Workiva warns weak governance is slowing AI reporting

Workiva has published commentary arguing that weak data governance is holding back the use of AI in corporate reporting in Australia, citing survey findings from Australian finance, risk and sustainability leaders.

According to the company, 95 per cent of respondents expect measurable return on investment from AI within a year, yet only 14 per cent believe their organisation's data quality is sufficient for AI use in reporting.

A further 21 per cent said data quality issues had significantly limited their use of AI in reporting workflows, while 44 per cent had worked around such issues despite the drag on progress.

Kristen "KP" Pimpini, Vice President and General Manager, APJ, at Workiva, said the gap should not be seen simply as a data problem.

"It's tempting to read those numbers as a data problem. I'd argue it's a governance problem wearing a data costume," Pimpini said.

She argued that AI does not solve inconsistency in reporting processes where the same figure appears across multiple spreadsheets, presentations and email chains. Instead, the technology can spread mistakes more quickly and make them harder to detect because the output appears assured.

The survey also found that 79 per cent of respondents were at least somewhat confident in the accuracy of AI outputs without human review, a result Workiva said underscored the risk of relying on systems built on fragmented information.

Reporting risks

Pimpini said organisations that know they are blocked by data issues may be in a safer position than those relying on manual fixes. She pointed to reconciliations, offline copies and dependence on individual staff knowledge as practices that may keep work moving in the short term but weaken traceability over time.

That matters in reporting functions because companies must be able to explain where figures come from in financial statements, board papers and sustainability disclosures. In Australia, mandatory climate reporting is being introduced, increasing scrutiny of how reported information is assembled and verified.

"A number you can't trace is a number you can't defend, meaning an AI-assisted process that can't be audited turns a productivity gain into a liability," Pimpini said.

Three elements

Workiva said organisations looking to make AI useful in reporting should focus on a connected, controlled data environment rather than simply seeking better models or new software.

It identified three necessary elements: a single source of truth so each figure exists in one place and updates flow through all related reports; control through ownership, permissions and version history; and built-in data lineage so figures can be traced quickly to their source.

Pimpini said those foundations would allow teams to use AI for tasks such as drafting commentary, flagging anomalies and reconciling data, while preserving the ability to verify every step.

Workiva also pointed to governance weaknesses at companies that already describe themselves as prepared for AI use. The survey found that 39 per cent of Australian executives said their most recent AI audit uncovered data lineage gaps or traceability issues.

AI-ready test

Pimpini set out a practical test for finance and reporting teams: take one AI-assisted figure from a recent board report and try to trace it back to its source. If the answer takes days to find, depends on a spreadsheet understood by one person, or relies on memory, the organisation is not ready, she said.

"Take one AI-assisted figure from your last board report and ask your team to trace it back to its source. If getting an answer takes days, relies on a spreadsheet only one person understands, or depends on someone's memory, you're not AI-ready. You're exposed," Pimpini said.

The argument reflects a broader debate in corporate technology spending, where pressure to show quick returns from AI is colliding with older problems in financial reporting, internal controls and accountability. Rather than treating AI as a separate layer added to existing systems, the commentary suggests businesses may need to address long-standing weaknesses in how they manage and verify data.

"Organisations that are genuinely AI-ready can show evidence. It's what gives teams confidence in their work, business leaders confidence in their decisions and reporting, and boards confidence to invest in AI as a real advantage," Pimpini said.