Throughout history, the ambition of technological advancement has always been driven by the pursuit of human prosperity. But with AI, we are approaching a pivotal gut check to live up to this promise for the next generation. In my role as CTO at SAS, I talk with a lot of
As we wrap up 2025, subject matter experts across SAS have been thinking ahead to 2026 and how we might see AI evolve in the public sector over the next 12 months. Recently, we released a compilation of public sector AI predictions, including mine: AI-led extraction and entity resolution will
People are starting to compile resolutions for the new year, focusing on evolving their own habits and goals. At SAS, we’ve also looked toward 2026 to gather predictions on how AI in the public sector might evolve over the next 12 months. Prediction: By 2026, governments will utilize large language
For years, “responsible AI” has lived comfortably as a corporate promise, a slide in a presentation, a talking point at a conference. But as the EU AI Act phases into force, that comfort is rapidly eroding. The regulation officially entered into force on August 1, 2024, but its obligations will
Health care is entering a new era, one that moves closer to where people live. By 2026, the traditional model of care, centered around hospitals and clinics, is giving way to a more decentralized, patient-centric approach. This shift is driven by three converging forces: rising costs, evolving patient expectations and
Hackers have a major milestone to celebrate this year as the phishing attack turns 30 years old. Phishing attacks can be traced back to the 90s, coinciding with the popularity of America Online (AOL). For those too young to remember, AOL was an early internet service provider that revolutionized the
Imagine being dropped into a vast mountain range, such as the Adirondacks and being tasked with finding a specific lake. You are told that the lake is located at the lowest part of the mountain range and the only tools you are given are a compass and a method for
Recently, AOL discontinued the dial-up tone synonymous with the internet. After 34 years, we will no longer hear the mechanical screech of connecting to the World Wide Web. Nostalgia notwithstanding, this news gives me pause to contemplate what my children will see sunset in their lifetimes. Consider Google today. A
Our daily lives are constructed from a continuous series of choices; some small, some big, some connected, many unrelated. These choices are intentional decisions we make to steer ourselves towards our goals (or away from potential pitfalls). Organizations do this, too, although how and by whom is often unclear. As
When companies invest in AI, the first question often asked is: “What’s the ROI?” It's a fair question – but often the wrong one, at least in the way it's traditionally framed. In the early 2000s, no one could give you an ROI calculation for building a website. But they could
Would you trust a car to make a life-or-death decision for you? That’s the kind of question that sits at the heart of AI today. As AI rapidly becomes a part of our everyday lives, from smart assistants to AI agents, it’s easy to get swept up in the excitement.
A new study spanning more than two decades and more than 500,000 issuer-months presents one of the most accurate and forward-looking models of corporate credit rating transitions to date. By combining machine learning with the SAS® KRIS® 1-year default probability (KDP), the authors show how investors can gain a powerful
When AI projects stall or fail, most leaders assume the culprit is flawed models or immature technology. But research shows the real barrier is trust. The new Data and AI Impact Report uncovered what we call the trust dilemma: the gap between how AI is perceived and how responsibly it’s
Procurement has long been burdened by complexity – slow contract cycles, compliance risks and manual handoffs that eat away at time and efficiency. As AI matures beyond basic chat interfaces and static outputs, procurement leaders are beginning to witness the transition from manual inefficiency to automated agility. What makes agentic
Before we get started, I’d like to acknowledge that we’re inundated with buzzwords – all day, every day. I work in marketing, so I totally understand I’m part of the group to blame (sorry). But hear me out: “AI engineering” not only makes sense, but it’s critical to the future
Generative AI (GenAI) adoption is skyrocketing, but are leaders putting too much trust in it? The new Data and AI Impact Report found decision-makers trust GenAI three times as much as traditional machine learning, even though machine learning is more mathematically explainable. Just because GenAI seems trustworthy doesn’t mean it
Agentic AI is generating excitement and being cheered as the next frontier in automation and decision-making. However, beneath the buzz, lies a sobering forecast: Gartner warns that “over 40% of agentic AI projects will be canceled by the end of 2027, due to escalating costs, unclear business value, or inadequate
Financial institutions operate in a highly regulated, data-sensitive environment. At the same time, these institutions are under pressure to modernize credit scoring models that balance fairness, accuracy and compliance. The challenge? Most financial institutions lack access to the volume and diversity of high-quality, privacy-safe data needed to fuel these models.
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
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.
