Leaders are increasingly preparing their organizations for the latest AI technology. The problem? They aren’t ready and struggle to implement and show ROI. Despite widespread recognition of AI’s potential, a critical trust gap has emerged in the enterprise landscape. A report by the Boston Consulting Group (BCG) reveals that 74%
Generative AI is everywhere in the headlines, but for most organizations, the real challenge is making it work with their own knowledge base. That’s the focus for SAS and its long-time partner Pinnacle, who are applying retrieval-augmented generation (RAG) to put company data directly in the hands of employees, made
Evidence-based policing shifts the dynamic from intuitive assumptions to confident, accountable decision making.
Clinical trials are the engine behind every new treatment we see – from life-saving cancer drugs to vaccines that help us fight global pandemics. But behind the scenes, running these trials involves juggling massive amounts of complex, sensitive data. For pharmaceutical companies, outdated technology systems can slow everything down, delaying
SAS: Un pionero que sigue liderando Desde su inicio como proyecto académico en la North Carolina State University en 1976, SAS se ha consolidado como un líder global en analítica e inteligencia artificial. Durante casi cinco décadas, la compañía ha capacitado a las organizaciones para transformar datos en información estratégica,
For small to medium businesses, the pressure to innovate is real, but so are the constraints. Teams are expected to deliver more with the same resources, manual processes and limited budgets. Modernizing analytic workflows often feels out of reach, especially without enterprise-level staff or funding. But change is coming fast.
If you’ve ever heard someone mention a “SAS User Group” and thought, “What does that actually mean?” you’re not alone. These groups are a cornerstone of the SAS ecosystem – but unless you’ve attended a meeting or conference and seen them in action, they can feel a little mysterious. Let’s break
The banking industry is at a crossroads. With rising customer expectations, intense competition, ever-evolving regulations and mounting cost pressures, financial institutions must transform – or risk falling behind. Enter agentic AI, an advancement in artificial intelligence that’s poised to redefine how banks operate, serve, and grow. What is agentic AI?
Imagine you're embarking on a road trip to your favorite vacation destination. Like most travelers today, you rely on a GPS to guide you. But not all GPS systems work the same way. Some provide a rigid, pre-planned route that doesn’t account for real-time changes. Others dynamically adapt and reroute
This is the third in a five-part blog post series that delves into modernizing marketing strategies through the integration of advanced marketing platforms. I had the pleasure of interviewing Shaun Memon of Munvo for this series, where we discuss a wide range of topics, from fragmented MarTech stacks, first-party data
With AI emerging as an increasing priority for organizations across all industries, it is critical for business and technology leaders to ensure AI is adding transformational value. That was the central theme in a recent conversation SAS CTO Bryan Harris had with streaming news channel Ticker. Harris shared his perspective
A new report from MIT estimates 95% of AI projects will fail. That’s staggering. Corporate GenAI pilots are failing to deliver significant revenue growth or measurable impact. The primary issues are not the quality of AI models, but a “learning gap” and flawed enterprise integration. Recent findings from the SAS
With AI, insurance underwriting evolves – and insurers can choose to manage the decisions of their AI agents.
With strong governance, data quality and thoughtful integration, agentic AI can transform insurance underwriting.
At SAS Innovate in Orlando, our partners shared how they’re driving meaningful change with SAS®. From strengthening financial services with AI-powered AML solutions, to helping marketers build privacy-conscious personalization, to enabling scalable, cloud-based analytics, they’re showing what’s possible when innovation meets collaboration. In the video above, you’ll hear directly from
The speed at which your organization can deploy new AI models determines your ability to stay ahead of the competition. It’s a measure of your ability to experiment and innovate, try new things and learn quickly. It’s also one of the reasons organizations are investing in SAS® Viya® – which
Ever feel like tech headlines are coming at you faster than your morning coffee kicks in? One minute it’s LLMs, the next it’s agentic AI, and suddenly your spreadsheet wants to talk back. In a world where innovation never hits pause, SAS isn’t just watching the change; we’re part of the
Every organization collects data, but collecting it isn’t enough. For companies that want to make personalized offers, detect fraud and optimize supply chains, decision-making is the ultimate measure of analytics success. But despite massive investments in data infrastructure and AI, many companies still struggle to bridge the gap between insight and action. That’s
Every day, AI is making choices that shape lives, industries and the future. But can we trust those choices? Organizations are making huge investments in AI, and it’s changing how decisions are made. But without clear results and proven value, investing in these technologies may be a failure. In fact,
Experimentation is the engine of innovation. Whether optimizing manufacturing processes, testing new materials, or simulating policy outcomes, the ability to run controlled experiments is essential. Design of experiments (DOE) is a well-established statistical methodology that helps organizations systematically explore the relationships between variables and outcomes. However, traditional DOE has its
From transforming online insurance services to combating the opioid epidemic, SAS customers are using data and AI to drive innovation, enhance efficiency and make a positive impact on society. These stories – and more – offer a glimpse into how our customers are shaping the future with SAS. Dive into
Let’s face it, supply chains today can feel like one headline away from chaos. Whether it’s new tariffs, labor strikes, warehouse fires or unpredictable weather patterns, retail and consumer goods companies are constantly juggling curveballs. Each disruption comes with a price: tighter margins, out-of-stock products, unhappy customers and many operational
Synthetic data – algorithmically generated data that mimics real-world data – has emerged as a cornerstone in modern AI workflows. But its promise comes with persistent myths about its capabilities, limitations and reliability. Synthetic data is being explored across industries, from training machine learning models to helping businesses safeguard customer
Every AI success story starts with a single decision: to move beyond experimentation and commit to real-world impact. But moving from idea to enterprise-scale deployment isn’t just about algorithms – it’s about laying the right groundwork. In the first part of this series, we explored three ways to lay the
Get inspired by a SAS Hackathon team that used AI and IoT to tackle heat stroke.
AI agents take on more responsibility in our most sensitive systems – from finance to public safety to health care – one thing is clear: trust can’t just be designed in. It has to be sustained. Continuously. In the first two parts of this series, we explored the ethical foundations
At SAS Innovate in Orlando, some of our partners spoke firsthand about how they’re driving innovation and delivering results with SAS®. In the video above, leaders from across our partner ecosystem offer insights into how collaboration, innovation and analytics are coming together to solve complex challenges and deliver results that
This is the second in a five-part blog post series that delves into modernizing marketing strategies through the integration of advanced marketing platforms. I had the pleasure of interviewing Shaun Memon of Munvo for this series, where we discuss a wide range of topics, from fragmented MarTech stacks, first-party data
They say data is the new oil, but it’s only valuable if you can refine it into something useful. In transportation, that means turning raw traffic data, sensor inputs and video feeds into real-time insights that actually improve how we move. That metaphor set the tone for a 2025 IoT
In an uncertain geopolitical world, integrated balance sheet management (IBSM) is crucial for building financial resilience. Fragmented risk systems hinder banks’ ability to navigate volatile markets. Isolated control models are especially problematic when managing liquidity, profitability and capital efficiently. According to a recent FT Longitude survey of executives from 300
