Evaluate Algorithmic Impact
Before Bias Becomes Liability

An Algorithmic Impact Assessment (AIA) is a systematic, documented process for identifying, analyzing, and mitigating the potential impacts of algorithmic and AI systems on individuals, organizations, and society. The assessment examines risks related to fairness, bias, discrimination, transparency, explainability, data protection, human oversight, safety, and potential social harms. It is especially relevant for high-impact systems, public sector deployments, or solutions that may affect fundamental rights.

Any organization that develops, deploys, or uses algorithmic or AI systems that influence decisions affecting people. This includes companies using AI in hiring processes, credit scoring, insurance, targeted advertising, or content moderation, public sector organizations deploying automated decision-making systems in areas such as justice, education, healthcare, or social benefits, and any organization subject to the EU AI Act, US state AI laws, or equivalent regulations requiring impact assessments for high-risk systems.

No. It is a diagnostic and evaluation process, not a certification. Its value lies in identifying the impact risks of an algorithmic system in advance of deployment or during operation, and in documenting the mitigation measures adopted. The results can be used as evidence of responsible governance before regulators, investors, or procurement teams, and as a foundation for structuring a certifiable AI management system under ISO/IEC 42001.

The ISO/IEC 23894 risk assessment focuses on the technical, operational, and organizational risks associated with AI systems throughout their lifecycle. The Algorithmic Impact Assessment focuses on the effects those systems have on people and society: discrimination, bias, lack of transparency, impact on fundamental rights, and collective harms. Both are complementary. ISO/IEC 23894 evaluates the risks of the system; the AIA evaluates the risks to the people affected by the system.

They are especially necessary for systems that make or influence decisions about people, such as credit scoring or financial evaluation systems, hiring and employee assessment tools, healthcare prioritization or automated triage systems, fraud or risk detection models, content moderation or recommendation systems, surveillance tools, biometric identification or facial recognition systems, and any system classified as high-risk under the EU AI Act or equivalent legislation.

The standard timeline is approximately four to six weeks, depending on the number of systems assessed, the complexity of the system's interactions with affected individuals, and the availability of technical documentation and performance data. Systems with multiple use cases or affecting diverse populations may require a longer timeline.

The assessment requires access to the functional description of the algorithmic system, technical documentation of the model, the training and validation data used, available performance and fairness metrics, human oversight procedures, applicable data protection policies, and any prior complaints, incidents, or audits related to the system.

A structured report that includes identification of the groups affected by the system, an impact analysis classified by risk type (fairness, discrimination, privacy, transparency, safety), an evaluation of existing mitigation measures, identification of gaps and residual risks, and a prioritized action plan with mitigation recommendations and timelines. The report is an auditable document that can be presented to regulators, investors, or procurement teams.

The EU AI Act requires providers and deployers of high-risk AI systems to conduct fundamental rights impact assessments. An independent Algorithmic Impact Assessment provides the documentary and analytical foundation to meet this obligation, and generates auditable evidence that the organization has proactively evaluated and mitigated the impact risks of its AI systems.

The Algorithmic Impact Assessment directly feeds into the risk management dimension of an AI management system under ISO/IEC 42001. The results can be used to strengthen fairness, transparency, and human oversight controls within the management system, facilitating certification. Zertia offers both services and can design an integrated engagement.

Yes. The resulting report provides documented evidence that the organization has proactively assessed the impact of its algorithmic systems on people. This can facilitate public procurement processes where algorithmic transparency is required, investor due diligence processes evaluating reputational and regulatory risks, and relationships with enterprise clients that require responsible AI governance from their suppliers.