Systematic technical analysis: Enhancing AI deployment in procurement for optimal transparency and accountability

Amaka Justina Obinna 1, * and Azeez Jason Kess-Momoh 2

1 Independent Researcher, Atlanta, Georgia. USA.
2 Ama Zuma Oil & Gas, Lagos, Nigeria.
 
Review Article
Global Journal of Engineering and Technology Advances, 2024, 19(01), 192–206.
Article DOI: 10.30574/gjeta.2024.19.1.0067
Publication history: 
Received on 13 March 2024; revised on 20 April 2024; accepted on 23 April 2024
 
Abstract: 
In today's rapidly evolving business landscape, the integration of Artificial Intelligence (AI) in procurement processes holds significant promise for improving transparency and accountability. This systematic technical analysis explores the implications of AI deployment in procurement and its potential to enhance transparency and accountability within organizations. The study adopts a mixed-methods approach, combining quantitative surveys and qualitative interviews to gather comprehensive data on the use of AI in procurement, legal and ethical challenges faced by organizations, and the effectiveness of current legal and ethical frameworks. Quantitative surveys are distributed to a diverse sample of organizations to assess the extent of AI use in procurement, perceived impacts on legal and ethical frameworks, and overall satisfaction with AI deployment. Qualitative interviews with key stakeholders, including procurement managers and legal advisors, provide deeper insights into the nuances of AI deployment and its implications for transparency and accountability. The analysis of quantitative data reveals the prevalence of AI use in procurement processes and its perceived impact on legal and ethical frameworks. Organizations report improvements in contract management, risk reduction, and compliance with regulations due to AI deployment. However, concerns remain regarding the legal implications of AI decision-making and the need for robust ethical frameworks to ensure accountability. Qualitative interviews shed light on the practical challenges and opportunities associated with AI deployment in procurement. Stakeholders highlight the importance of transparency, fairness, and human oversight in AI-driven processes. They emphasize the need for clear ethical guidelines and oversight mechanisms to address potential biases and ensure accountability. Overall, this systematic technical analysis provides valuable insights into the implications of AI deployment in procurement for transparency and accountability. The findings underscore the importance of integrating AI-related training and education into procurement processes and developing robust legal and ethical frameworks to mitigate risks and ensure responsible AI deployment.
 
Keywords: 
Systematic; Technical Analysis; Al Deployment; Procurement; Optimal Transparency
 
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