Investors and corporate finance chiefs hold competing views on whether a two-decade-old financial data standard still has a future — and artificial intelligence is making the question harder to ignore.
That divide emerged at a recent meeting of the Financial Accounting Standards Advisory Council, a body of advisers to the FASB, where investors and corporate finance chiefs weighed in on whether eXtensible Business Reporting Language (XBRL) — the structured tagging system baked into every major company filing — is an indispensable tool or an expensive relic waiting to be replaced by AI.
The answer, depending on who was talking, was both.
“XBRL would be far more accurate to retrieve the data,” said Yin Luo, vice chairman at Wolfe Research, arguing that precisely tagged data lets investors zero in on exact figures instead of relying on AI to interpret broad swaths of text. He went further, saying investors not only want to keep it — they want it made more uniform across every company that files.
Joe Holmes, chief accounting officer at Thermo Fisher Scientific, raised a longer-term concern. “I remember from last year the question was whether it’s become old tech,” Holmes said. “And I think eventually the answer to that question will be yes.” With XBRL tagging costing companies real money and time, Holmes argued there will eventually be a hard cutoff where the math simply stops working.
FASB Chair Richard Jones offered a telling data point. He told the group that a large investment firm had come in and demonstrated an internal tool that pulls and compiles financial data without touching XBRL at all — suggesting that for some sophisticated players, the workaround is already here.
That is a striking development for a standard that has been mandatory for nearly 20 years. The SEC launched a voluntary XBRL program in 2005, made it mandatory in 2009, and in 2018 tightened the rules further by requiring Inline XBRL — a format readable by both humans and machines. This is not experimental technology. It is the backbone of how corporate America has reported its numbers for a generation.
But the rise of AI is now putting that backbone under pressure. The two technologies work in fundamentally different ways. XBRL functions like a barcode — a human deliberately tags a specific data point so a machine can retrieve it with precision. AI does the opposite, reading raw unstructured text and pulling meaning from context without any labels at all. For years XBRL was the only reliable way to get a machine to read financial data accurately. Now it has a rival.
Daniel Murdock, chief accounting officer at Comcast, put the question plainly: in a world where AI can read unstructured filings directly, are companies and investors even using XBRL the same way anymore?
Luo said investors want to keep it. From an investor’s perspective, he said, “there’s a strong desire to continue to have it” — and what would make it even more valuable is requiring every company to follow exactly the same tagging process, something that does not currently exist.
That is the central tension the March 10 meeting laid bare. Investors see AI making it easier than ever to consume vast volumes of financial information and still want the precision that structured tagging delivers. Corporate preparers are increasingly asking whether a smarter AI might eventually do the same job without the cost and burden of tagging every data point by hand.
For now, XBRL has strong defenders. But as AI gets more powerful, the pressure to justify its cost may grow.
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