Digital Procurement 4.0: Redesigning Government Contracting Systems with AI-Driven Ethics, Compliance, and Performance Optimization
DOI:
https://doi.org/10.32628/CSEIT24102138Keywords:
Digital Procurement 4.0, AI in Government Contracting, Ethical Procurement, Compliance Optimization, Public Sector Innovation, Automated Bidding, Vendor Performance Analytics, Predictive Compliance, Procurement Transparency, Contracting System ReformAbstract
The advent of Digital Procurement 4.0 marks a transformative shift in government contracting systems, integrating artificial intelligence (AI), data analytics, and automation to enhance transparency, efficiency, and ethical compliance. This study explores the redesign of public procurement frameworks using AI-driven models that ensure not only cost-effectiveness but also adherence to legal, ethical, and performance standards. Traditional procurement systems often grapple with inefficiencies, corruption, lack of accountability, and delayed service delivery. Digital Procurement 4.0 presents an opportunity to counter these limitations through predictive analytics, blockchain-based audit trails, robotic process automation (RPA), and intelligent contract management systems. This paper proposes a comprehensive AI-driven framework that embeds real-time risk detection, compliance verification, vendor performance monitoring, and ethical safeguards throughout the procurement lifecycle. By integrating natural language processing (NLP) for contract analysis, machine learning algorithms for bid evaluation, and automated compliance checkers, governments can ensure fairness, reduce fraud, and promote value-for-money outcomes. Moreover, digital twin technologies enable simulations that forecast procurement outcomes under varying socio-economic scenarios, thus enhancing strategic decision-making. The research draws on recent case studies from digitally advanced governments, demonstrating how AI integration has improved procurement efficiency by up to 45%, reduced fraud incidences by 30%, and enhanced stakeholder trust. Additionally, the study outlines a regulatory and governance blueprint to mitigate algorithmic bias and ensure accountability in AI-led procurement systems. Particular emphasis is placed on ethical algorithm design, data transparency, and participatory oversight mechanisms involving civil society and independent watchdogs. Ultimately, this paper underscores the national importance of adopting Digital Procurement 4.0 in public sector governance. As public expenditure accounts for over 12% of global GDP, optimizing this function through technology has widespread implications for fiscal sustainability, public trust, and socio-economic development. This research offers policy recommendations, implementation strategies, and a roadmap for governments aiming to build ethical, efficient, and AI-enabled contracting ecosystems.
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