Leveraging AI in Marketing: Financial Outcomes and Practical Applications
2025 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE credits
Student thesis
Abstract [en]
In recent years, artificial intelligence (AI) has become a transformative force in the field of marketing. From content creation to campaign optimization and marketing efficiency, AI technologies are reshaping how businesses conduct marketing practices. Despite growing adoption, there is limited understanding of how AI-driven marketing is applied in practice and how it influences financial performance. This thesis explores how businesses utilize AI in marketing activities and evaluates its financial outcomes. The goal is to identify the types of AI tools used, their strategic integration across marketing functions, and their impact on businesses' finances. The study adopts a qualitative, exploratory approach rooted in a critical realist research philosophy. Using purposive sampling, semi-structured interviews served as the primary data source, conducted with three senior marketing professionals from different organizational contexts. Thematic analysis was applied to identify recurring patterns in the data, complemented by financial observations from secondary sources. The findings reveal that AI is deeply embedded in modern marketing operations, driving improvements in various marketing areas. Participants consistently reported measurable financial benefits, including cost reductions, improved conversion rates, and enhanced return on investment. However, challenges remain regarding ethical concerns, transparency, and integration complexity. The study contributes practical insights for businesses considering AI adoption and advances understanding of the strategic value AI brings to marketing performance.
Place, publisher, year, edition, pages
2025. , p. 72
Keywords [en]
Marketing, Artificial Intelligence, Financial performance, Acceptance Model (TAM), Resource Based View (RBV)
National Category
Business Administration
Identifiers
URN: urn:nbn:se:hj:diva-68035OAI: oai:DiVA.org:hj-68035DiVA, id: diva2:1963116
Subject / course
JIBS, Business Administration
Supervisors
Examiners
2025-06-242025-06-022025-10-13Bibliographically approved