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Abstract: Thanks to artificial intelligence, the corporate has been transforming rapidly and positively in the start-up culture. The study delves into how AI is affecting start-ups and looks at the potential it has to change innovation in business. Our study is undertaken to uncover places where marketing-only AI has been implemented, since we have not access to data and cases necessary for the revealing of complex metrics in this paper. The results showed better decision-making, increased Bicer processing times and significant cost savings with AI application. It is costly to implement, demands particularized knowledge and involvement of sporadically moral estimation. The paper offers implications for AI industrialization in start-ups and future work related to the advantages, as well as hurdles of incorporating this technology. The above has a significant impact to startups — while AI provides vast opportunities for introducing innovation and smart features from data analysis or deep learning paradigms in their offerings, achieving successful adoption as well as ongoing stability is reliant on navigating these constraints proficiently. Thanks to artificial intelligence, the corporate has been transforming rapidly and positively in the start-up culture. The study delves into how AI is affecting start-ups, and looks at the potential it has to change innovation in business. Our study is undertaken to uncover places where marketing-only AI has been implemented, since we have not access to data and cases necessary for the revealing of complex metrics in this paper. The results showed better decision-making, increased Bicer processing times and significant cost savings with AI application. It is costly to implement, demands particularized knowledge and involvement of sporadically moral estimation. The paper offers implications for AI industrialization in start-ups and future work related to the advantages, as well as hurdles of incorporating this technology. The above has a significant impact to startups — while AI provides vast opportunities for introducing innovation and smart features from data analysis or deep learning paradigms in their offerings, achieving successful adoption as well as ongoing stability is reliant on navigating these constraints proficiently
Kumar et al. (Tue,) studied this question.
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