By Jasmin Saidi-Kuehnert
June 13, 2025
Artificial Intelligence (AI) is rapidly transforming industries worldwide, and the field of international credential evaluation is no exception. As demand grows for faster, scalable, and more efficient processing of academic documents, some organizations are turning to AI-powered tools to support or even automate aspects of the evaluation process. While the potential benefits are compelling, the rush toward adoption raises serious questions about transparency, oversight, and reliability.
The Promise of AI in Credential Evaluation
AI can streamline many administrative tasks involved in credential evaluation. Optical character recognition (OCR) and natural language processing (NLP) technologies can help extract data from foreign-language documents, classify credential types, and identify educational institutions. This can reduce processing time and support evaluators in high-volume settings.
Moreover, AI can be useful in spotting patterns and anomalies, flagging suspicious credentials, and cross-referencing institutional data across large datasets. In theory, AI could enhance accuracy and consistency by applying standardized protocols to each case. When used appropriately, AI could serve as a powerful tool in the evaluator’s toolkit—not a replacement, but a complement to human expertise.
The Risks of Rushed Implementation
However, the speed with which some providers are claiming AI can evaluate credentials autonomously raises red flags. Full automation in this context is not only premature—it may be dangerous. International credential evaluation involves interpreting nuanced academic systems, cultural contexts, and accreditation frameworks that require expert judgment. AI systems, especially those based on machine learning, rely on historical data. If this data is incomplete, biased, or unverified, the AI’s “decisions” may be flawed or misleading.
Another major concern is the lack of transparency in how some AI-driven evaluations are performed. Many companies tout the use of AI in their services without disclosing what data is used, how it’s sourced, or what verification protocols are in place. There is little clarity on how AI determines institutional legitimacy, equivalency, or grading conversions. Without transparency, users—both institutions and individuals—are left to place blind trust in a process they don’t understand.
The Need for Oversight and Standards
The absence of regulation around the use of AI in credential evaluation only amplifies the risk. There is currently no governing body or accepted standard to ensure that AI tools meet quality benchmarks, uphold ethical standards, or undergo peer review. Without oversight, there is potential for misuse, inaccuracies, and unfair outcomes for applicants whose credentials may be improperly assessed.
Conclusion: Proceed with Caution
AI holds promise for improving efficiency in international credential evaluations, but its role must be clearly defined, transparent, and subject to professional scrutiny. Human evaluators bring contextual understanding, discretion, and ethical accountability that no algorithm can replicate. As the industry continues to explore the role of AI, it must do so responsibly—balancing innovation with integrity, speed with accuracy, and automation with oversight.
Until clear standards, accountability, and transparency are in place, AI should support—not substitute—the expert judgment at the heart of credential evaluation.
Jasmin Saidi-Kuehnert
President & CEO
The Academic Credentials Evaluation Institute, Inc. (ACEI), was founded in 1994 and is based in Los Angeles, CA, USA. ACEI is a full-service company providing complete and integrated services in the areas of international education research, credential evaluation, training and consultancy. https://acei-global.org/
