High-Impact AI Explained: AI That Affects Human Safety and Fundamental Rights, Complete Guide

High-impact AI is a concept under the AI Basic Act that refers to AI that may seriously affect the safety of human life and body and fundamental rights, or that may pose a risk. Providers of such AI are bound by duties such as risk management, explanation, and human oversight.

Why you need to know about high-impact AI

AI has begun to be used for decisions about people.

When AI was limited to summarizing documents or helping with search, a wrong result left plenty of room for a person to correct it. Now AI is also used for judgments that directly affect a person's rights and opportunities, such as hiring, credit scoring, and loan screening. If such judgments go wrong, the harm can be hard to reverse.

In Korea, the law commonly called the AI Basic Act, formally the Basic Act on the Development of Artificial Intelligence and the Creation of a Trust Base, took effect on January 22, 2026, together with its enforcement decree. The law classifies as high-impact AI those AI systems that may seriously affect the safety and fundamental rights of people. It sets ten areas, including hiring and loan screening, and imposes separate duties on providers of such AI.

Companies that use external AI without developing their own models are not exempt either. Organizations that want to apply AI to their work should first check whether their service falls under high-impact AI and, if so, what they must prepare.

The exact definition of high-impact AI: how it differs from general AI services

Three axes of difference between general AI services and high-impact AI

First, the criteria for classification differ. High-impact AI is judged by where AI is used and what effect it has on people, not by which technology was used. The same model can be judged differently when used for internal document search versus for a decision that screens a person.

Second, the provider's duties differ. A service that uses generative AI must notify users in advance of that fact, and the method of notice and labeling is covered by the transparency guidelines issued by the Ministry of Science and ICT. High-impact AI, in addition, must establish a risk management plan, an explanation plan, and a user protection plan, and must build a system for people to manage and supervise it.

Third, the level of records to keep differs. A general service focuses on delivering results. High-impact AI requires preparing and keeping documents that confirm what measures were taken to secure safety and reliability, so the judgment process and the measures taken must be left as records.

Whether something falls under this is often unclear. The law provides a procedure in which a business can attach relevant documents, such as a service overview, and request the Minister of Science and ICT to confirm whether it is high-impact AI.

Five duties that high-impact AI providers must meet

Content of the five duties set by law

First, establish and operate a risk management plan. Identify and manage the risks that may arise when the AI makes a wrong judgment, set a plan to do so, and make sure the plan is actually followed in operation.

Second, establish and implement an explanation plan. Prepare a way to explain the results the AI produced and the criteria used for them.

Third, establish and operate a user protection plan. Prepare and run measures to protect users affected by the AI's judgments.

Fourth, manage and supervise by people. Put in place a system in which people can check the AI's judgments and correct them when necessary.

Fifth, prepare documents confirming the measures taken to secure safety and reliability, and keep them for five years.

The detailed standards for each duty are set by subordinate legislation such as the enforcement decree, so actual preparation must proceed while checking the original text of the law.

Practical preparation for high-impact AI

Check applicability by business first

Make a list of the business tasks where the organization uses or plans to use AI, and mark whether the AI's results are used for decisions about people in each. The size of the effect changes depending on whether staff merely consult the result or whether it is reflected directly in the decision.

Work that is hard to judge should get a legal review and, where necessary, use the confirmation request procedure. Keeping the inspection results and the reasons for the judgment as a record becomes the standard for reviewing again when the work changes or the uses of AI expand.

Keep the basis for judgment and the history

To fulfill the explanation plan and the document retention duty, you must be able to show later how the AI reached its result. If AI agents are used for document screening, record for each case the location in the original that served as the basis of judgment, the rules applied, and the model and rule versions used.

Records must be in a form people can read, so that you can respond to a user's request for explanation or objection. When a model or rule is changed, also keep before-and-after comparisons of results and approval records.

Keep a human check on final decisions

Human oversight is hard to satisfy with a formal signature. Put in place a review screen that shows the AI's judgment results together with their basis, and keep a record of when a person approved or corrected them. Design the flow so that cases that deviate from the criteria are automatically handed to the responsible staff member.

High-impact AI in a domestic environment

The AI Basic Act treats not only businesses that develop and provide AI but also businesses that provide products or services using AI made by others as AI businesses. A company that connects an external model through an API to build a screening tool can also become subject to the duties.

The government has said it will set a grace period of at least one year before fact-finding and fines are imposed. However, the grace period is time to prepare, not a period without obligations, so it is better to start early on preparation that takes time, such as record-keeping systems.