As financial organizations rush to incorporate AI into reporting processes, the need for robust controls and data quality has never been greater. Workiva’s research reveals an optimistic executive mindset on AI trust, but warns of operational risks without established safeguards.
- 84% of executives trusting AI for reports signals confidence ahead of readiness
- Only 11% rate their data quality sufficient for reliable AI use
- Human approval continues as essential for financial statement responsibility
What happened
Workiva Inc. has identified a growing trend where executives are increasingly willing to rely on AI to generate financial reports, with 84% expressing some degree of trust in AI outputs without mandatory human review. This development reflects an eagerness to leverage AI for automation within finance departments, aiming to increase speed and efficiency.
However, Workiva’s insights also reveal a significant gap in operational readiness among organizations, particularly concerning underlying data quality and governance controls. Despite pressure to adopt AI rapidly, many finance teams lack the necessary frameworks to ensure AI-generated reports are accurate and fully accountable.
Why it matters
The incorporation of AI in financial reporting introduces a nuanced risk profile that mirrors traditional risks but in new forms. When AI-generated data is unchecked or built on low-quality inputs, it can propagate errors more quickly and obscure the audit trail, undermining both internal controls and external compliance.
Financial executives remain ultimately accountable for reports presented to stakeholders, meaning human oversight cannot be sidelined. Responsible AI use demands that established controls—such as tracking data origin, documenting processing steps, and final human signoff—remain embedded in the workflow to prevent costly control failures.
What to watch next
Moving forward, organizations will need to prioritize improving the quality and governance of financial data to safely scale AI applications. Workiva’s findings that only 11% of executives currently deem their data fit for AI use highlight a large opportunity for targeted data management and cleansing initiatives.
Simultaneously, firms should develop and reinforce operational controls tailored to AI-generated outputs, ensuring that automation complements rather than replaces vital human judgment. The balance between speed and risk mitigation will be critical as AI becomes a standard component of financial reporting.