Artificial intelligence-driven scalability and its impact on the sustainability and valuation of traditional firms

The objective of this study is to determine the impact of artificial intelligence (AI) on the\r\nearnings before interest, taxes, depreciation, and amortization (EBITDA) of firms as a proxy\r\nof their financial and economic margins by improving revenues and minimizing expenses.\r\nThis impact is positive on the market value and scalability by improving the economic and\r\nfinancial sustainability of companies. The methodology is based on a business plan that\r\nconsiders the savings obtained by a traditional firm implementing AI. Specifically, a sensitivity\r\nanalysis will demonstrate that AI savings impact key parameters, leading to economic and\r\nfinancial sustainability. Additionally, a mathematical interpretation, based on network theory,\r\nwill be produced to provide and compare the added value of two ecosystems (without and\r\nwith AI that adds up new nodes and strengthens the existing ones). The main contribution of\r\nthis paper is the combination of two unrelated approaches, showing the potential of AI in\r\nscalable ecosystems. In future research, this innovative methodology could be extended to\r\nother technological applications.