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Intelligence Brief
What's happening with AI in business: facts, primary sources, and named authors. In English, Russian, and Spanish.
Enterprise
62 articles
AI Voice Agent Compliance: A Prelaunch Checklist for US Small Businesses
A practical way to separate inbound answering, outbound telemarketing, call recording, disclosure, and escalation before an AI receptionist goes live.
OpenAI Launches Presence, a Managed Platform for Enterprise Voice and Chat Agents
OpenAI introduced Presence, an enterprise platform for voice and chat AI agents that is deployed by OpenAI engineers rather than sold as self-service. Early customers include BBVA Mexico, SoftBank and IAG. We break down the launch facts and what they mean for banks, clinics and call centers.
McKinsey: 60 Percent of AI Agent Costs Go to Refining Answers, Not Generating Them
A new McKinsey report says the next phase of enterprise AI will be decided by unit economics. About 60 percent of an agentic task's cost goes to verifying and refining answers, agent tasks can burn nearly 1,000 times more tokens than chat, and six distinct drivers shape the bill. Here is what that means in practice for teams putting agents into production.
An AI Agent Ran Lyzr's $100M Fundraise: What It Proves and What It Does Not
Lyzr pointed its own AI agent, SivaClaw, at its $100M Series B, drafting memos, answering 130+ investors, and tracking slide engagement. The round is still coming together. Here is what that actually proves for enterprises building agents.
Microsoft Puts $2.5 Billion Behind a New Company That Deploys AI for You
Microsoft announced the Frontier Company on July 2: a $2.5 billion unit with more than 6,000 engineers who will work inside customer organizations to build and run AI systems. It follows similar moves by Amazon, OpenAI and Anthropic, and it confirms that the hardest part of enterprise AI is no longer the model. It is the deployment.
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.