Shadow AI was already a problem
Now we're entering the era of shadow agents. An employee creates an AI agent.....Connects it to company data.......Gives it access to an...
What it takes to run AI and autonomous agents reliably in the enterprise.
Now we're entering the era of shadow agents. An employee creates an AI agent.....Connects it to company data.......Gives it access to an...
Before an agent enters the enterprise environment, you should know: Who is it? Who owns it? What is it allowed to access? What can it do? What data can it...
Why? Because AI agents need context. An agent working with customers needs to know which customer record is authoritative. An agent working with products...
Why? Because AI agents don't just need models. They need context. And enterprise context lives in: ->CRM ->ERP ->PIM ->MDM ->Documents ->Knowledge bases...
and seeing 150,000 AI agents. That's Gartner's prediction for the average Fortune 500 enterprise. For context, Gartner says the number was fewer than 15...
That's one of the biggest mistakes I'm seeing in enterprise AI thinking. Consider three agents: Agent A: summarizes documents. Agent B: recommends pricing...
And we're asking AI agents to make decisions. MIT Technology Review Insights found that 55% of executives say their current data systems actively prevent...
I call it the Agent Control Plane. It should answer five questions: Who is the agent? What data can it access? What systems can it change? What decisions...
Agents that shine in a two-minute demo fall apart in a 20-hour workflow. The fix is state persistence, not better system prompts.
When an agent loops through thinking, critiquing, and fixing its own code, token usage explodes. If you don't control this at the architecture layer,...
The defining separator between the winners and everyone else won't be model capability. Gartner's latest Data & Analytics trends report highlights the...
Every enterprise is realizing a simple reality: your AI agent is only as good as the underlying data stack feeding it. The current operational model of...
If your enterprise AI agents are hallucinating, the problem isn't the model—it's your missing data context layer. According to Gartner's CIO & Technology...
Only 8% have a governance framework to control it. According to Deloitte, while adoption is accelerating, just 21% of organizations have mature oversight...
The root cause isn't the model. It's bad data. Recent 2025–2026 data from RAND, Gartner, and MIT Sloan exposes a critical truth: you cannot build 5-star...
Define the explicit boundaries, assign hard human ownership to every domain, and treat digital assets with strict strategic discipline.. 🔗 Read the full...
Bain & Company, in it's four-part series from Roadmap to Reality: Phasing Agentic AI into Production (Eric Sheng, Roger Zhu, Brendan O., Dale P., and...
Their core architectural standard is remarkably simple yet incredibly powerful: you must give every single autonomous agent a definitive, unalterable...
Just as you need a skilled product manager to guide software development, you need dedicated leaders to run autonomous agent fleets at scale. This role...
A shocking market evaluation shows that just 21% of companies possess the capability to govern the autonomous agents they are already running. When you...
Microsoft’s Cyber Pulse Report exposes that while 80% of Fortune 500 firms run agents, 29% of corporate staff are leveraging completely unapproved...
EY has mapped out a highly tactical blueprint consisting of 6 Steps to Enhance Agentic AI Governance. The framework dictates a precise operational path,...
The metrics looked incredible: reduced cycle times, minimized manual data entry, and seamless multi-system routing. He paused the presentation and asked a...
He woke up to an urgent compliance alert and a flurry of customer complaints. An autonomous data-routing agent had silently bypassed its internal...
To bridge this execution gap, I advocate IBM'S 5 Layer Context Model. An AI Epic cannot be committed unless it satisfies all 5 Context Layers. Layer 1 is...
I recently finished listening to a fascinating discussion on the AI in Infrastructure podcast with Anahita Tafvizi, Chief Data & AI Officer at Snowflake,...
Anthropic just dropped a comprehensive roadmap detailing exactly how to leverage AI tools like Claude to build a self-sustaining business from day one....
Deploying live agentic workflows without runtime guardrails is the enterprise equivalent of leaving the roof hatch unlocked and hoping nobody climbs. Data...
The recent Databricks Data + AI Summit dropped some massive updates, but two announcements got my attention: Omnigent: An open-source layer to build,...
Every department is building its own isolated chat or code-generation assistants. This tool sprawl creates an uncontrolled chaos of unmonitored spend,...
Have you ever wondered what all these terms mean? Data management terminology can easily blend together. Let's look at what the most commonly talked about...
The basement has broken plumbing. That gap kills innovation. Executives sit in clean, high-level meetings discussing grand generative visions, intelligent...
When you build a POC, you control the playground. The dataset is perfectly curated, the size is limited, and the system is implicitly fine-tuned to answer...
Many leadership teams assume that deploying a faster, larger model will inherently accelerate business outcomes. But when you strip away the technological...
You cannot patch a lack of data integrity with a highly sophisticated algorithm. Right now, leadership teams are rushing to deploy autonomous business...
You could sweep duplicate records, poor definitions, and unmapped metadata under the rug for a long time. A human analyst would usually spot the error in...
In fact, the more powerful your model is, the faster it will make catastrophic mistakes on messy data. Right now, executive teams want to deploy...
Leaders want to talk about how many autonomous agents they have running. They want to talk about the massive scale of their new language models. They want...
In 2005, it was the newest Enterprise Data Warehouse. In 2015, it was the ultimate Data Lake. Today, it’s the latest, greatest LLM or AI agent. The trap...
Today, it is a business necessity. Not just for risk management. Not just for IT departments. But for any organization that wants to successfully deploy...
While other organizations are stuck paying public cloud platforms, forward-thinking architecture teams are completely rewriting the rules of AI...
As enterprises transition from chatbots to autonomous systems, the conversation is shifting from capability to control. Deploying agents that can actually...
Context Engineering > Prompt Engineering: The future belongs to those who can manage the "memory" and "data access" of their agents. 2. Sandboxing is...
An autonomous agent burned a month of API budget in one afternoon. The lesson: agents need governance policies before they need more autonomy.
Databricks Academy is now offering all self-paced courses for FREE! • Build AI agents and applications using Mosaic AI • Collaborate on data science and...
AI-first startups in legal, tax, compliance, and financial services are leading the way. AI agents can handle basic tasks and extend human capabilities....
Weekly thinking on data and AI governance from Ash Srivastava.