AI workflow governance

Define what an AI workflow may do—and who remains accountable.

A focused governance assessment for finance and risk sponsors considering AI assistance within a specific business process.

When to engage

There is a useful AI idea. Its operating boundaries remain unclear.

Start with one workflow, its intended business value, permitted information and consequences of an incorrect result. Define the evaluation and human oversight needed before broader use.

Suitable starting points include document-assisted research, evidence classification or decision-support drafting. The scope must establish which actions require accountable human review.

What you receive

A governed experiment your team can evaluate.

Workflow and value definitionDocument the task, sponsor, expected benefit, baseline and practical constraints.

Data and action boundariesSpecify authorised sources, access, permitted outputs and actions requiring approval.

Risk and control mapIdentify failure consequences, ownership, escalation, logs and review requirements.

Evaluation and operating planDefine test cases, evidence, acceptance criteria, human review and conditions for continued use.

Capability and ownership

Make accountability part of the workflow.

The sponsor, process owner, technology team and relevant control specialists agree responsibilities before implementation.

This is architecture and governance advisory. Applicable legal and regulatory obligations require review by the appropriate specialists; no certification or regulatory approval is implied.

Your next decision

Discuss a specific AI workflow.

Start with the decision you need to make. Scope, evidence requirements, responsibilities and fees are agreed after an introductory conversation.

Discuss your problem View sample outputs