Your firewall didn’t cause the last major breach your organization experienced. Your vendor did.
That’s not a hypothetical. According to the 2025 Verizon Data Breach Investigations Report, roughly one in three data breaches now involves a third party โ double the figure from the prior year. Supply chain attacks and vendor credential compromise have become the preferred entry point for attackers who have learned that your perimeter extends through every SaaS tool, cloud provider, and managed service you’ve ever trusted with access to your data.
The question isn’t whether your vendors introduce risk. They do. The question is: do you know which ones, and how much?
The Supply Chain Has Become the Attack Surface
Traditional TPRM programs were built around annual questionnaires, static security ratings, and periodic document reviews. A vendor would complete a self-assessment, security teams would review a SOC 2 report, and the relationship would proceed โ with risk understood only at a single point in time. In a threat landscape that changes daily, this is the equivalent of checking the weather once a year and deciding what to wear for all twelve months.
The 2026 KPMG Global TPRM Survey found that 48% of risk professionals cite cyber risk as their top TPRM concern โ ahead of every other category. Yet the same survey revealed that only 15% of leaders express high confidence in the data underpinning their programs. Organizations know vendor risk is a top threat. They’re just not equipped to manage it at the speed and scale the threat demands.
That’s beginning to change, driven by AI.
Why Manual TPRM Is Breaking Under Its Own Weight
A typical enterprise manages hundreds of vendors. For each one that warrants scrutiny, a security analyst must review dense compliance documentation. A SOC 2 Type II report can run hundreds of pages; a HECVAT document is equally demanding. Thorough manual review takes six to eight hours per analyst, per vendor.
Multiply that by vendor volume, add weeks of follow-up to collect documents in the first place, then layer on regulatory complexity โ DORA, NIS 2, GLBA, PCI DSS, and HIPAA all mandate third-party oversight with real penalties for non-compliance. Most security teams are already stretched thin. The math simply doesn’t work, and organizations are forced to review fewer vendors, review them superficially, or divert resources away from proactive defense.
This is not a staffing problem. It’s a structural one that requires a fundamentally different approach.
How AI Is Transforming Third-Party Risk Management
AI is the game-changer, automating tedious tasks, enhancing accuracy, and enabling continuous monitoring. More than half of organizations in the KPMG survey are exploring AI for TPRM, with 22% reporting it as “very effective.” AI shifts TPRM from process management to autonomous risk intelligence, predicting threats before they materialize.
Automated Report Auditing
FortifyData’s AI Auditor accepts SOC 2, HECVAT, SIG, and other vendor compliance documents and audits them against chosen frameworks โ NIST CSF, ISO 27001, CIS Controls, or AI-specific frameworks like NIST AI RMF and HITRUST’s AI Security Assessment. In minutes, it produces a visual dashboard showing compliance coverage by control group, flags deficiencies with page-level citations, and highlights gaps that might otherwise go undetected in a manual review.
Critically, it doesn’t just mirror what a human analyst would find. In real deployments, it has surfaced risks that reviewers overlooked โ a distinction that matters when the goal is preventing breaches, not generating paperwork.
Proof in Practice:ย
Pima Community College was managing vendor risk the traditional way: one analyst, one vendor, six to eight hours per review โ consuming roughly 10% of the security team’s capacity.
After deploying FortifyData’s AI Auditor, review times dropped to one to two hours per vendor, a reduction of over 75%. Team time dedicated to vendor reviews fell from 10% to under 2%. CISO Lorenso Trevino noted the AI not only matched manual findings but surfaced concerns the team had previously missed, and that analysts could shift focus to other tasks while the audit ran โ a meaningful operational win in a lean security environment.
Validation Against Real-World Signals
One persistent problem with traditional TPRM is its reliance on self-reported information. A vendor claims to encrypt data at rest โ but without independent validation, there’s no way to confirm it.
AI-powered TPRM addresses this by cross-referencing vendor claims against External Attack Surface Management (EASM) scan data. If a vendor claims strong patch management but active CVEs appear on their public-facing systems, that inconsistency surfaces automatically. This is the difference between TPRM that creates defensible risk decisions and TPRM that simply generates documentation.
Automating the Vendor Lifecycle
Beyond document analysis, AI is taking over the administrative orchestration of the entire vendor risk lifecycle โ onboarding requests, document collection follow-ups, deadline reminders, remediation tracking โ tasks that consume enormous analyst time with low strategic value. FortifyData’s AI Workflow Automation handles these activities autonomously, maintaining audit trails and ensuring timely responses without manual coordination.
What This Means for CISOs and Risk Leaders
For security leaders, the shift toward AI-powered TPRM creates both immediate opportunity and strategic urgency. The efficiency gains are real: teams that adopt AI-powered auditing and workflow automation can cover far more vendor relationships without proportional headcount increases.
The urgency stems from the threat data. With one in three breaches now involving a third party โ a figure that doubled in a single year โ vendor risk is no longer a compliance sub-discipline. It is a core component of enterprise cyber risk, and regulators are treating it as such.
A few practical priorities follow from both the data and the technology:
Classify vendors before you review them. Apply assessment intensity in proportion to data sensitivity, operational criticality, and breach impact potential. AI can supercharge a risk-based approach, but only if the triage logic is sound.
Move from point-in-time to continuous. Real-time EASM monitoring combined with AI-triggered alerts for changes in vendor risk posture replaces the annual snapshot with a living picture of exposure.
Validate, don’t just collect. Cross-referencing vendor claims against technical scan data transforms questionnaire responses from a starting point into something closer to assurance.
Use contract renewals as leverage. Initiating assessments two to three months before renewal creates natural cooperation incentives and a defined window for remediation commitments.
The Stakes Are Real
One in three breaches. Doubling year-over-year. A regulatory environment that is actively tightening around vendor oversight. The organizations that close the gap between their stated and actual vendor risk posture โ moving from periodic, document-driven TPRM to continuous, AI-validated risk intelligence โ will reduce breach exposure and operate with a level of supply chain confidence their peers cannot match.
The battlefield has shifted to your vendor ecosystem. The tools to defend it are here.
FortifyData provides AI-powered third-party risk management as part of its integrated Cyber GRC platform, combining External Attack Surface Management, AI Auditor, automated questionnaire validation, and agentic workflow automation. Learn more at fortifydata.com or schedule a demo.


