Vanta’s State of Trust Report 2023 identified a practical problem: security and compliance teams were spending substantial time collecting evidence and coordinating reviews while still lacking confidence in their risk visibility. The report presented AI-powered trust management as a way to reduce repetitive work. That is a narrower and more defensible claim than saying AI makes an organization secure or compliant.
The findings came from a Vanta- and Sapio Research-conducted survey of 2,500 business and IT leaders in the United States, United Kingdom, Germany, France and Australia. Published on November 8, 2023, the survey measures respondents’ perceptions and operating practices; it is not a breach study, penetration test, audit or independent assessment of Vanta’s product.
What Vanta’s 2023 survey measured
The survey examined security and compliance programs, risk visibility, staffing and budgets, manual compliance work, automation plans and how organizations prove their security posture to customers and partners. Those are related but different measures:
- Security posture concerns the safeguards and technical practices intended to reduce cyber risk.
- Compliance status concerns whether an organization meets the scope and requirements of a framework or regulation.
- Risk visibility concerns whether leaders can identify assets, weaknesses, control failures and exceptions.
- Trust proof concerns the evidence an organization can provide during sales, procurement and audits.
A positive answer in one category does not prove success in the others. An organization can possess audit evidence and still have exploitable weaknesses, while a technically mature company may struggle to assemble documentation quickly.
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The report’s main findings
| Finding | What it means |
|---|---|
| 67% said their security and compliance measures needed improvement. | A self-reported perception, not an independent audit result. |
| 46% rated their risk visibility as strong. | Fewer than half of respondents expressed high confidence in visibility. |
| 7.5 hours per week was the average time spent achieving or maintaining compliance. | Vanta describes the survey estimate as roughly 360 hours annually; the figure was not a time-and-motion study. |
| Respondents expected automation to save about two hours per week, or approximately 96 hours per year. | Expected savings, not measured customer results. |
| 83% were increasing or planned to increase their use of automation. | A stated intention, not product-adoption telemetry. |
| 70% said stronger security and compliance could improve business performance. | Perceived benefits such as customer trust, not a causal revenue analysis. |
| About 39% identified identity and access management as a blind spot. | A reported area of concern in VentureBeat’s account of the report. |
| IT-security spending averaged about 9% of IT budgets. | A survey-reported allocation; organizations define and classify budgets differently. |
| One in eight respondents reportedly could not provide security and compliance evidence when asked. | Indicates a documentation and trust-review problem, not proof that controls were absent. |
Vanta’s first-party announcement and the full report are available at Vanta’s State of Trust announcement and the 2023 report download. VentureBeat’s original news account was published on November 8, 2023.
Why teams turn to trust-management automation
Compliance programs become labor-intensive when evidence is scattered across identity providers, cloud consoles, HR systems, ticketing tools, endpoint platforms, code repositories and spreadsheets. The workload also rises when a company supports several frameworks, answers customer questionnaires or reviews hundreds of suppliers.
Automation is most valuable when it turns recurring, structured work into monitored workflows. It does not remove the need to decide which systems are in scope, assign control owners or judge whether a control works in context.
What “AI-powered trust management” does in practice
Evidence collection and monitoring
Connectors can collect machine-readable evidence and test conditions such as multifactor authentication, access reviews, employee onboarding and offboarding, cloud configuration, vulnerability-management records, backups, logging, change management and security-training completion. Continuous checks can flag a changed configuration or overdue task instead of waiting for an audit scramble.
Policies and control mapping
AI features may search policies, controls, tests and evidence; draft or update policy language; summarize changes; and map one control library to multiple frameworks. Mapping can reduce duplicate work, but a shared label does not make SOC 2, ISO 27001, HIPAA, PCI DSS and internal requirements identical.
Questionnaires and customer reviews
Platforms can reuse approved information to draft answers to security questionnaires and direct prospects to a Trust Center. This is useful when sales and security teams repeatedly answer the same questions. Every material response still needs an accountable reviewer.
Vendor-risk workflows
Automation can distribute questionnaires, organize supplier evidence, score risk, identify overdue reviews and route exceptions. It is particularly useful for a small team managing a large vendor population.
Trust Centers
Vanta launched its Trust Center alongside the report after acquiring Trustpage. Vanta said a Trust Center could reduce deal cycles by 30%; that is a vendor claim and is not independently validated by the sources cited here. Public disclosure should be balanced against the risk of revealing infrastructure details, response procedures or exceptions. NDA-gated access, role-based permissions, watermarking and document versioning can reduce that exposure.
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- Offboarding: a workflow can compare HR departures with identity-provider accounts and create remediation tasks for accounts that remain active.
- Access reviews: scheduled evidence can show reviewers which users, groups and privileges existed at a defined time.
- Cloud controls: connected environments can provide recurring evidence for encryption, logging, network settings or backup configuration.
- Questionnaires: approved answers and source documents can produce a first draft rather than a blank spreadsheet.
- Vendor reviews: reminders, scoring and escalation can prevent supplier assessments from quietly expiring.
- Audit preparation: an evidence trail with timestamps and owners can expose missing items before an auditor requests them.
What AI cannot close by itself
A green automated check proves only that a connected system reported an expected state. It does not establish that every relevant asset was connected, that the scope was configured correctly, that the control was effective or that the underlying data was accurate.
- Security architecture, identity design and safe custom applications still require qualified engineering judgment.
- Risk acceptance, exceptions and compensating controls require an authorized decision-maker.
- Physical safeguards, employee behavior and incident response cannot be reduced to a dashboard status.
- Privacy-law interpretation and complex regulatory judgments require legal, privacy or compliance expertise.
- Evidence can be incomplete, stale or manipulated; human validation remains necessary.
- An automated platform cannot provide the independence or assurance of an external auditor.
AI-generated questionnaire answers also create procurement and legal risk if they are outdated or overbroad. A sound workflow shows the source for each answer, records who approved it and prevents autonomous sending of material representations.
How to evaluate Vanta or an alternative
- Define scope first. List products, entities, regions, systems, data types and frameworks before comparing feature lists.
- Test integration coverage. Include cloud, identity, HR, endpoint, ticketing, code and data systems, plus legacy, on-premises, acquired or shadow environments.
- Inspect evidence provenance. Ask how often tests run, whether history and timestamps are preserved, and whether auditors can inspect the trail.
- Require human-review controls. Verify approval gates, source citations, exception handling, compensating controls, audit logs and the ability to limit autonomous actions.
- Check framework and entity support. Confirm current mappings, custom controls, multiple business units and regional requirements.
- Review technical and data terms. Assess SSO, SCIM, RBAC, APIs, data residency, retention, subprocessors, model providers and whether security evidence is used for model training.
- Run a representative proof of concept. Connect real systems, validate sample evidence and test AI-generated questionnaire responses with an auditor or control owner.
- Calculate total cost. Include licenses, modules, implementation, consulting, auditor fees, integration maintenance and the internal time needed to correct inaccurate evidence.
Current commercial signals for common platforms
Product packaging and pricing change, so treat these as buying signals observed around August 18, 2026 rather than permanent terms.
| Platform | Positioning and pricing signal | Potential fit |
|---|---|---|
| Vanta | Compliance, risk, evidence, questionnaires and Trust Center features. Standard dollar prices were not displayed; personalized pricing is requested. | Teams wanting compliance, risk and customer-trust workflows together. |
| Secureframe | Fundamentals listed as starting at $5,000 per year; Complete and Defense are quote-based. | Buyers wanting a public entry-price signal or CMMC-focused Defense workflows. |
| Drata | Compliance automation and audit-readiness platform; verifiable public pricing was not available in the supplied material. | Organizations prioritizing common frameworks and audit preparation. |
| Sprinto | Compliance automation for growing companies; pricing was not verified in the supplied material. | Startups and growth companies seeking guided implementation. |
| OneTrust | Broader enterprise GRC, privacy, risk and governance; pricing was not verified in the supplied material. | Large organizations needing privacy and governance breadth beyond certification automation. |
The practical verdict
Vanta’s 2023 evidence supports a clear but limited conclusion: teams reported weak visibility and too much repetitive compliance work, and many expected automation to help. AI-assisted trust management can close process and documentation gaps, accelerate reviews and surface some control problems.
It cannot independently close security-risk gaps. Organizations still need complete asset scope, sound controls, responsible owners, careful review of generated content, engineering work, governance and—where required—independent assurance. The best buying test is therefore not whether a platform says “AI,” but whether it produces trustworthy evidence from your actual systems while keeping consequential decisions under accountable human control.
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