As adoption of AI agents looks set to surge by as much as 300% in the next two years, leadership teams are carefully considering the implications of a hybrid human-AI workforce. Unlike existing enterprise-level automation that relies on manual input, AI agents are capable of autonomously coordinating complex tasks, interacting with multiple tools and environments across…
At SXSW London last week I gave a talk called “Five things you need to know about AI,” in which I shared what I think are the biggest themes in AI right now. I pulled a few things from our first AI10 list, an annual guide to the most important trends in this buzzy world,…
Remember Claude Mythos Preview? Yes, the very AI model that Anthropic had announced earlier this year, one that sent even the governments around the world into a frenzy. The model that found security loopholes in almost any network it was tested on, and was so powerful that it had to be kept limited within a very controlled environment of existing Anthropic […]
The post I Tested Claude...
Enterprise leaders face a growing gap between rapid AI advancement and the fragmented data and processes that limit their ability to operationalize it. In this episode, Guillermo Vazquez, Chief Architect in the Business Transformation Services for SAP America, examines with host Nick Gersch how harmonized data, standardized processes, and clear identification of differentiating workflows...
Every hour your team spends manually checking dashboards is an hour not spent fixing what those dashboards reveal. By the time someone spots a problem (a campaign bleeding budget over the weekend, a location with a sudden cost spike, a trial account going quiet), the window for action has already narrowed. Automated dashboard alerts change […]
The CFO opens the board meeting with a revenue figure. The sales director pulls up their dashboard. The numbers don’t match. Both teams insist they’re looking at the same data. Both are right, and that’s exactly the problem. Data discrepancies are one of the most destructive and least-diagnosed issues in modern data operations. They erode trust […]
Time series forecasting predicts future values by learning patterns from past data. It is widely used in sales, finance, energy, web traffic, inventory planning, and business decision-making. But a lot has changed since the advent of advance ML models. Forecasting has moved from traditional statistical models to neural and foundation-model approaches. Tools like Prophet, NeuralProphet,...
While AI usage is widespread, finance leaders cite governance challenges, skills gaps, and data quality concerns as key obstacles to broader deployment RALEIGH, N.C. — June 9, 2026 — New research from insightsoftware, the most comprehensive provider of solutions for the Office of the CFO, reveals a growing gap between AI adoption and AI readiness […]
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AI powered Power BI reporting skills is a collection of multiple skills that enables AI agents to automate report creation, from designing pages to publishing to Fabric. Now available through the Power BI authoring plugin in Skills for Fabric —a first-party catalog of agent skills for Microsoft Fabric optimized for GitHub Copilot CLI—this capability allows agents to author reports through...
This article will teach you how to perform a language task like text classification by integrating locally hosted large language models (LLMs) of manageable size, like Mistral, Gemma, and Llama 3: all for free thanks to Ollama — a free repository for local LLMs — and the Scikit-LLM Python library.