AI agents in business: governance for measurable returns
Kyndryl is launching a service for managing AI agents, aiming to help companies get a better payoff from their AI investments. CEO Martin Schroeter is betting on proper oversight: businesses need more than new models, he argues. They also need clear rules, metrics and observability. Without them, even useful agents quickly run into risk, unclear costs and scaling problems inside large teams.
AI-processed from Bloomberg Tech; edited by Hamidun News
Companies that deploy AI agents in their workflows need to build a control system if those investments are to deliver measurable returns.
Why do companies need control over AI agents?
According to Kyndryl CEO Martin Schroeter, businesses need more than just access to AI. They need a clear control mechanism so that these systems deliver measurable returns.
What is AI agent governance?
It is a control mechanism that helps companies get measurable returns from AI investments embedded in their workflows.
Why is control needed when deploying AI?
So that a business does not merely get access to AI agents, but understands the effectiveness and payback of its spending on the technology.
Why does business need control over AI agents?
According to Kyndryl's leadership, companies need more than just access to AI. They need a clear control mechanism so that these systems deliver measurable returns.
Where is the enterprise AI market heading?
The enterprise market is gradually shifting from experiments with individual models to the infrastructure built around them.
Why do AI agents need a management and control system?
So that a business can get a measurable return on its investment: a control system provides a clear mechanism for managing AI agents in workflows.
How are companies moving from AI experiments to full-scale deployment?
The enterprise market is shifting from experiments with individual models to building the infrastructure around them, which lets companies manage agents more effectively.
- Oct 31, 2026Author puts his script before an AI jury: the verdict cost 850 thousand tokens
- Oct 29, 2026OvisOCR3: an 0.8B-parameter model that reads documents better than specialized systems
- Oct 29, 2026Tencent releases Youtu-Parsing-Omni: one model parses documents, audio and video
- Oct 28, 2026Liquid AI releases LFM2.5-24B-A2B: an agent model with 2B active parameters
Key Questions Answered
Why do companies need control over AI agents?
According to Kyndryl CEO Martin Schroeter, businesses need more than just access to AI. They need a clear control mechanism so that these systems deliver measurable returns.
What is AI agent governance?
It is a control mechanism that helps companies get measurable returns from AI investments embedded in their workflows.
Why is control needed when deploying AI?
So that a business does not merely get access to AI agents, but understands the effectiveness and payback of its spending on the technology.
Why does business need control over AI agents?
According to Kyndryl's leadership, companies need more than just access to AI. They need a clear control mechanism so that these systems deliver measurable returns.
Test Frontier LLMs & Autonomous Agents in One Workspace
Run Claude Opus 5.5, GPT-6, Gemini 3.1, and DeepSeek side-by-side in Nomad AI (nomadnet.ai) — unified model routing, deep research, and multimodal workflows under one subscription.
The AI world, distilled — once a week
Seven stories that actually mattered, hand-picked. No noise, no reposts, no press releases.
Done! Check your inbox for a confirmation.