Aggregated enterprise architecture wisdom
By Christian Siegers, of KPMG Netherlands In a previous article, The Resilience Paradox, I argued that AI is forcing organizations to rethink resilience. As enterprises become increasingly dependent on AI platforms, data ecosystems and interconnected […
Put four enterprise architects in a room and ask them how AI should fit into architecture practice, and you will not get a single answer. However, it will spur a deeply insightful conversation about the very real struggles organizations today …
By Dr. Robert Furey Something is coming. Something as astounding as creation itself. As mind-boggling as stellar nucleosynthesis or the discovery of flint knapping. Looking backward we see a vista of change. From where we […]
Tom King, a longtime leader in electric grid research at the Department of Energy’s Oak Ridge National Laboratory, has been named director of the Next-Generation Data Centers Institute (NGDCI). The institute “aligns ORNL’s capabilities across com…
By Joydeep Sarkar, of Wipro Ltd Abstract Retrieval-Augmented Generation (RAG) has emerged as the industry standard for grounding Large Language Model (LLM) outputs in proprietary data; yet, the persistence of “grounded hallucinations”, wher…
By Holt Hackney A series of recent AI security lapses, including the OpenAI-Hugging Face incident, is raising a broader governance question: Can technology companies adequately oversee the increasingly powerful AI systems they develop, or will […]
Why architecture and governance functions need an accurate model of what AI systems actually are before they can be trusted, controlled, or blamed. By Stuart Dee There is a seductive habit, in boardrooms and server […]
By Ashokkumar Ganesan, AI Governance & Decision Architecture Executive Summary Enterprises today are investing heavily in AI governance: policies, principles, committees, risk frameworks, and compliance programs. Yet AI systems continue to fail in …
We brought enterprise architects and IT leaders together for our Customer Advisory Board this spring, and the conversations didn’t go the way most AI panels do. Nobody argued about whether AI matters, but instead what it’s exposing.
By Dr. Magesh Kasthuri Small Language Models, commonly called SLMs, are becoming a practical alternative to very large general-purpose models for enterprises that need sharper domain behavior, lower latency, better cost control, and stronger governance…
A practical pattern for preserving trusted business logic, while transforming the digital experience. This article uses a real-world enterprise modernization initiative as the reference implementation. By Alok Mehta Every enterprise architect eventuall…
Over the past few years, progress in large language models has often been associated with a single word: bigger. Larger parameter counts. Larger training datasets. Larger computational budgets. And, with each new generation, stronger performance […]