Article
AI-Driven Digital Marketing and Sustainable Entrepreneurship: A Multi-Dimensional Entrepreneurial Learning Framework
Purpose: Artificial intelligence (AI) is increasingly transforming digital marketing practices and creating new opportunities for entrepreneurial ventures to engage customers and generate market insights. At the same time, entrepreneurs face growing pressure to balance economic performance with social and environmental sustainability. Despite these developments, existing research remains fragmented, with limited integration between AI-driven marketing capabilities, entrepreneurial opportunity recognition, customer engagement, and sustainable value creation. This study aims to develop a conceptual framework explaining how AI-driven digital marketing capabilities contribute to sustainable entrepreneurial growth through a dynamic entrepreneurial learning process.
Design/methodology/approach: This study adopts a conceptual research design that integrates insights from digital marketing, entrepreneurship, and sustainability literature. Building on theories of customer engagement, opportunity recognition, resource-based view, and dynamic capabilities, the study develops a multi-dimensional conceptual framework. The framework conceptualizes entrepreneurship as a dynamic learning system in which AI-driven digital marketing capabilities generate data-driven marketing intelligence, support entrepreneurial opportunity recognition, enhance customer engagement, and contribute to entrepreneurial competitive advantage and sustainable value creation.
Findings: The study proposes a multi-stage entrepreneurial learning framework linking AI-driven digital marketing capability, data-driven marketing intelligence, entrepreneurial opportunity recognition, customer engagement, competitive advantage, and sustainable value creation. The model suggests that AI-enabled marketing technologies enhance entrepreneurs’ ability to interpret market signals and identify opportunities. These opportunities facilitate stronger customer engagement, which generates relational and informational assets such as brand trust, customer knowledge advantages, switching costs, and network effects. These mechanisms contribute to entrepreneurial competitive advantage, which in turn enables ventures to pursue sustainability-oriented strategies that generate economic, social, and environmental value. The framework also incorporates dynamic feedback loops that reinforce capability development and market learning over time.
Practical implications: The proposed framework provides guidance for entrepreneurs and small and medium-sized enterprises (SMEs) seeking to leverage AI-driven marketing technologies for sustainable growth. Entrepreneurs can enhance competitive positioning by investing in AI-enabled marketing analytics, strengthening customer engagement strategies, and using digital data to identify emerging opportunities. Policymakers may also support entrepreneurial ecosystems by promoting AI adoption, digital infrastructure development, and data-driven capabilities among SMEs.
Originality/value: This study contributes to the literature by integrating AI-driven digital marketing, entrepreneurial opportunity recognition, customer engagement, and sustainable entrepreneurship within a unified conceptual framework. By conceptualizing entrepreneurship as a multi-dimensional entrepreneurial learning system and introducing a capability–engagement–value perspective, the study provides a novel theoretical lens for understanding how AI-enabled marketing technologies can support sustainable entrepreneurial development in digital markets.