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Integrating AI in a Swedish Public Procurement Setting: Identifying Factors Which Drive or Inhibit the Adoption of AI-Solutions in Public Procurement
KTH, Skolan för industriell teknik och management (ITM), Industriell ekonomi och organisation (Inst.).
KTH, Skolan för industriell teknik och management (ITM), Industriell ekonomi och organisation (Inst.).
2024 (Engelska)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsNo name for locale sv/1000Alternative title
OrganizationsIntegration av AI i svenska offentliga inköpsorganisationer
Abstract [en]

As the world becomes increasingly digitalized, new technologies like Artificial Intelligence (AI) are now more than ever before an important tool for organizations to meet future challenges. This is true for the private as well as the public sector, however, certain organizational functions are falling behind on AI-adoption, with public procurement being a standout example. This study examines the feasibility of integrating AI-solutions in public procurement. Using the theoretical lens of technology adoption and the AI-adapted Technology Organization Environment (TOE)-framework, a series of interviews were conducted with procurement practitioners, experts and solutions providers, identifying what factors drive or inhibit AI-adoption. The results confirmed that the previously identified TOE-factors relative advantage, management support, and external pressure are drivers of AI-adoption in public procurement, while competence, resources and procurement regulation are inhibitors. Additionally, three new factors were identified in the interviews; available solutions, resistance to change and public policy. The findings of the study contributed to the proposal of an updated TOE-framework for AI-adoption in public procurement. They further confirm the findings of previous studies utilizing the TOE-framework to investigate public organizations.

Abstract [sv]

I takt med att världen blir alltmer digitaliserad är nya teknologier som artificiell intelligens (AI) nu viktigare verktyg än någonsin för organisationers förmåga att bemöta framtida utmaningar. Detta gäller både den privata och den offentliga sektorn, men vissa organisatoriska funktioner ligger efter när det gäller AI-implementation, där den offentliga upphandlingsfunktionen är ett tydligt exempel. Denna studie undersöker möjligheterna att integrera AI-lösningar inom offentlig upphandling. Genom att använda organisationell teori om teknologiadoption som teoretisk lins och mer specifikt det AI-anpassade (TOE)-ramverket genomfördes en serie intervjuer med upphandlingspraktiker, experter och produktägare för att identifiera vilka faktorer som driver eller hämmar AI-implementation. Resultaten bekräftade att de tidigare identifierade TOE-faktorerna relativ fördel, ledningsstöd och extern press är drivkrafter för AI-implementation inom offentlig upphandling, medan kompetens, resurser och upphandlingsregler är hinder. Dessutom identifierades tre nya faktorer i intervjuerna; tillgängliga lösningar, motstånd mot förändring och offentlig styrning. Studiens resultat bidrog vidare till att föreslå ett uppdaterat TOE-ramverk för AI-implementation inom offentlig upphandling. Den bekräftar vidare resultaten från tidigare studier som använder TOE-ramverket för att undersöka teknikinförande inom offentliga organisationer.

Place, publisher, year, edition, pages
2024. , p. 60
Series
TRITA-ITM-EX ; 2024:104
Keywords [en]
Artificial Intelligence, Machine Learning, Natural Language Processing, Public Sector, Public Procurement, Technology Adoption, TOE-Framework, Drivers, Inhibitors
Keywords [sv]
Artificiell intelligens, Maskininlärning, Naturlig språkbehandling, Offentlig sektor, Offentlig upphandling, Teknikinförande, TOE-ramverket, drivare, inhibitorer
National Category
Identifiers
URN: urn:nbn:se:kth:diva-347788OAI: oai:DiVA.org:kth-347788DiVA, id: diva2:1870207
External cooperation
MTC Proc. Research Center
Subject / course
Industrial Economics and Management
Educational program
Master of Science - Industrial Engineering and Management
Presentation
2024-05-30, 00:00
Supervisors
Examiners
Available from: 2024-06-14 Created: 2024-06-14 Last updated: 2024-06-14Bibliographically approved

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