IJLTEMAS International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS) IJLTEMAS 2278-2540 IJLTEMAS 104 10.51583/IJLTEMAS.2026.150700099 Commerce Artificial Intelligence as an Enabler of Transformative Social Entrepreneurship – A Hypothetical Assessment of Its Role in Achieving Sustainable Development Goals Deeksha S Dr. Faculty, Department of Studies and Research in Commerce, Dr Manmohan Singh Bengaluru City University, Commerce Block, Bengaluru – 560001, Karnataka, India. India Komal. S Mrs. Faculty, Department of Studies and Research in Commerce, Dr Manmohan Singh Bengaluru City University, Commerce Block, Bengaluru – 560001, Karnataka, India. India 15 7 1263 1275 27 07 2026 01 08 2026 17 08 2026 Artificial Intelligence Social Entrepreneurship Transformative Innovation Sustainable Development Goals Organizational Agility Social Impact. Abstract

Social entrepreneurship is becoming a vital means of responding to complex problems related to both socio-economic and environmental conditions globally. Despite the potential for social entrepreneurship to transform society and achieve the Sustainable Development Goals (SDGs), social enterprises experience numerous barriers to scale-up, resource mobilization, impact measurement and operational efficiencies. The use of Artificial Intelligence (AI) offers social enterprises potential solutions to enhance decision making; optimize resource allocation; strengthen their ability to innovate and deliver measurable social impacts. Therefore, the purpose of the current study is to investigate whether social entrepreneurs' awareness of AI capabilities influences their ability to develop transformative social entrepreneurship that achieves SDGs. The research study uses a mixed-methods design and collects primary data from registered social enterprises. A quantitative survey instrument will be used to collect data from social entrepreneurs. Quantitative data analysis will be conducted via a factor analysis and structural equation model. Qualitative data collection methods, specifically interviews with social enterprises utilizing AI technology, will be used to gather deeper insight into transformative processes. It is expected that the ability of AI to increase the agility and innovation capacity of organizations, along with measured SDG outcomes, will be significantly enhanced. However, there are anticipated financial constraints, digital skills deficits and concerns about ethics of data usage that could impede the adoption of AI technology. Findings from the research study should be useful for policymakers, social enterprise leaders and development agencies seeking ways to leverage AI technology as a catalyst for sustainable transformation.

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