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  • Businesses can make well-informed strategic decisions that are in line with changing market dynamics thanks to this data-driven approach. For example, businesses such as Procter and Gamble use AI analytics to precisely predict product demand, which enables them to minimise waste and optimise production schedules. Also, by offering predictive analytics that spot possible threats before they become real, AI helps improve risk management. AI algorithms are being used more & more by financial institutions to identify fraudulent activity through real-time transaction pattern analysis.
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  • Concerns about the ethical implications of using AI are another frequent problem. Inadequate management of issues like algorithmic bias, data privacy, & transparency can put organizations at serious risk. When deploying AI, businesses need to set moral standards that put accountability and justice first. Businesses such as IBM, for example, have created frameworks for responsible AI that prioritize openness in algorithmic decision-making. Organizations can increase stakeholder trust & reduce the possibility of negative feedback from customers and authorities by proactively addressing these ethical issues.
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