Designing a model for the transformation of B2B marketing strategies based on artificial intelligence in small and medium-sized companies

Document Type : Original Article (Qualitative)

Authors

1 Master, Department of Management, Znjan Branch , Islamic Azad University, Znjan, Iran.

2 PhD in Business Administration, Department of Business Administration, Science and Research Branch, Islamic Azad University, Tehran, Iran.

3 PhD student, Department of Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.

4 Assistant Professor of Management Department, Takestan Institute of Higher Education, Qazvin, Iran.

Abstract
the purpose of this study was to analyze the role of artificial intelligence in the evolution of b2b strategies and to explain its consequences in small and medium - sized enterprises .this study was applied in terms of purpose and was designed based on a qualitative approach based on داده‌بنیاد 's strategy .data were collected through semi - structured interviews with 15 marketing managers , experts of artificial intelligence and sales strategists who had lived experience in applying smart technologies .data analysis was performed in three stages : open , axial and selective coding using MAXQDA software .the results showed that causal factors , including necessity of analysis of large competitive data , change in decision - making patterns of organizational purchasers and pressure to reduce marketing costs have a key role in the beginning of this evolution .contextual factors include digital maturity of the organization and the quality of data infrastructure provide the necessary tools for successful implementation of intelligent marketing , while financial resources limitation , technical complexity and resistance of traditional sales experts act as confounding factors .according to the results , adopting strategies such as deployment of smart metering systems , پیش‌بینانه analysis and content automation can improve outcomes such as rate of return , loyalty of key customers and reduction of sales cycle .this research presents a systematic framework that helps managers of small firms to gain competitive advantage in industrial markets by understanding complex interactions between artificial intelligence tools and marketing strategies.

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  • Receive Date 12 April 2026
  • Revise Date 19 May 2026
  • Accept Date 15 June 2026