Abstract

The convergence of information and communication technology (ICT) with agricultural entrepreneurship presents unprecedented opportunities for empowering women in rural economies. This chapter explores the intersection of algorithmic intelligence, social pedagogy, and gender-responsive entrepreneurship to advance women-led agri enterprises through ICT-based capacity building and digital innovation. Central to this framework is the integration of AI-driven decision-support systems tailored to the specific needs, socio-cultural contexts, and market dynamics faced by women farmers and agripreneurs. Emphasis is placed on mitigating algorithmic bias, promoting fairness in digital services, and enhancing the quality of gender-disaggregated datasets to ensure equitable participation in emerging agricultural markets.

The narrative addresses critical ethical considerations in data governance, advocating for transparent, participatory models of data collection, consent, and usage that safeguard women’s rights in the digital economy. Beyond technology, the chapter underscores the importance of community-driven pedagogical approaches that embed digital literacy, entrepreneurial leadership, and cooperative ownership structures. This dual emphasis on technological sophistication and socially grounded learning creates a holistic capacity-building model capable of transforming the entrepreneurial agency of rural women.

Policy coherence emerges as a central pillar in promoting sustainable digital entrepreneurship. Effective alignment of gender, agricultural, and digital economy strategies fosters an enabling environment for inclusive innovation, complemented by regulatory frameworks that institutionalize ethical practices, protect data privacy, and promote algorithmic accountability. The chapter further advances governance models that promote community ownership of ICT platforms, positioning women not merely as users but as leaders and co-creators within digital ecosystems. By bridging technological intelligence with participatory governance and inclusive education, this framework provides a scalable pathway for advancing women’s leadership, economic autonomy, and resilience in agricultural value chains within an increasingly digital global economy.

Introduction

Women’s participation in agriculture has always formed the backbone of rural economies, particularly in developing nations. Their contributions range from subsistence farming to managing agri-enterprises and leading value-added production [1]. However, structural inequalities in access to finance, land ownership, training, and technology continue to limit their potential for entrepreneurial growth. Digital technologies, specifically information and communication technology (ICT) platforms, have emerged as transformative tools that can redefine the agricultural landscape for women entrepreneurs [2]. The convergence of mobile applications, AI-powered advisory systems, e-commerce platforms, and digital financial services holds the capacity to reshape how women engage with agricultural value chains [3]. These tools enable better market linkages, improve access to critical agricultural inputs, provide weather and crop advisories, and facilitate networking with stakeholders across regions. Yet, the mere presence of technology does not automatically translate to empowerment unless accompanied by deliberate interventions addressing existing social, cultural, and digital divides [4]. Building comprehensive models that interlink technological innovations with tailored capacity-building approaches becomes essential to elevate women’s entrepreneurial potential in agriculture [5].

A significant dimension of digital transformation in agriculture is the increasing reliance on algorithmic intelligence to generate predictive insights for farm management, supply chain optimization, and business decision-making [6]. Artificial intelligence (AI)-driven platforms offer tremendous potential for enhancing efficiency and competitiveness in agricultural enterprises [7]. However, these technological advances often replicate existing gender disparities embedded in datasets, algorithms, and deployment frameworks. Women, particularly those from marginalized regions, are often underrepresented in agricultural data, leading to biased outputs that perpetuate exclusion rather than alleviate it [8]. Ensuring algorithmic fairness is therefore critical to safeguarding equitable participation in digital agri-entrepreneurship. This requires intentional efforts to create gender-inclusive datasets, transparent algorithmic processes, and participatory design methodologies that involve women at every stage of technological development. Without addressing these structural biases, digital tools risk reinforcing existing inequalities [9]. By embedding fairness, transparency, and inclusivity into the fabric of AI systems, digital interventions can become true enablers of women’s economic empowerment in agricultural settings [10].