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Enterprise AI
57 articles
Straiker Raises $64 Million to Secure Enterprise AI Agents
Straiker, a Sunnyvale security company, raised a $64 million Series A to protect the AI agents that businesses now give real access to real systems. Here is what it changes for banks, clinics, and call centers deploying agents.
Enterprise AI Agent Spending Will Reach 206 Billion Dollars in 2026, but Most Companies Have Not Deployed One
Gartner expects AI agent software spending to reach 206.5 billion dollars in 2026, up 139 percent from 2025, yet only about 17 percent of companies have deployed agents and 40 percent of agentic projects may be canceled by 2027. The real work is deployment and governance, not the purchase.
Salesforce, Coupa and Asana Are Buying the AI Execution Layer
In five weeks, Salesforce, Coupa and Asana spent billions to own the layer where AI agents finish work instead of just suggesting it. Here is the pattern, and how to choose agent tools around it.
Enterprise AI Agents Start Working Together: Cognizant Links ServiceNow Agents to a Shared Orchestration Layer
Cognizant connected ServiceNow AI agents to its Neuro AI platform through the open MCP standard, a concrete sign that enterprise AI is shifting from isolated agents to governed, interoperable networks. Here is what it means for businesses adopting AI.
Why Enterprise AI Agents Keep Failing: The Memory Problem No One Is Solving
Your enterprise AI agent just closed a deal — and tomorrow it won't remember the client's name. The #1 reason Fortune 500 AI deployments stall isn't the model, it's memory architecture. Here's what KPMG, Microsoft, and Palantir aren't telling you.
Why Enterprise AI Agents Keep Failing: The Memory Problem Costing CTOs Millions
Your enterprise AI agent just forgot everything it learned last quarter. Every workflow optimization, every edge case it solved, every process nuance your team spent months teaching it — gone. This isn't a bug. It's the defining architectural flaw holding enterprise AI adoption back in 2026.
Why Enterprise AI Agents Fail in Production: The Context Layer Crisis CTOs Can't Ignore
Microsoft and VentureBeat are saying the same alarming thing this week: your AI agents aren't failing because the models are weak — they're failing because your enterprise data context is broken. Here's what that means for every CTO who already signed the deployment contract.
Enterprise AI Agents Are Creating Data Silos — And Your CISO Should Be Alarmed
Every AI agent your teams deploy to boost productivity is quietly building its own data kingdom. Microsoft just admitted it at Build 2026. Here's what enterprise security leaders need to do before the sprawl becomes a breach.
Why Enterprise AI Agents Keep Failing: The Memory Problem Killing ROI at Scale
Your enterprise AI agent just forgot everything it learned last week. That's not a bug — it's the architecture. And it's quietly destroying your AI ROI while your board waits for results.
Why Enterprise AI Deals Die in the Security Review: What CISOs Actually Block and Why
Databricks' co-founder said it plainly at Disrupt 2026: security and compliance reviews kill more enterprise AI deals than technical failures. A new risk report reveals AI risk is concentrated among a small group of power users — exactly the profile CISOs flag first. Here's the anatomy of a stalled AI deployment, and what separates the deals that close from the ones that don't.
Prompt Debt, Retrieval Debt, Evaluation Debt: The Hidden AI Technical Debt Silently Killing Enterprise ROI
Your enterprise AI deployment looks healthy on the dashboard — until it doesn't. A new class of technical debt is accumulating in the background of every RAG pipeline, every fine-tuned model, and every LLM integration your team shipped in the last 18 months. Unlike code debt, you can't see it in a git blame. But when it breaks, it breaks in production, in front of customers, and in front of your compliance team.
Why Enterprise AI Agents Fail in Production: The Memory Gap No One Talks About
You deployed the agent. It aced the demo. Six weeks later, it's confidently repeating mistakes it already made — because enterprise AI has a memory problem, and most vendors are selling you amnesia with a dashboard.