Article 14 of the AI Act requires that high-risk artificial intelligence systems be subject to effective human oversight. The European Commission explains that those deploying such systems must assign this supervision to individuals who have the proper training, resources, and authority to carry it out. In practice, this legal requirement translates into a complex organizational challenge. Legal departments must now implement specific processes to ensure compliance. One key step is to map the decisions where AI plays a role. Rather than starting with the AI tools themselves, organizations should examine each workflow to determine what the AI recommends, classifies, selects, writes, or triggers—and who has the final say in each case. Another crucial step is to designate a supervisor with real authority. Simply listing a person in a procedure is not enough. The supervisor must have access to the necessary information, time, and skills, and most importantly, the authority to request a review, reject an AI-generated output, or even halt the process. Additionally, clear escalation thresholds must be defined. These thresholds determine when a human review is required—such as when an AI makes a decision that affects fundamental rights, produces a low score, or faces an objection from an affected person. These thresholds must be established in advance to avoid confusion or delays during an incident. Organizations must also ensure that individuals have the right to contest AI decisions. If no one can challenge the AI's recommendations, the supervision process lacks credibility. A clear procedure must be in place for people to report errors, request the reasoning behind AI decisions, ask for reconsideration, and document the outcome. Furthermore, it must be possible to trace the human decisions made in response to AI inputs. This includes knowing who made the decision, based on what information, what the AI had suggested, why the human accepted or rejected the recommendation, and what the consequences were. Testing for automation bias is another essential step. The main risk is not the absence of human oversight, but the tendency of humans to blindly accept AI recommendations. Conducting tests, simulations, and sample reviews can help ensure that supervisors are actually making independent judgments rather than just following AI suggestions. Finally, training must go beyond just understanding how to use AI tools. As outlined in Article 4 of the AI Act, individuals must understand the limitations of AI, the rights of affected individuals, escalation rules, and their own responsibilities. At the Arkemia Institute, researchers are focused on turning these principles into practical governance processes. Their work ensures that AI supports and informs human decisions, while humans retain ultimate responsibility. This approach aligns with the AI Act requirements and supports training in ethical organizational governance. However, it does not serve as a compliance certification on its own. The next step for legal professionals is not only to verify if an AI system is compliant but also to ensure that the organization is capable of rejecting it when necessary.