An AI Impact Assessment (AIIA) is a systematic process designed to identify, evaluate, and mitigate the potential legal, ethical, and societal risks associated with the deployment of an artificial intelligence system before it is put into use.

Unlike a standard Data Protection Impact Assessment (DPIA), which focuses primarily on data privacy and the protection of personal information under GDPR, an AIIA has a much broader scope. It examines how an AI system might affect fundamental human rights (such as non-discrimination and freedom of expression), physical safety, and broader societal well-being. This proactive governance tool is essential for organizations to demonstrate "accountability by design," ensuring that AI systems are not only compliant with regulations but are also trustworthy and ethically robust.

To conduct a comprehensive AIIA, an organization must evaluate the system across several critical dimensions:

• Fundamental Rights Impact: Analyzing whether the system could lead to discrimination, bias, or the erosion of civil liberties (e.g., a hiring algorithm that inadvertently penalizes women).
• Stakeholder Analysis: Identifying all groups who will be affected by the system's decisions—not just the direct users, but also the subjects of the AI's decisions (e.g., loan applicants, patients).
• Technical Robustness and Safety: Assessing the risk of errors, hallucinations, or adversarial attacks that could lead to physical or financial harm.
• Societal and Environmental Impact: Considering the long-term effects, such as the displacement of workers or the energy consumption required to train and run the model.

Regulatory Context: The EU AI Act explicitly mandates a Fundamental Rights Impact Assessment (FRIA) for deployers of high-risk AI systems (such as those used in education, employment, or law enforcement). Similarly, the NIST AI Risk Management Framework (AI RMF) encourages the use of impact assessments during the "Map" and "Measure" functions to contextualize risks.

Strategic Value: Performing an AIIA is not merely a compliance exercise; it is a strategic safeguard. By identifying "unacceptable risks" early in the development lifecycle, organizations can avoid costly redesigns, legal challenges, and reputational damage that often accompany the deployment of flawed or biased AI systems.