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Phase 1 · Bewusstsein AI agents · AI agents

Build and Adopt AI Agents With Confidence: Governance, Change and Scale

How to put governance, change management and measurement around AI agents so they are trusted and keep working after go-live.

← Agentic ERP & CRM
By Software Dynamics AI practice · 2 Nov 2026 · 8 min read Build and Adopt AI Agents With Confidence: Governance, Change and Scale

Die kurze Antwort

Confidence comes from design, not from the technology: clear ownership, approvals where the risk is, an audit trail, honest measurement and people who understand what the agent does. Build those in from the start and scaling is a series of small, evidence-based decisions.

Governance

  • Owner. One named person for each agent.
  • Permissions. The agent has only the access its job needs.
  • Approval. A person confirms any step that moves money, contacts a customer or changes master data, until measured results justify relaxing it.
  • Audit trail. What the agent read, decided and did is recorded.
  • Switch off. You can pause an agent immediately, and you know who may do it.

Change management

  • Explain what the agent will and will not do, to the people whose work changes.
  • Train reviewers on what good and bad output looks like.
  • Give staff a simple way to flag a wrong result.
  • Tell people what the freed time is for.

Measurement

Track the measures you agreed in the proof of concept, and add accuracy and exception rates. Review them monthly at first. Relax an approval only when the numbers justify it, and record who decided.

Scaling in stages

Stage What you do What you need before the next stage
Pilot One process, review of every action Accuracy and benefit at the agreed mark
Controlled live Same process, review by sample Stable exceptions and a named owner
Extend A second process or entity, same governance A reusable pattern for approvals and measures
Operieren Monitoring, improvement and updates for each release wave A regular review of the agent portfolio

Support after go-live

Microsoft updates its agents with each release wave, and your processes change. We offer review and support so that agents are tested against each release, instructions are adjusted and the benefit is checked. Book a consultation to plan the first agent and how it will be run.

Häufig gestellte Fragen

How do we govern AI agents?

Name an owner for each agent, give it only the access it needs, require approval for steps that move money or contact customers, keep an audit trail and keep a switch-off.

When can we relax approvals?

When measured accuracy over a period justifies it, and the decision is recorded.

What happens after go-live?

Agents are tested against each Microsoft release wave, instructions are adjusted and benefit is reviewed regularly.

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