Next-Gen 3rd Party Cybersecurity Risk Management Practices: AI Enablement

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Author(s): Aneesh Krishna (University at Buffalo, SUNY, USA)and Moksh Gupta (University at Buffalo, SUNY, USA)
Copyright: 2026
Pages: 30
Source title: Advancing IT Audits Through Integrative Approaches and Emerging Technologies
Source Author(s)/Editor(s): Manish Gupta (University at Buffalo, SUNY, USA), John Walp (University at Buffalo, SUNY, USA)and Raj Sharman (University at Buffalo, SUNY, USA)
DOI: 10.4018/979-8-3373-3078-5.ch001

Keywords: Engineering Science Reference / IT Governance / IT Policy and Standardization / Library & Information Science

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Abstract

As organizations deepen their reliance on third-party vendors to drive innovation and operational flexibility, the landscape of Third-Party Risk Management (TPRM) has become increasingly intricate and vulnerable to cyber threats, regulatory violations, and operational disruptions. This study presents a comprehensive review of how Artificial Intelligence (AI), particularly Natural Language Processing (NLP) and Large Language Models (LLMs), are transforming the TPRM ecosystem. By automating the analysis of vendor communications, compliance audits, legal contracts, and security assessments, AI-driven tools enabling real-time monitoring, predictive risk scoring, and anomaly detection at an unprecedented scale. The paper investigates a range of academic and industrial solutions and compares their effectiveness in automating assessments and enhancing transparency. Ultimately, the research advocates for building adaptable, interpretable, and secure AI systems that can support enterprise-wide risk governance in an evolving third-party ecosystem.

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Next-Gen 3rd Party Cybersecurity Risk Management Practices: AI Enablement

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