Making Sense of AI in B2B Strategic Positioning

Sammanfattning

Title: Making Sense of AI in B2B Strategic Positioning Date of Seminar: 2026-06-04 Authors: Noor Essaidi & William Eriksson Advisor: Mats Urde Key words: Artificial Intelligence, Strategic Positioning, B2B, Value Proposition, Differentiation, Sensemaking Purpose: The purpose of the study is to explore how professionals in B2B firms use, evaluate and make sense of AI in strategic positioning work. Methodology: A qualitative research strategy with an abductive approach was used. The primary data was collected from 14 semi-structured interviews with professionals representing established B2B firms across different industries, analyzed through a thematic analysis. Theoretical Perspective: The study primarily applies Weick’s Sensemaking Model to analyze how professionals interpret, enact, select, and retain meanings around AI in strategic positioning work. Porter’s Generic Strategies is used as a complementary lens to analyze tensions between efficiency, cost, differentiation, and strategic positioning. Empirical Data: The empirical data consists of semi-structured interviews with professionals from 13 established B2B firms across several industries. These include professional services, software, market research, logistics, pharmaceutical, architecture, real estate, industrial security, industrial engines, advertising, and packaging solutions. Originality: The originality of this study lies in the focus of how B2B firms use and make sense of AI. This study provides insights about AI, not only as an operational tool but also in relation to value proposition, differentiation and strategic positioning. Conclusions: The study concludes that AI mainly strengthens and extends existing value propositions rather than replacing firms' strategic positioning. As AI becomes more common, differentiation appears to depend less on having AI and more on how firms combine AI with human judgement, customer understanding and firm-specific strengths.