As artificial intelligence increasingly integrates into business operations and society, the governance of AI-driven decisions has become more critical than the governance of the underlying infrastructure. While robust infrastructure remains essential for supporting AI systems, the focus is shifting toward ensuring that the algorithms and automated decisions adhere to ethical, legal, and operational standards. Governing decisions involves oversight of AI’s outputs and impacts, aiming for transparency, fairness, accountability, and compliance with evolving regulations. This shift reflects the growing recognition that AI’s influence on people and institutions is shaped mainly by the choices embedded in its design and use, rather than just the hardware or software environment. Effective decision governance can help mitigate risks such as bias, discrimination, unintended consequences, and privacy infringements, thereby building trust and enabling sustainable AI adoption. It also aligns with broader trends in AI strategy, where organizations prioritize responsible AI practices and seek frameworks to monitor and interpret AI behaviors. Thus, in the age of AI, investing in governance mechanisms that oversee decision-making processes is paramount for harnessing AI’s benefits while managing its challenges.