Building And Scaling Marketing Businesses Across B2B: An AI-Enabled Enterprise Growth Strategy Perspective

Abstract

The rapid digital transformation of enterprise ecosystems has fundamentally reshaped the architecture of B2B marketing, necessitating scalable, intelligence-driven growth strategies. This study investigates how AI-enabled enterprise systems contribute to building and scaling marketing businesses across B2B environments. Adopting a mixed-method research design, data were collected from 250 medium-to-large B2B enterprises and analyzed using structural equation modeling (SEM) and Random Forest machine learning techniques. The results indicate that AI capability significantly enhances revenue growth both directly and indirectly through enterprise integration maturity. Integration across CRM, ERP, sales, and finance systems emerged as a critical mediating mechanism, while governance and leadership readiness significantly moderated the AI–growth relationship. Machine learning analysis identified predictive analytics usage and CRM–ERP synchronization as the strongest drivers of scalable marketing performance. Distributional and interaction analyses further confirmed that enterprises achieving high AI maturity and strong integration simultaneously experience compounded growth advantages. The findings highlight that sustainable B2B marketing scalability is not driven by technology alone but by the convergence of analytical intelligence, systemic alignment, and governance-supported leadership. The study contributes to enterprise growth theory by conceptualizing AI as a structural growth catalyst embedded within integrated organizational ecosystems and provides actionable insights for firms pursuing data-driven expansion strategies.