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The Relevance of AI-Driven Marketing Through Design Thinking for a Strategic Approach to Resilient Problem-Solving and Communication for SMEs

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  • Ioseb Gabelaia

    (Faculty of Business, Kauno Kolegija Higher Education Institution, LT-50468 Kaunas, Lithuania)

Abstract

SMEs often face challenges in optimizing their marketing strategies to achieve measurable and sustainable effectiveness in resource-constrained business environments. There is a limited knowledge how integrating the Design Thinking philosophy into AI-driven marketing strategies can generate resilient marketing results for SMEs. The purpose of this research is to explore how integrating DT philosophy can improve and sustain the effectiveness of AI-driven marketing campaigns for SMEs. The author used a qualitatively driven mixed-data case study approach to develop a comprehensive understanding integrating AI-driven marketing and DT. Data were collected through interviews, performance metrics analysis, and document review within three SMEs. The results revealed that incorporating the DT philosophy into AI-driven marketing strategies is associated with marketing effectiveness for SMEs. Additionally, SMEs adopting this integration achieve greater customer engagement and interaction. The combination of DT and AI-driven marketing observed higher improvements than traditional approaches. These results are challenged due to the potential risk of bias, and the qualitative nature may present challenges in convincing readers accustomed to definitive and statistical results.

Suggested Citation

  • Ioseb Gabelaia, 2025. "The Relevance of AI-Driven Marketing Through Design Thinking for a Strategic Approach to Resilient Problem-Solving and Communication for SMEs," Sustainability, MDPI, vol. 17(20), pages 1-21, October.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:20:p:8994-:d:1768608
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    References listed on IDEAS

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    1. Meinel, Martin & Eismann, Tobias T. & Baccarella, Christian V. & Fixson, Sebastian K. & Voigt, Kai-Ingo, 2020. "Does applying design thinking result in better new product concepts than a traditional innovation approach? An experimental comparison study," European Management Journal, Elsevier, vol. 38(4), pages 661-671.
    2. Nakata, Cheryl & Hwang, Jiyoung, 2020. "Design thinking for innovation: Composition, consequence, and contingency," Journal of Business Research, Elsevier, vol. 118(C), pages 117-128.
    3. Shepherd, Dean A. & Majchrzak, Ann, 2022. "Machines augmenting entrepreneurs: Opportunities (and threats) at the Nexus of artificial intelligence and entrepreneurship," Journal of Business Venturing, Elsevier, vol. 37(4).
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