🤖 AI Summary
This study addresses the inefficiency of manual auditing in corporate governance and the challenges in validating automated alternatives by proposing a task replacement system within a Digital Governance Framework (DGF). Methodologically, it introduces a residual workload threshold as the criterion for task substitution, establishing an information sufficiency gating mechanism. Architecturally, the framework integrates intelligent agents, rule engines, and evidence services, automating auditing workflows through forward deployment engineering and constructing the DGF-Bench benchmark for multi-model evaluation. Experimental results demonstrate that models such as Gemini achieve success rates up to 94.98% under strict gating conditions, confirming the technical feasibility of automating specific governance tasks and offering an effective paradigm for enterprise digital governance.
📝 Abstract
Enterprise governance requires decisions, evidence, and accountable authority; it does not require every review task to retain its current human implementation. We develop a task-substitution framework for Digital Governance Frameworks (DGF), treating each gate as an executable contract. Substitution requires sufficient accessible information, valid decision and authority checks, and a reduction in total human work after exceptions, verification, correction, and maintenance are counted. We derive a residual-work threshold and show why automating most cases can still increase labor. Forward deployed engineering connects these conditions to an architecture for agents, rule engines, evidence services, and escalation. DGF-Bench supplies controlled evidence from 300 synthetic projects and 899 evaluable model-project runs. Gemini 3.8 Flash, GPT-5.6 Luna, and DeepSeek v4.1 Flash achieve strict gate success of 94.98%, 83.29%, and 74.18%; complete-route success is 76.92%, 42.33%, and 24.67%. A deterministic control passes all 1,700 gates given the supplied rules and structured facts, locating the comparison in execution of a supplied decision kernel. Evidence audits and 135 repeated runs distinguish correct decisions from reliable execution. A document counterexample establishes an information-sufficiency obstruction. These results support the technical feasibility of replacing human execution of specified governance-review tasks with agents and software. The framework specifies a workforce test based on the complete human effort required at fixed output and quality; the present measurements concern review performance. Sources, dossiers, traces, and analyses are public.