Topic

Agentic AI

How enterprises design, govern and scale AI agents that plan, reason and act.

Agentic AI

Mission-Critical AI Agents: The Architecture That Gets Them to Production

Most AI agent prototypes never become trusted production systems. LangChain Deployed Engineer Christine Manegan says the teams that succeed own their intelligence, from models and harness to evals and governance, and describes how an agent harness manages context, sub-agents and human-in-the-loop controls.

By The AI Enterprise Magazine Team ·

Agentic AI

AI Agent Sprawl: Why Enterprises Need an Agentic Control Plane

Building an AI agent is easy; running thousands of them is not. IBM's Ann Leach says agent sprawl creates security and cost risk, lists five questions an agentic control plane must answer and describes how Starlink coordinated procurement agents.

By The AI Enterprise Magazine Team ·

Security & Fraud

AI Agent Overreach: Why Enterprises Need Context-Based Controls

AI agents will overreach, and traditional security controls weren't built for probabilistic software, says Rubrik's Cal Al-Dhubaib. He offers real examples of agent overreach, a three-part model of context-based control and three questions every team should ask before AI fails.

By The AI Enterprise Magazine Team ·

Agentic AI

From Automation to Autonomy: Trusted Agentic AI Controls for Banks

Banks are using AI to rerun fixed chatbot workflows, not to act autonomously, according to Midships CEO Ajit Gupta. Checking each agent's purpose, objective, plan and API call, with signed human approvals, can keep autonomous agents on track, he says.

By The AI Enterprise Magazine Team ·

Agentic AI

Agentic AI in the Enterprise: From Human in the Loop to Agent Ops

Leaders from Revefi, Rhino Federated Computing, Precisely, AtScale and Google Cloud define what makes AI truly agentic and argue human review won't scale. Their alternative: human-on-the-loop oversight, two-tier governance, agents that govern agents and the rise of agent ops.

By The AI Enterprise Magazine Team ·

Agentic AI

Agentic Data Management: How AI Agents Let Analysts Self-Serve Data

Agentic data management pays off most for the analysts, data scientists and leaders stuck in the data team's queue, Matillion's field engineering team argues. Its Maia agent offers self-service pipeline building, permission prompts, context files that enforce standards and AI-driven troubleshooting.

By The AI Enterprise Magazine Team ·

Agentic AI

Five Questions Enterprises Must Answer to Scale Agentic AI, per IBM

IBM's Ryan Zombo lays out five questions enterprises must answer to move agentic AI into production, from avoiding agent sprawl to avoiding lock-in. Governance works like brakes on a race car, he argues, citing productivity results from IBM's internal client zero program.

By The AI Enterprise Magazine Team ·

Agentic AI

Custom MCP Servers and the Composable, Agentic Enterprise Platform

No one is closer to enterprise data than the integration platform, argues SnapLogic Senior Solutions Engineer Dylan Vetter. He explains how IT teams can share governed integration assets across business units and build custom MCP servers that connect LLMs to company data.

By The AI Enterprise Magazine Team ·

Agentic AI

From A2A to MCP: How Seven Vendors Are Giving AI Agents Business Context

Snowflake, Denodo, Zenlytic, PromptQL, Fivetran, Google Cloud and Precisely are attacking the same problem from different angles: conversational agents, logical data layers, verified metrics, confidence signaling, fresh pipelines, the Agent2Agent protocol and location data through MCP.

By The AI Enterprise Magazine Team ·