Financial reporting, sustainability, and risk teams are accountable for work where the stakes are highest. Workiva AI is built for that reality. It works inside the same permissions and controls that govern the rest of your work on the platform.
This article covers three things: how Workiva governs an AI feature before and after it ships, how you verify and control what Workiva AI does in your workspace, and what evidence you have when an auditor asks. Each section describes what's available today and where the capability is headed.
Note: Items listed under "What's coming" describe the direction of this work, not commitments to specific features or delivery dates.
AI governance
AI governance is how Workiva confirms an AI feature is safe before it reaches your workspace, and keeps it that way after it ships. New AI features are tested against defined criteria and cleared through a governance checklist before they go live, so quality is confirmed rather than assumed.
These practices sit under Workiva's five Responsible AI principles: Accountability, Transparency, Fairness, Safety and Reliability, and Privacy and Security. The principles align with international standards including ISO/IEC 42001 and the NIST AI Risk Management Framework, and with regulations including the EU AI Act and GDPR. Read the principles in full in Workiva's approach to AI.
What's available today
- New AI features complete a governance checklist before they are turned on in production. The checklist documents the feature's purpose, its risk boundaries, the testing evidence behind it, how it's monitored, and who approved it.
- Release controls prevent a new AI feature from operating in production until the required governance steps are complete.
- AI features are tested against defined quality criteria using graded test sets, so response quality is measured before release.
What's coming
- A central internal record of every AI feature, covering ownership, release decisions, approvals, supporting evidence, and version history.
- Continuous evaluation that compares live responses against reference data sets, so quality is monitored after release and not only before it.
- Automatic re-evaluation when a model, prompt, tool, or workflow changes.
- Production monitoring for quality, failures, cost, and latency, with threshold alerts and regression detection.
AI verification and control
AI verification and control is how you check what Workiva AI produced and set what it's allowed to see and do. You can rely on an answer because you can prove it, not because it sounds right.
What's available today
- Responses cite their sources. Inline citation markers point back to the source, and you can hover a marker to see the document or knowledge base name and the section, or select it to open the source.
- A Sources list at the end of a response names the sources the response drew from, with a link to each one.
- Workiva AI works within the permissions you already have, down to the section level. Permissions are checked when Workiva AI retrieves content, so it can't retrieve or cite content you don't have access to.
- Actions that change your content require confirmation.
- You can stop a running workflow at any time by selecting Stop. The response records that you stopped it.
- A workflow can only use the tools it's been given, and it runs with the permissions of the person who runs it.
What's coming
- Section-level citations for referenced files.
- Citations that point to the exact span of text or the specific cell a claim came from.
- Derivation lineage for calculated figures, so you can trace a number back through each step rather than stopping at the first document.
- Confidence scoring on citations.
- Exportable citation sets you can hand to an auditor.
- Broader permissioning for multi-step workflows, bounding what a workflow can act on and not only what it can cite.
AI audit readiness
AI audit readiness means the record of where AI touched your work already exists, so you aren't reconstructing it afterward. It's built as you work.
What's available today
- Workiva AI grounds its answers in your own content rather than in general model knowledge alone. Grounding applies across use cases including tie-outs, Knowledge, benchmarking, and financial insights.
- AI interactions are recorded in the activity log, including the user, the interaction, and the model provider. Workspace admins can view these records.
- AI activity is governed by the same logging policy that already covers account access, data changes, and permission changes across the platform.
- Within a session, you can review the steps Workiva AI took. Select Show thinking to see its reasoning, the tools it called, and the actions it completed.
What's coming
- AI authorship in document history, so changes made by Workiva AI are attributable alongside human edits.
- Activity records that carry AI attribution through to downstream actions, connecting an AI interaction to the change it caused.
- Searchable AI activity history and detailed reconstruction of individual AI events.
- Human review evidence, tamper-evident records, evidence packages for auditors, and read-only auditor access.
This isn't a finished checklist. Workiva continues to raise the bar on governance, verification, and audit readiness as AI evolves.
Have questions about how this applies to your work? Contact us at security@workiva.com.