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 [...]
The post Human in the lead: Redefining the...
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 [...]
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Learn how SAS 9 customers can modernize to SAS Viya incrementally, leveraging AI assistance, agentic AI, open-source collaboration, and scalable cloud deployment while preserving existing SAS investments and governance.
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Is the roof over your head about to cave in? Did you just change jobs, get married or start planning for retirement? In situations like these, most people think about their insurance. Life changes are a great time to evaluate insurance coverage (for customers and insurance companies alike), but waiting [...]
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Editor’s note: This post was co-authored by Diana Rothfuss. For the past few years, banks have focused on proving that AI can deliver business value. Across financial services, organizations have launched pilots, explored generative AI use cases and tested how AI can improve everything from customer engagement and fraud detection [...]
The post Beyond AI pilots: Why governance matters...
Mientras millones de personas siguen atentos cada partido, analizan alineaciones y debaten sobre las posibilidades de sus selecciones favoritas, existen diferentes factores cada vez más influyentes en los resultados dentro y fuera de la cancha: los datos, la Inteligencia Artificial (IA) y la analítica. El fútbol moderno ya no se [...]
The post Cuando el fútbol, la IA y la analítica...
Many AI initiatives don’t stall because of the models – they stall because of the data behind them. Teams can build promising prototypes, but moving those models into production is where progress slows down. Data is spread across systems, pipelines are difficult to maintain and governance often lags behind how [...]
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The Manual Reconciliation Problem: The Financial Close Needs AI, But Where? Last April FloQast, an American maker of accounting software, published something unusual: a detailed engineering post on Amazon Web Services’ machine-learning blog, co-authored with AWS personnel, explaining precisely how its AI-powered transaction-matching feature works under the hood. The post described cloud...
DataRobot OpenCode: your coding agent, your model choice There are over 70 coding agents on the market: Claude Code, Codex, Cursor, Copilot, Devin, and a long tail of smaller entrants showing up in engineers’ newsfeeds every week. Someone runs a benchmark, posts the leaderboard, and by the end of the week, half the org wants...
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As AI applications become more complex, the infrastructure powering them needs to evolve. Corey Sanders, SVP of Product at CoreWeave, joins Chris to discuss why AI requires a fundamentally different approach than traditional cloud computing. They explore AI-native infrastructure, training and inference workloads, the rise of agentic development, optimizing GPU performance, AI research...