Preparing Business Data and Workflows for AI Agents

Data readiness

Identify systems of record for customers, entities, invoices, approvals, and users.

Reduce duplicate master data where agents would otherwise invent conflicting “truths.”

Document retention and redaction rules before any model sees sensitive fields.

Workflow readiness

Map the prepare → review → approve path for each candidate process.

Name the human roles accountable for exceptions.

Decide which actions an agent may propose versus which require a hard stop.

Permission readiness

Agents should inherit role limits, not bypass them.

Separate service credentials from end-user authority.

Log prompts/tool calls that influence business actions when policy requires.

A staged adoption path

Start with read-and-prepare assistance on one workflow.

Measure reviewer edit rates and escalation frequency before expanding write capabilities.

Only then consider broader automation - still with human gates for finance-sensitive steps.

How this maps to Verion

Verion’s platform direction emphasizes shared workspace context, product modules, and Veda for human-approved preparation in supported pilots.

Availability still varies by product. Preparation work on your side remains valuable even before a full rollout.

Key takeaways

• Fix systems of record and roles before chasing agent demos.
• Design prepare/approve separation explicitly.
• Measure reviewer corrections as a readiness signal.
• Expand write access slowly and only where policy allows.