Designing and Explaining an Entrepreneurship Model for Artificial Intelligence–Based Businesses

The primary objective of the present study was to design and explain an entrepreneurship model for artificial intelligence–based businesses, with a focus on the information and communications technology and computer software industries in knowledge-based companies located in Tehran Province. In terms of purpose, the study was applied, and in terms of approach, it was a qualitative study employing a sequential exploratory design. In the qualitative phase, grounded theory was applied using the systematic approach to identify and conceptualize the dimensions, components, and relationships among the variables affecting AI-based entrepreneurship. The qualitative research field consisted of senior and middle managers, specialists, experts, and experienced employees working in the information and communications technology and computer software industries of knowledge-based companies in Tehran Province. Participants were selected through purposive sampling, which continued until theoretical saturation was reached. Qualitative data were collected through semi-structured interviews and analyzed using MAXQDA 2024. To enhance the credibility and trustworthiness of the data, triangulation and Lincoln and Guba’s criteria, including credibility, transferability, dependability, and confirmability, were employed. The findings indicated that the entrepreneurship model for AI-based businesses consists of an interconnected set of causal conditions, contextual conditions, intervening conditions, strategies, and consequences. The causal conditions included factors such as market needs and technological gaps, entrepreneurial opportunity recognition, and customers’ digital preferences, all of which played a fundamental role in the formation of AI-based entrepreneurship. The contextual conditions included the need to establish a knowledge-based ecosystem, policymaking and regulations, financial capabilities and initial investment, advanced technological capacities, specialized human capital, team competencies, and intraorganizational collaboration. Intervening conditions, including legal and regulatory constraints associated with sensitive data and cybersecurity, as well as economic restrictions and sanctions, were also found to affect the development of entrepreneurship. According to the findings, the key strategies were the development of strategic collaborations, product development and upgrading, digital marketing and market penetration, and human capital empowerment. Finally, the consequences of implementing the model included economic and financial maturity, the development of technological authority, social and employment effects, digital transformation in upstream industries, and software export development.