Published Insights

A comprehensive examination of where TPRM and data privacy practice is heading — covering AI vendor risk, evolving regulatory frameworks, and the governance models organizations will need to thrive in an increasingly connected risk landscape.

An exploration of how large language models are reshaping vendor risk assessment, privacy compliance, and the future of automated governance — and what practitioners need to understand before deploying AI in their risk programs.

AI-powered tools quietly process, store, and transmit corporate data as unmanaged third parties. A practitioner-focused framework for bringing AI vendor risk into existing TPRM programs before regulators or incidents force the issue.

Quantum computing will eventually break today's public-key encryption, and adversaries are already harvesting encrypted data for future decryption. What Q-Day means for governance, third-party risk, and the migration to post-quantum cryptography.

AI-native security scanning is uncovering vulnerabilities that decades of expert review missed, reshaping how we evaluate vendor software risk. An analysis of the gaps this creates in current TPRM assessment frameworks and what leaders should do now.

Enterprise AI governance is struggling to keep pace with how employees actually use AI tools. An examination of why current frameworks are falling short and a structured approach to closing the gap between policy and practice.

Applicant tracking systems and AI-driven hiring tools create governance and compliance risks that most organizations overlook. An exploration of the third-party risk, data privacy, and oversight challenges embedded in modern recruitment technology.

With nearly half of fintech breaches tied to third parties and 96% of S&P 500 companies exposed to vendor data breaches, TPRM excellence is no longer optional. A case for investing in strategic risk management despite the ROI paradox.