Utilization of Artificial Intelligence in Early-Stage Startups : How early-stage startups are utilizing AI tools in their business operations, and what factors act as challenges and barriers to AI adoption?

Abstract

Over the recent years, Artificial intelligence (AI) technologies have grown in a fast pace making advanced tools and software not only to the large firms but also to small startups. AI has great potential to help startup journey by enabling the new techniques and ideas of innovation, improving efficiency and saving time. Even though there is increasing interest in AI, relatively less research has been done regarding how small startup adopt and use AI in their everyday business practices. This study helps to understand how founders of a small startup perceive and utilize AI tools and what benefits and challenges they face when adopting AI in their business operations. This study is based on the Technology Acceptance Model (TAM) that describes the adoption of technology through two main concepts of perceived usefulness and perceived ease of use. This study is a qualitative study based on semi-structured interviews with founders and co-founders of five startups. The interviews are emphasized on how startup founders use AI tools in daily business operations. The benefits they get and the challenges they have faced while adopting these technologies. The interviews were analyzed using thematic analysis to identify key patterns in the cases. The results indicate that startup engage in artificial intelligence in order to streamline their operations, make better decisions, and facilitate the process of innovation. AI tools help entrepreneurs to automate their routine processes, process a large amount of data, and get insights that will assist in product development and strategic planning. Simultaneously, the research indicates that founders of a startup actively experiment with the use of AI technologies in order to comprehend their potential and implement them in the everyday operations of the business. AI helps startup change with market conditions, refine their products and enhance their competitiveness in dynamic entrepreneurial environments through the process of iterative learning and data-driven experimentation.