Operational Risk Assessment in AI Algorithms: A Multi-Faceted Approach

Abstract

With artificial intelligence technology businesses now make better decisions faster while reducing manual tasks. The way AI algorithms function brings important operational risks which businesses have to take seriously. Organizations using AI face major problems when their systems exhibit algorithmic discrimination or privacy problems together with unexpected breakdowns. Research exposes every operational risk AI systems pose using an in-depth analysis of source, impact and safety methods. Using advanced optimization methods with regulatory standards the report shows how ANNs metaheuristic algorithms and prudential testing methods can lower and manage these operational risks. The research presents real-world applications from banking, power and health sectors to show how these risk reduction methods actually work. Strong governance and ethical standards must guide AI development to prevent misuse. The study presents future guidelines to build AI systems that can adjust to change while showing users what they do while reducing risk of this technology (Fortes et al., 2022).