Factors Influencing the Adoption of Artificial Intelligence (AI) Based Accounting System in Malaysian Organization: A Conceptual Paper
Why this work is in the frame
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Bibliographic record
Abstract
As technology rapidly changes, digital technology has been introduced to the accounting field, forcing businesses to adapt. The accounting profession is expected to embrace the new era of digitalization that will change traditional accounting practices. The roles of the accountants will shift to more challenging. Some of it predicted that this technology would take over the accountant's job, but the roles of accountants in this digital economy are still noteworthy. Amidst COVID-19, the transition to online operations is imperative for all businesses, compelling the accounting sector to embrace this technology alongside others. This study aims to discuss how artificial intelligence (AI) impacts the organization in Malaysia in this digital era. This research is anticipated to incorporate the reasons behind the organization's potential transition from conventional accounting methods to AI-driven accounting systems and analyze the resulting impact on the company's efficiency.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it