From “audit machines” to tech‐savvy auditors: Auditors' quest for professional security with respect to digital transformation
Bibliographic record
Abstract
Abstract In recent years, the Big 4 firms have embarked on digital transformation projects that have the potential to throw auditors' daily practice into turmoil. This study looks at the auditors' quest for professional security—namely, their confidence in the fundamental features of their profession. Specifically, we investigate how auditors, when construing their experiences in a firm engaged in a digital transformation project promoting automation of a significant portion of their work, seek to preserve their sense of professional security. Interviews with auditors indicate that, in contrast to the high professional insecurity caused by the commercialization of auditing in the early 2000s, the digital transformation of the profession ultimately strengthened auditors' professional security. Over time, the interviewees became receptive to the firm‐promoted label of tech‐savvy auditor and subscribed to the technological complementarity thesis, which sees closer “collaboration” with technology as enhancing the auditor's work rather than replacing, undermining, or enslaving the auditor. Three implications are discussed. First, our study casts doubt on auditors' romanticized view of the technological complementarity thesis in light of economic and socio‐organizational theories about the automation of work. These theories lead us to question the auditors' belief that they will retain their professional autonomy. Second, according to our analyses, one key explanation for auditors' high level of professional security is that digital transformation projects surrounding the audit function are part of a continuing and reassuring trajectory of commercialization within accountancy. Third, our findings suggest that digital transformation projects act as vehicles for identity development, allowing the tech‐savvy auditor to escape the shameful stereotypes ascribed to the traditional auditor—that is, an auditor who manually performs most of the mundane tasks required to complete an audit.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".