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Demonstrating Potential: A Study About Acceptance of AI Technology
KTH, School of Industrial Engineering and Management (ITM).
KTH, School of Industrial Engineering and Management (ITM).
2024 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Demonstrera potential : En studie om acceptans av AI-teknologi (Swedish)
Abstract [en]

Digital transformation is crucial for maintaining competitiveness, however, it presents significant challenges for established manufacturing companies. This study investigated challenges associated with adopting AI technology to enhance automation within aleadingglobal industrial manufacturer. Utilizing the Technology Acceptance Model (TAM) and a demonstrator concept, the research examines both organizational and technological factors that influence AI acceptance.

A mixed-method approach was employed, incorporating empirical data collection through semi-structured interviews with internal employees, representatives from external companies, and academic experts, analyzed via thematic analysis. Additionally, a literature review was conducted. The primary challenges identified include data management, resistance to change, organizational inertia, and the need for effective communication and training. The findings indicate that demonstrators can mitigate resistance and boost user engagement.

The study extends the TAM model by adding a new dimension that includes a demonstrator to address the identified challenges. These results underscore the importance of addressing both technical and cultural barriers to achieve successful digital transformation.

Abstract [sv]

Digital transformation är avgörande för att bibehålla konkurrenskraften, men det innebär betydande utmaningar för etablerade tillverkningsföretag. Denna studie undersökte utmaningar som är förknippade med att implementera AI-teknologi för ökad automation inom en globalt ledande lastbilstillverkare. Genom att använda Technology Acceptance Model (TAM) tillsammans med en konceptuell demonstrator undersöker studien både organisatoriska och teknologiska faktorer som påverkar hur AI accepteras.

Forskningsmetoden inkluderade empirisk datainsamling genom semi-strukturerade intervjuer med interna medarbetare, externa företag och akademiska experter och insamladdata analyserades genom tematisk analys tillsammans med en genomgång av tidigare publicerad litteratur. De huvudsakliga utmaningarna som identifierades var datahantering, motstånd mot förändring, organisatorisk tröghet och behovet av effektiv kommunikation och utbildning. Resultaten indikerar att en demonstrator kan minska motstånd och öka användarengagemanget.

Studien utvidgar även TAM-modellen för att bättre hantera de identifierade utmaningarna genom att lägga till en ny dimension som inkluderar en demonstrator. Detta resultat framhäver vikten av att belysa både tekniska och kulturella hinder för en framgångsrik digital transformation.

Place, publisher, year, edition, pages
2024. , p. 79
Series
TRITA-ITM-EX ; 2024:347
Keywords [en]
Digital Transformation, Automation, Technology Acceptance Model (TAM), Artificial Intelligence (AI), Demonstrator, Manufacturing
Keywords [sv]
Digital Transformation, Automation, Technology Acceptance Model (TAM), Artificiell Intelligens (AI), Demonstrator, Tillverkning
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-353320OAI: oai:DiVA.org:kth-353320DiVA, id: diva2:1898254
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Examiners
Available from: 2024-09-17 Created: 2024-09-17 Last updated: 2024-09-17Bibliographically approved

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CiteExportLink to record
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