An Integrated Ethical Governance Framework for AI-Driven Business Decision-Making: AIIA, Explainable AI Contracts, Ethics-By-Design, and Algorithmic Sustainability Indices

Existing AI regulatory frameworks, including the EU AI Act, the General Data Protection Regulation (GDPR), and industry standards such as IEEE Ethically Aligned Design and ISO/IEC 42001, have demonstrated structural inadequacy in preventing ethical failures arising from AI-driven business decision-making. Responding to these documented deficiencies, this paper proposes and evaluates an Integrated Ethical AI Governance Framework (IEAGF) comprising four novel, complementary mechanisms: (1) Pre-Deployment AI Impact Assessments (AIIA), which mandate bias auditing, fairness evaluation, and stakeholder impact mapping before system deployment; (2) Explainable AI with Algorithmic Contracts (XAI-AC), which legally bind AI systems to defined behavioural parameters and transparency obligations; (3) Ethics-by-Design (EbD) Frameworks, which embed ethical principles, fairness constraints, and stakeholder inclusivity into AI development lifecycles; and (4) Algorithmic Sustainability Indices (ASI), which introduce standardised metrics for quantifying the energy consumption, socioeconomic impact, and renewable infrastructure usage of AI deployments. The IEAGF is evaluated against established practicability criteria across sectors including finance, healthcare, and logistics. Feasibility analysis demonstrates that the framework is implementable across organisational scales, aligns with existing ESG disclosure obligations, and provides regulators with enforceable technical benchmarks absent from current frameworks. The IEAGF represents a shift from reactive compliance to preventive ethical governance, grounded in both technical operationalisability and institutional accountability.

AI governance, ethics-by-design, explainable AI, AI impact assessment, algorithmic sustainability, GDPR, ESG, ethical AI, algorithmic contracts, responsible AI deployment

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