This chapter provides a Management Model for Artifitial Intelligence (MMAI) that, through its application and analysis, enables corporate decision-makers, academics, consultants, and others interested in the topic to seek the best alternatives for AI management, helping them streamline their organizations and achieve the highest standards of profitability, competitiveness, and sustainability. The MMAI is composed of nine key factors: 1) Clear objectives, 2) Ethics and regulation, 3) Data governance, 4) Transparency and explainability, 5) Performance and scalability, 6) Continuous training, 7) Risk management, 8) Integration and compatibility, and 9) Stakeholder engagement. Each factor, in turn, contains a series of variables that explain it. In total, there are twenty-seven (27) variables explained in detail in the theoretical framework of this chapter, which measure four levels ranging from 0 to 100%.
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