The concept of Artificial Intelligence (AI) turned out to be one of the game changers that can reshape the modern business environment by offering an opportunity to make decisions, automated and efficient, depending on the existing data. The application of AI technologies to the functioning of organisations representing other industries is becoming more widespread, with the intention to enhance their strategic abilities and to be able to preserve their competitiveness in the environment of highly evolved markets. Despite the general adoption of its application, however, there is no unanimity in the strategic merit of AI in fuelling innovation, operational efficiency, and competitive advantage simultaneously. The present paper will engage in a critical analysis of the multitasking attribute of AI as a strategic enabler within contemporary business models. The research is grounded on the secondary data-driven approach since the systematic review of current academic and industry articles is carried out in order to establish trends and outcomes of AI implementation. The findings indicate that AI can positively influence the organisational performance by a wide margin in terms of the accuracy of decisions made, reducing the workload, the cost involved, and the ability of the customers to experience a personal experience. Also, AI assists in being innovative in the development of new products, services and business models. The results of the research are as follows: AI is not only a technological solution but a strategic resource that can be considered the basis of long-term value generation and a sustainable competitive advantage in the digital economy.
Artificial Intelligence, Business Strategy, Innovation, Operational Excellence, Competitive Advantage, Digital Transformation
. Algorithmic Advantage: A Critical Analysis of Artificial Intelligence as a Strategic Driver of Innovation, Operational Excellence, and Competitive Differentiation in Contemporary Business Models. Indian Journal of Modern Research and Reviews. 2023; 1(1):95-101
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