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

dc.contributor.authorPesqueira, A.
dc.contributor.authorMachado, A. de. B.
dc.contributor.authorBolog, S.
dc.contributor.authorSousa, M. J.
dc.contributor.authorPereira, R.
dc.date.accessioned2024-10-25T10:00:44Z
dc.date.available2024-10-25T10:00:44Z
dc.date.issued2024
dc.date.updated2024-10-25T10:58:11Z
dc.description.abstractThis 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.eng
dc.description.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.citationPesqueira, A., Machado, A. de. B., Bolog, S., Sousa, M. J., & Pereira, R. (2024). Exploring the impact of EU tendering operations on future AI governance and standards in pharmaceuticals. Computers and Industrial Engineering, 198, Article 110655. https://doi.org/10.1016/j.cie.2024.110655
dc.identifier.doi10.1016/j.cie.2024.110655
dc.identifier.issn0360-8352
dc.identifier.urihttp://hdl.handle.net/10071/32543
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier
dc.rightsopen access
dc.subjectArtificial Intelligence (AI)eng
dc.subjectPharmaceutical industryeng
dc.subjectTender Management (TM)eng
dc.subjectGovernanceeng
dc.subjectEthicseng
dc.subjectOperational efficiencyeng
dc.titleExploring the impact of EU tendering operations on future AI governance and standards in pharmaceuticalseng
dc.typearticle
dc.volume198
dspace.entity.typePublicationen
iscte.identifier.cienciahttps://ciencia.iscte-iul.pt/id/ci-pub-106163
iscte.journalComputers and Industrial Engineering

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