Exploring the impact of EU tendering operations on future AI governance and standards in pharmaceuticals

IF 6.7 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
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引用次数: 0

Abstract

This research examines the incorporation of artificial intelligence (AI) into the domain of tender management (TM) within the pharmaceutical industry, with a particular emphasis on operational efficiency, governance, and compliance with European regulatory standards. A comparative analysis of four companies—two that have adopted AI and two that have not—reveals significant discrepancies in the management of TM processes between AI-driven and traditional companies.
The study employs the Delphi method to ascertain expert consensus on eight critical areas of AI governance, including data privacy, transparency, and ethical AI use. The findings indicate that companies integrating AI demonstrate enhanced decision-making capabilities, accelerated processing times, and enhanced stakeholder engagement. However, they also encounter challenges pertaining to ethical governance and regulatory compliance.
The research highlights the necessity of aligning the adoption of AI with the latest European directives, such as the AI Act and General Data Protection Regulation (GDPR), to ensure both operational efficiency and adherence to ethical standards. The broader implications of the study underscore the necessity for pharmaceutical companies to develop robust governance frameworks, prioritize ethical considerations, and maintain regulatory compliance to fully leverage the potential of AI. Additionally, the study contributes to the ongoing scholarly discourse by providing empirical evidence on the interplay between AI, ethics, and governance, thereby encouraging further interdisciplinary research. This work emphasizes the critical role of strategic AI adoption in maintaining competitive advantage while safeguarding societal trust and adhering to legal requirements.
探索欧盟招标操作对未来人工智能治理和制药标准的影响
本研究探讨了将人工智能(AI)纳入制药业招标管理(TM)领域的情况,重点关注运营效率、管理以及是否符合欧洲监管标准。通过对四家公司(两家已采用人工智能,两家未采用)进行比较分析,发现人工智能驱动型公司与传统公司在招标管理流程管理方面存在显著差异。研究采用德尔菲法,以确定专家对人工智能管理八个关键领域的共识,包括数据隐私、透明度和人工智能的道德使用。研究结果表明,整合了人工智能的公司显示出了更强的决策能力、更快的处理时间和更高的利益相关者参与度。研究强调,采用人工智能必须符合最新的欧洲指令,如《人工智能法》和《通用数据保护条例》(GDPR),以确保运营效率和遵守道德标准。这项研究的广泛影响强调,制药公司有必要制定稳健的治理框架,优先考虑道德因素,并保持监管合规,以充分发挥人工智能的潜力。此外,这项研究还为当前的学术讨论提供了有关人工智能、伦理和治理之间相互作用的实证证据,从而鼓励了进一步的跨学科研究。这项工作强调了战略性采用人工智能在保持竞争优势、维护社会信任和遵守法律要求方面的关键作用。
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来源期刊
Computers & Industrial Engineering
Computers & Industrial Engineering 工程技术-工程:工业
CiteScore
12.70
自引率
12.70%
发文量
794
审稿时长
10.6 months
期刊介绍: Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.
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