The Intelligence Infrastructure Behind AI Agents
•InnovationThe Intelligence Infrastructure Behind AI AgentsByUri Knorovich,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license...
•Opinions expressed are those of the author.
•| Membership (fee-based)May 20, 2026, 08:15am EDTUri Knorovich, CEO and co-founder of Nimble, orchestrating thousands of web search agents to give you complete, accurate data in real time.
هذا الخبر من Forbes. خبر يقدم أدوات ذكاء اصطناعي للتلخيص والترجمة والاستماع.
InnovationThe Intelligence Infrastructure Behind AI AgentsByUri Knorovich,Forbes Councils Member.for Forbes Technology CouncilCOUNCIL POSTExpertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. | Membership (fee-based)May 20, 2026, 08:15am EDTUri Knorovich, CEO and co-founder of Nimble, orchestrating thousands of web search agents to give you complete, accurate data in real time. gettyFor decades, platforms like Bloomberg Terminal dominated financial intelligence by aggregating data, analysis and news into a single interface.Despite a strong affinity among its enthusiastic user base, that model is starting to break. The plain truth: the way we access and use data is fundamentally changing.Enterprises are now deploying AI agents to analyze markets, monitor competitors, automate research and support decision-making at scale. Still, as these systems move into real workflows, a limitation is becoming clear: AI is powerful, but it doesn’t know how to reliably interact with the outside world.Models can reason and generate, but they struggle with questions like “What’s actually happening in the market right now?”This isn’t a model problem. It’s an infrastructure problem: getting the right external information at the right time.There’s A Gap Between AI Potential And RealityWhen it comes to capturing relevant, external information, most of today’s AI systems operate on static knowledge or generic web search. They often work better in demos than in production.For example, in financial services, agents must validate companies, monitor regulatory changes and track real-time signals. In retail or CPG, they must understand pricing shifts, competitor activity and supply chain disruptions as they happen.Without reliable access to live information, most AI systems either hallucinate or fail silently. But neither is an acceptable outcome in an enterprise context.Ultimately, the problem that most organizations are startin...المصدر: Forbes | Source: Forbes
ملاحظة تحريرية | Editorial Note: نُشر هذا المقال في الأصل بواسطة Forbes. خبر (Khabr) هي منصة إعلامية أردنية مرخّصة تعمل بالذكاء الاصطناعي. نضيف قيمة تحريرية من خلال: تحليل ذكي للأخبار، ملخصات تلقائية، رواية صوتية بالذكاء الاصطناعي، ترجمة متعددة اللغات، وتدقيق الحقائق. هدفنا جعل الأخبار أكثر وضوحاً وسهولةً للقارئ العربي.
This article was originally published by Forbes. Khabr is a licensed Jordanian AI-powered news platform (Registration #82086). We add editorial value through: AI-powered news analysis, automated summaries, AI audio narration, multi-language translation (Arabic, English, French, Turkish), and AI fact-checking. Our mission is to make news more accessible and understandable for Arabic-speaking audiences worldwide.

