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AI-enabled assessment technologies are increasingly used by higher education institutions to protect academic integrity, scale online assessment and respond strategically to generative artificial intelligence. This paper examines how online proctoring, automated scoring, AI writing detection, and learning analytics risk flagging reshape institutional governance, stakeholder trust, and assessment strategy in higher education business ecosystems. Using a systematic-narrative review approach informed by PRISMA 2020 reporting principles, the study synthesises peer-reviewed literature and authoritative policy guidance published between 2015 and 2025. The analysis is organised around an integrated theoretical framework that combines assessment validity, academic integrity values, algorithmic accountability, and ecosystem strategy. The findings show that AI-enabled assessment can support identity verification, monitoring capacity, workflow triage and timely feedback when deployed as human-governed decision support rather than automated adjudication. However, over-reliance on surveillance and detection creates strategic risks: false positives, bias against linguistically diverse students, privacy intrusion, opaque decision-making, weakened due process and construct distortion when assessments measure surveillance compliance instead of intended learning outcomes. The review further shows that institutional legitimacy depends less on the technical promise of tools and more on governance capability, including proportionality, transparency, contestability, equity auditing, privacy protection and authentic assessment redesign. The paper contributes to business ecosystem and strategy scholarship by positioning academic integrity technology as a strategic governance issue within higher education service ecosystems. It recommends integrity-by-design, cross-functional AI governance, vendor accountability and assessment strategies that preserve fairness, validity and stakeholder trust.

AI-enabled assessment technologies are increasingly used by higher education institutions to protect academic integrity, scale online assessment and respond strategically to generative artificial intelligence. This paper examines how online proctoring, automated scoring, AI writing detection, and learning analytics risk flagging reshape institutional governance, stakeholder trust, and assessment strategy in higher education business ecosystems. Using a systematic-narrative review approach informed by PRISMA 2020 reporting principles, the study synthesises peer-reviewed literature and authoritative policy guidance published between 2015 and 2025. The analysis is organised around an integrated theoretical framework that combines assessment validity, academic integrity values, algorithmic accountability, and ecosystem strategy. The findings show that AI-enabled assessment can support identity verification, monitoring capacity, workflow triage and timely feedback when deployed as human-governed decision support rather than automated adjudication. However, over-reliance on surveillance and detection creates strategic risks: false positives, bias against linguistically diverse students, privacy intrusion, opaque decision-making, weakened due process and construct distortion when assessments measure surveillance compliance instead of intended learning outcomes. The review further shows that institutional legitimacy depends less on the technical promise of tools and more on governance capability, including proportionality, transparency, contestability, equity auditing, privacy protection and authentic assessment redesign. The paper contributes to business ecosystem and strategy scholarship by positioning academic integrity technology as a strategic governance issue within higher education service ecosystems. It recommends integrity-by-design, cross-functional AI governance, vendor accountability and assessment strategies that preserve fairness, validity and stakeholder trust.