W4401979750 Peer-reviewed research AI × management and organizations

How Does Artificial Intelligence Shape Audit Firms?

Kelvin K. F. Law · Michael Shen

Also recorded as: doi:10.1287/mnsc.2022.04040

Management Science

Recorded claims
1
coded from the inspected source
Evidence classes
1
crossref-api-metadata
Recorded limitations
4
stated, never hidden

From the hash-bound evidence releases

Recorded claims

Each claim states what the inspected source says, at the recorded location—bounded by its scope and graded by its confidence. Nothing here is a synthesis across works.

Evidence from U.S. audit-office adoption patterns and interviews with audit partners reports that AI use was associated with more auditor jobs, greater demand for soft skills, and more accurate audit opinions; investment was centralized while deployment decisions often remained local.

confidence: high crossref-api-metadata apw-c1-obot-journals

Scope: publisher-deposited abstract metadata; audit-firm employment, skills, organizational authority, and audit quality; study period is not stated

Structured relationships

In-corpus citations

Only source-supplied cites relationships whose two endpoints are admitted are shown. Invocation evidence remains a separate relationship.

Cites (0)

No in-corpus outgoing citation is available in the current enrichment coverage.

Cited by (1)

Boundaries

Limitations & independence

Recorded at coding time, carried with the work forever. A claim without its limits is not evidence.

Recorded limitations

  • Abstract-level Crossref metadata only; the blocked publisher surface was not retried.
  • The captured abstract does not state the empirical period or office denominator; numerical effect sizes are not carried forward.
  • Crossref supplies only a year and month for publication, so published_date is null rather than an invented day.
  • Full text was not inspected.

Source independence

publisher-only