Agentic AI transforms enterprise decision automation with trust and transparency

Enterprises are rapidly adopting agentic AI—autonomous systems capable of independent operation, learning, and decision-making. This shift marks a new phase in AI transformation, where organizations must balance innovation with trust and transparency.

Key Insights from SAS

• Three-Pronged Approach: SAS focuses on:

  • Embedded AI assistants for productivity
  • Customizable agents for unique workflows
  • Pre-built agents based on industry models

• Trust as a Priority: Shadi Shahin, VP of Product Strategy at SAS, emphasized the need for monitoring and validation to prevent AI-driven missteps. "Agents are about autonomy, but we must ensure they don’t lead us down the wrong path," he said.

• Phased Adoption: SAS recommends starting small—measuring success with a single agent before scaling—to build confidence and secure funding for broader implementation.

Challenges and Solutions

• Data Quality Risks: Synthetic content and LLM hallucinations pose threats. SAS integrates:

  • Explainability mechanisms
  • Rule-based compliance checks
  • Rigorous data governance

• Platform Support: The SAS Viya platform enables end-to-end agent development, deployment, and monitoring.

Industry Context

Shahin spoke at the AI Agent Builder Summit, highlighting SAS’s commitment to customer success. "We’re not just in the technology game—we’re here to help enterprises make better decisions," he noted.

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Disclosure: SAS sponsored this segment. Sponsors do not influence editorial content.