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Hits and Misses from Gartner Data & Analytics Summit 2026
Gartner opened the Data & Analytics Summit 2026 with a memorable metaphor. The keynote framed the current moment as a raft ride through a roaring, treacherous river. The river represented AI . Fast-moving. Powerful. Difficult…
AI Can't Run on Untrusted Data: Why Agentic Analytics Requires Live Semantic Connectivity
A logistics company deploys an AI agent to monitor inventory and automatically trigger reorders. The model is solid. The prompts are well-engineered. The agent connects to their analytics environment and starts running. Three weeks in,…
Autonomous AI Without a Semantic Layer Is Just Expensive Guessing
I’ve been in the BI and data space long enough to recognize when something fundamental shifts. Denny Lee and I first worked together when he was at Microsoft on SQL Server Analysis Services (SSAS) ,…
Headless AI Agents Are Already Here and They’re Where the ROI Is
Most enterprise AI conversations still center on prompts, whether through chat interfaces, copilots, or question-answer workflows. But the highest-value AI agents don’t wait for someone to ask a question. They monitor signals, detect thresholds, and…
The Missing Pillar in Agentic AI: Why I Joined AtScale
Recently, while debating my next career chapter with a close friend, they highlighted something I had almost begun to take for granted: the most important work our civilization is doing right now is tied to…
Why Agentic AI Fails Without a Semantic Layer
Many teams assume they’re doing agentic analytics because they support text-to-SQL or chat-based BI. And while conversational BI does change how questions are asked, it doesn’t go so far as to change how decisions are…
The Hidden Costs of Letting People “Talk to Data” with AI
Conversational BI pilots succeed because they operate in constrained environments. A dozen users, curated datasets, predictable query patterns. When AI agents enter the picture, everything breaks. Gartner forecasts that more than 40% of agentic AI…
AI Governance Isn't Theoretical Anymore: What Enterprise Leaders Are Actually Asking
AI governance discussions used to center on frameworks and theoretical risk scenarios. This month’s TDWI webinar with Cal Al-Dhubaib, head of AI and data science at Further, revealed the many ways in which theory has…
Why Most Enterprise AI Projects Fail (and How to Make Them Work at Scale)
Most enterprise AI projects follow a familiar pattern. Successful demos lead to promising pilots. Executives commit budgets to scale the initiative across departments. Then the wheels come off. Despite $30-40B in enterprise investment in GenAI…
Why Context Became the Most Critical Layer in Enterprise AI
I recently sat down with Juan Sequeda, Principal Researcher at ServiceNow and co-author of Designing and Building Enterprise Knowledge Graphs , to discuss what’s happening in enterprise data and AI. Listen to the full podcast…