
Build
Build & deploy governed agent workflows
Create AI agents that don’t just generate insights, but take action within defined business rules.
With SAS® Viya® and the SAS Agentic AI Accelerator, teams can design, deploy and monitor agent workflows with built-in explainability, guardrails and human oversight.
Connect
Connect AI agents to enterprise systems & analytics
Integrate AI agents into your existing data, models and decisioning processes.
Through SAS Viya MCP Server, agents can securely access SAS capabilities – preparing data, running models, scoring outcomes and triggering decisions with full auditability.
Ground
Ground agents in business context
Ensure AI agents operate with the right data, policies and institutional knowledge.
SAS combines retrieval-augmented generation (RAG) with governed data access to connect agents to enterprise context – so decisions are relevant, explainable and aligned with organizational goals.
Accelerate
Accelerate with prebuilt AI agents
Move faster with validated, purpose-built agents designed for high-impact use cases.
SAS provides ready-made agents for areas like marketing, risk and supply chain – so teams can start delivering value immediately without lengthy build cycles.
Recommended resources on agentic AI
Agentic AI frequently asked questions
What are AI agents?
AI agents are autonomous software systems that can analyze data, make decisions and take action to achieve specific business goals. Unlike chat-based assistants, AI agents operate across workflows, connecting data, analytics and decision logic to execute tasks with minimal human intervention.
What is agentic AI?
Agentic AI refers to systems of AI agents that can act independently to complete tasks, make decisions and drive outcomes. It combines technologies such as large language models (LLMs), machine learning, decisioning and automation to enable AI systems that move beyond conversation to real-world action.
How are AI agents different from copilots or chatbots?
Copilots and chatbots primarily assist users by generating responses or recommendations. AI agents go further by taking action – executing workflows, triggering decisions and operating across systems based on data, models and business rules.
Why do enterprise AI agents need more than LLMs?
LLMs are powerful for understanding and generating language, but they do not provide the full system required for business decision-making. Enterprise AI agents also need:
- Trusted data.
- Analytical models.
- Decision logic.
- Governance and compliance.
Without these, AI agents may generate outputs, but cannot deliver reliable, auditable business outcomes.
What makes AI agents “trusted” in the enterprise?
Trusted AI agents are:
- Governed (aligned with policies and regulations).
- Explainable (decisions can be understood and audited).
- Controlled (operate within defined business rules).
- Accountable (produce measurable outcomes).
These characteristics are essential for deploying AI in regulated or high-risk environments.
How does SAS support AI agents?
SAS provides a unified platform that combines:
- Data access and integration.
- Advanced analytics and modeling.
- Decision intelligence.
- Governance and compliance.
This enables organizations to build and deploy AI agents that are trusted, scalable and aligned with business objectives.
How does SAS ensure governance and trust in AI agents?
SAS provides a unified system for AI governance that ensures every agent-driven decision is explainable, auditable and compliant. By combining advanced analytics with business rules, SAS prevents the black box risks often associated with language models alone.
Can AI agents be integrated into existing business decisioning?
Yes. Using SAS Intelligent Decisioning, organizations can embed complex business rules and analytics directly into agent workflows. This ensures that agents take actions aligned with specific organizational goals, such as fraud detection or supply chain optimization.
What are common use cases for AI agents?
AI agents are used across industries to automate and improve operational decisions, including:
- Customer engagement and marketing optimization.
- Fraud detection and risk management.
- Supply chain planning and forecasting.
- Health care monitoring and intervention.
- Data integration and preparation.
They deliver the most value in high-volume, decision-driven workflows.