SAS forges path beyond generative AI with intelligent decisioning and industry-specific solutions

AI SAS Moves Beyond Generative AI Trend into Intelligent Decisioning

Since the arrival of ChatGPT, many companies have rushed to adopt generative artificial intelligence (gen AI). However, becoming truly AI-driven involves more than just jumping on the latest trend. SAS Institute Inc. takes a different approach by focusing on the best artificial intelligence technique for each customer's specific needs.

Jay Upchurch, Chief Information Officer at SAS, explains that the industry initially got caught up trying to apply generative AI to every problem. This led to significant spending on solutions that might have been better addressed with other AI methods.

Choosing the Right AI Approach

Instead of immediately using gen AI, SAS evaluates what tool fits the client's situation best, especially since many of their customers operate in high-stakes fields like healthcare. Inaccurate AI results in such areas can have serious consequences. Upchurch emphasizes the importance of data readiness: "What does your data state look like? Is it well-governed? Is it secure?"

He points out that organizations are at different stages in their AI journey and that leadership direction plays a crucial role. For example, a CEO might mandate that all initiatives be AI-driven, but without proper data governance, that push can fall flat.

Governance and Customization

SAS prioritizes AI governance and offers flexible solutions tailored to each client. Recent updates to Viya, SAS's cloud-based AI analytics platform, enhance governance features and allow users to build AI agents for specific industry tasks.

Upchurch highlights the company culture as a key factor in their ongoing innovation. Their talented teams draw inspiration from customer needs, fueling a continuous cycle of development that has driven SAS for decades.

Conclusion

SAS’s approach shows that effective AI integration means more than following the latest buzz. It requires thoughtful selection of AI techniques based on data quality, industry requirements, and clear leadership support. For organizations looking to advance their AI capabilities responsibly, focusing on intelligent decisioning and governance is essential.

For those interested in learning more about AI applications and governance, exploring latest AI courses can provide practical insights and skills.