I've seen firsthand how companies often treat AI governance as a necessary evil – something bolted on after innovation, like installing smoke detectors in a finished building. As both a data scientist building models and an advocate pushing for responsible AI practices, I experienced this dynamic daily. The companies winning
As more organizations migrate work to the cloud, the conversation is moving from infrastructure requirements to the impact of cloud technologies. Organizations can see the benefits. IT teams are being freed up to focus on innovation and high-return projects. According to Gartner, cloud computing is a must for capitalizing on
Leading brands like Macy’s prioritize creating meaningful, personalized customer experiences driven by data and thoughtfully orchestrated marketing decisions. Macy’s focus centers on customer obsession, which fuels its drive for customer loyalty and sustainable growth. Marketing analytics and AI serve as the foundation for a successful marketing decisioning journey underpinned by
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
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 For pharmaceutical companies, outdated technology systems can slow everything down, delaying
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
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
“What’s in the box?” This question can come from a joyous child tearing into a nondescript package – or it can come from Brad Pitt’s infamous line in the crime thriller Seven. Most of the time, what’s in the box ends with smiles and laughter. In banking, though, the “box”
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.
The emergency department (ED) has always been the front line of patient care – fast, chaotic and often lifesaving. But behind every quick decision made by a clinician, there’s a critical dependency: the lab. The link between EDs and hospital labs has a rich history, rooted in science, technology and
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
In a world where headlines often warn of automation replacing jobs and AI outpacing human creativity, it’s easy for young professionals to feel uncertain about their place in the future. But this summer, a group of SAS interns proved that technology can be a tool for good. Through a data
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
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
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
AI is transforming every industry, from automating insurance claims to optimizing supply chains in manufacturing. But for many organizations, the challenge isn’t whether to adopt AI; it’s how to start. This blog, the first in a two-part series, outlines the initial steps you can take to deliver a strong foundation for
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
The first leg of SAS Innovate on Tour has wrapped and what a journey it has been. These initial stops have set the tone for a year of innovation. Each recap below captures the energy and insights from the events so far, offering a glimpse into how data and AI
Financial fraud is a high-stakes issue in banking, where schemes are becoming increasingly sophisticated and costly. As a result, detecting anomalies quickly and accurately is a top priority. But traditional data-driven fraud detection models face challenges such as data scarcity, privacy constraints, and model bias. This is where synthetic data
