Researchers introduce Policy-as-Skill, a modular runtime that packages LLM-driven policy decisions with evidence validation, version control, and audit trails—achieving 53.8% exact accuracy on 600 ...
Research shows AI agents return inconsistent answers 38-74% of the time on repeated tasks—a critical failure for audit and compliance. Researchers propose "skill habit formation" to improve reliabi...
Researchers propose an agentic framework that autonomously generates Business Requirements Documents by reverse-engineering source code and configuration files, reducing manual work during system m...
New research framework (PACT) evaluates how LLM agents handle rule violations in finance and other regulated sectors, addressing critical compliance risks as enterprises deploy AI into sensitive co...
Academic paper argues audit independence for agentic AI systems must move beyond binary classification, introducing graded standards across principal, substrate, and evidence independence dimensions.
Researchers test whether detailed procedural traces in LLM audit loops make judges gullible; analysis of 4,551 compliance judgments shows error detection stays near ceiling despite trace variations.
Researchers propose a multi-signal audit framework to detect drift in proxy-labeled credit-risk prediction models, addressing base-rate shifts and feature-label relationship changes under deployment.
Researchers evaluate open-source large language models with retrieval-augmented generation for automating ESG KPI extraction from 498 real-world EU corporate reports, addressing a gap in domain-spe...
Academic paper models how a breach in shared AI vendors used for fraud detection and credit decisioning across banks could cascade into systemic financial contagion.
AICPA partners with ex-IRS Commissioner Danny Werfel to establish Council on AI Tax Risk, addressing information integrity and accountability as AI adoption in tax accelerates.
General-purpose AI systems fail to cite sources for tax and accounting advice, creating liability exposure under IRS Circular 230 requirements for practitioners to justify positions with specific s...
CPA Practice Advisor argues that rushed AI implementation creates adoption chaos—with enthusiasts moving fast while skeptical staff resist—requiring a deliberate behavioral design playbook to align...
Sovos explores how agentic AI addresses the persistent gap between finance automation and tax compliance, tackling ERP limitations and regulatory complexity that have plagued enterprises for 20+ ye...
Deloitte's June 2026 ASC 606 guidance on outcome-based pricing for agentic AI SaaS is forcing controllers and revenue accounting leaders to rethink revenue recognition as vendors shift to per-resul...
LogicGate argues that "vibe coding" GRC systems with isolated AI prompts creates compliance chaos; enterprises need integrated platforms with governed AI agents and proven audit trails.
AuditBoard explores how Chief Audit Executives must adapt internal controls, guard against "agent washing," and upskill teams as AI agents reshape audit practices.
AppZen's agentic AI automates indirect tax recovery in travel and expense workflows, reducing manual auditing and preventing tax compliance leakage through intelligent expense categorization.
AICPA pushes back on IRS guidelines requiring tax practitioners to pass AI savings to clients, citing implementation costs and value-pricing concerns.
OntoKG-EQ addresses the audit and reproducibility crisis in equity analysis by replacing ad-hoc spreadsheets with a provenance-grounded knowledge graph that links analyst queries to evidence, times...
Auditoria.AI explores how autonomous AI systems are evolving finance beyond passive record-keeping and dashboards toward active decision-making and transaction execution, requiring new safety archi...