AI isn’t just making vendor assessments faster. It’s changing who performs the work, how risk is evaluated, and what TPRM teams can accomplish.
Most third party risk management (TPRM) programs have better technology than they did five years ago, but the underlying work hasn’t changed much. Teams still spend significant time collecting vendor documentation, reviewing evidence, following up on questionnaires, and identifying control gaps. Modern platforms have improved how that work is organized, but people still perform most of the assessments.
As vendor portfolios grow, this approach becomes increasingly difficult to sustain. Organizations can hire more analysts, extend assessment timelines, or limit the number of vendors they review, but none of those options fundamentally changes the problem.
AI offers a different approach. Rather than simply helping analysts complete individual tasks faster, specialized AI agents can perform much of the evidence collection and analysis themselves. Risk professionals remain responsible for oversight and decisions, but they no longer need to execute every step of the process.
This is the shift toward machine executed, human governed TPRM.
Why Traditional TPRM Needs to Change
Before cofounding VISO TRUST, I served as CISO at several organizations, including LendingClub, where we relied on more than 4,000 vendors. As the business grew, we needed to onboard new providers quickly while maintaining appropriate oversight of third-party risk.
We implemented what we believed was a lightweight questionnaire process, following established industry practices. In practice, it created significant manual work. Vendors were slow to respond, assessments delayed procurement, and our security team developed a reputation as the “department of no.”
The experience highlighted a fundamental limitation of traditional TPRM: assessment capacity depends on the number of people available to perform the work. Workflow automation can make the process more manageable, but it doesn’t eliminate the underlying workload.
To scale effectively, organizations need to change who performs the assessment work, not simply how that work is tracked.
Not All AI in TPRM Is the Same
Nearly every TPRM provider now talks about AI, but there’s an important difference between AI assistance and AI driven assessments.
A general-purpose AI tool might summarize a SOC 2 report, research a vendor, or draft questionnaire responses. These capabilities can save time, but an analyst still needs to evaluate the underlying evidence and determine whether the vendor meets the organization’s requirements.
More importantly, AI generated answers aren’t necessarily accurate. A vendor can produce a convincing questionnaire response without demonstrating that the underlying control exists or operates effectively.
A well written answer isn’t evidence.
Specialized AI agents take a different approach. Rather than generating broad conclusions, they’re designed to perform defined assessment tasks against specific criteria.
For example, agents can examine a SOC 2 report to identify relevant controls, testing results, exceptions, and subservice organizations. Findings can be connected to the supporting documentation, giving risk professionals a clearer basis for review.
At VISO TRUST, we’ve been developing AI supported vendor assessments since 2020. Today, more than 50 specialized agents support vendor research, evidence analysis, and assessment operations.
The objective isn’t to remove human judgment. It’s to reduce the manual effort required to reach a defensible risk decision.
Faster Assessments Create New Opportunities
Reducing assessment time is valuable, but the bigger opportunity is changing how TPRM supports the business.
Traditionally, risk teams often become involved after a business owner has already selected a vendor. By that point, commercial discussions may be underway, and any significant finding can delay procurement.
When AI can analyze available vendor evidence quickly, TPRM teams can engage earlier in the selection process. Instead of evaluating one vendor after the decision has effectively been made, they can provide risk information while the business is still comparing alternatives.
The same efficiency gains can help organizations expand assessment coverage. Many programs concentrate their resources on critical vendors because comprehensive reviews require substantial manual effort. AI makes it more practical to evaluate a broader vendor population while applying deeper scrutiny where the risk warrants it.
It also supports a move toward more continuous risk visibility. Updated assurance documents, incident disclosures, and information about downstream providers can inform reassessment as circumstances change, rather than relying exclusively on periodic reviews.
These changes allow TPRM to become more proactive without requiring staffing to increase proportionally with the vendor portfolio.
From Performing Assessments to Governing Risk
The most significant change may be how TPRM professionals spend their time.
Today, experienced analysts devote substantial effort to collecting documents, reviewing artifacts, and coordinating vendor follow up. These activities are necessary, but they don’t always represent the best use of their expertise.
When specialized AI agents handle more of that work, risk professionals can focus on evaluating exceptions, determining appropriate remediation, engaging business owners, and advising leadership on meaningful exposure.
They also play an essential role in governing the technology itself. Organizations still need people to establish assessment criteria, evaluate the quality of AI outputs, and make decisions based on business context and risk appetite.
That’s what machine executed, human governed TPRM means in practice. AI performs much of the analysis, while people remain accountable for the decisions.
For TPRM teams, this creates an opportunity to move beyond being an approval checkpoint and become a more valuable partner to the business.
The Future of TPRM
For years, TPRM technology has focused on organizing assessments and managing workflows. AI is now making it possible to change the work itself.
Specialized agents can analyze vendor evidence, support broader assessment coverage, and provide more timely risk information. Risk professionals can focus their expertise on oversight, significant findings, and decisions that matter to the organization.
The opportunity isn’t simply to complete the same assessments faster. It’s to build a TPRM program that can understand more risk, engage earlier, and support better business decisions.
The future of TPRM isn’t about managing questionnaires more efficiently. It’s about turning vendor evidence into better risk decisions.