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Consider the following quote from George Box: “All models are wrong, some are useful.” Most of today’s models are free. And models power AI outcomes. When considering your enterprise strategy, AI should fit snuggly into business processes that successfully execute tasks supporting the overall strategic vision – underwriting policies, pricing
Explore how SAS Health and SAS Viya help healthcare organizations transform clinical and operational data into predictive, AI-driven decisioning workflows that improve patient outcomes through risk identification, model deployment, and governed agentic AI.
Learn how SAS 9 programmers can use agentic AI tools such as Claude Code and ChatGPT Codex with SASPy to automate code generation, execution, testing, and debugging while maintaining human oversight, validation, and ownership of results.
This post introduces a conceptual, plug-and-play predictive maintenance framework for wind farm management.
Customer engagement is entering a new era that’s evolving very quickly. And it’s not defined by more messages or channels – it centers on intelligence, autonomy and trust. As organizations rethink how they connect with customers, a new model is emerging: engagement that predicts, learns and acts with purpose. In
Most of us think about digestion only shortly after we eat or if we experience gastrointestinal symptoms, but our guts are busy clearing leftover food particles, waste, and bacteria long after a meal. This digestive tract housekeeping involves a pattern of cleansing waves called the migrating motor complex (MMC), and
AI can analyze data, automate tasks and accelerate decisions. But as organizations adopt AI more broadly, one question continues to surface: What role do humans play? During the opening session at SAS Innovate 2026, SAS CTO Bryan Harris put that tension plainly when he asked, “Will people matter?” He described a growing
A bank deploys a new AI-powered credit decisioning model. The technology works. The model performs well. The business team is ready to move forward. Then the questions begin. Can we explain the recommendation? What data was used? Who approved the model? How do we monitor performance over time? What happens
Public health systems are under pressure from rising costs, workforce shortages, increasing demand and limited resources. Data and AI can help organizations use their resources more effectively, improve care decisions and deliver better outcomes. But the next phase of health care AI will depend on more than what the technology
Rules-based decisioning engines (also known as enterprise decisioning applications) have long been a mainstay for marketers. These applications automate marketing actions using predefined business rules. When the decision is executed as part of a marketing campaign, specific conditions defined in the rules will trigger actions without requiring manual segmentation or
A previous article discusses the problem of fitting a kernel density estimate (KDE) to data that are strictly positive. If you use a standard KDE, the resulting density curve might estimate non-zero probability for negative values. This is unsatisfactory because quantities like lengths and mass cannot be negative. The previous
As SAS celebrates its 50th anniversary, one question naturally follows: What comes next? Few groups have a better vantage point than the partners who work alongside SAS every day. They help organizations apply analytics and AI across industries, giving them a front row seat to the challenges customers are trying
Explore how the DementAI team used SAS Viya's integrated AI, machine learning, governance, and decisioning capabilities to help identify Alzheimer's disease up to two years earlier while maintaining the trust and oversight required in healthcare.
Most conversations about agentic AI focus on how autonomous these systems can become. Financial services leaders are asking a different question: Where should autonomy stop? For banks and insurers, the challenge is not simply deploying AI agents. It is determining how those systems, governance requirements and human expertise can work
AI is reshaping how work gets done across industries. In marketing, the real challenge is turning a multitude of ideas into a final campaign. A typical campaign often starts with a strategy meeting, followed by sessions with data teams and creative reviews. Stakeholders weigh in at different stages, sometimes with