Third-party risk management (TPRM) teams rely on assurance reports to help evaluate vendors, suppliers, and business partners. But having an assurance report is not the same as having the information needed to make a risk decision.

That distinction was at the center of The Assurance Gap: What 103 SOC 2 Reports Actually Showed Us, a recent HITRUST webinar featuring  AJ Yawn, Author and GRC Engineering Lead at Rippling, and HITRUST's Ryan Patrick. The conversation explored findings from an analysis of more than 100 SOC 2 reports and asked a fundamental question: Are the assurance reports organizations rely on actually providing visibility into the risks that matter most?

That analysis is now detailed in The Assurance Gap, a new HITRUST paper.

The purpose of the analysis is not to suggest that SOC 2 has no value. A SOC 2 Type 2 report can provide detailed information about a service organization, its controls, testing, and identified exceptions. But the flexibility inherent in SOC 2 also means that scope, control selection, testing, and other elements can vary from report to report.

For organizations relying on those reports to make third-party risk decisions, understanding what the report actually provides is critical.

Ransomware recovery requires more than a report label

One of the findings Ryan highlighted during the webinar was particularly stark: 0% of the sampled SOC 2 reports included an organizational control requiring offline or immutable backups.

Offline or immutable backups can play an important role in recovering from ransomware by helping organizations restore data without relying on backups that may also have been compromised.

The issue for a report recipient is visibility. The absence of an offline or immutable backup control from a SOC 2 report does not mean the organization does not have those backups. It means the report does not provide evidence that allows the recipient to confirm the control.

That distinction becomes especially important when an organization is using the report to evaluate a third party. If ransomware affects a critical vendor, the TPRM team needs to understand whether that vendor can respond and recover. If the assurance artifact does not address a control that is material to that decision, additional evidence may be necessary.

During the webinar, Ryan and AJ also connected several of the findings as parts of the same potential attack chain. Phishing may provide an initial entry point. Multi-factor authentication can help prevent compromised credentials from being used. If ransomware is ultimately deployed, recovery capabilities such as offline or immutable backups become critical.

Yet the analysis found gaps in the visibility provided by the sampled reports across each of those areas.

Phishing remains persistent, but assurance coverage was limited

Of the 103 SOC 2 reports analyzed, only 7% included a control for dedicated phishing training or simulations, while only 5% included a prescriptive control requiring an email filtering solution to block suspicious emails and unnecessary file types before they reached employee inboxes.

Only 1% included controls addressing both requirements.

This does not mean the organizations represented in the sample were not conducting general security awareness training. In fact, the analysis found that most included general security awareness training. What was far less common was explicit coverage of dedicated phishing training, simulations, and preventive email filtering controls.

AJ focused on that distinction during the webinar. Phishing is not a new or obscure cyber risk. It is a well-understood threat, which makes the limited visibility in the sampled reports especially important for organizations relying on those reports to make third-party risk decisions.

As AJ put it during the discussion, if organizations are trusting third-party reports to make decisions, those reports should at a minimum be relevant to the existing threat landscape.

That is the broader issue behind the findings. Cyber threats continue to evolve. Assurance must provide enough relevant evidence for recipients to understand whether controls addressing those threats are actually included and validated.

What does the report actually allow you to conclude?

The ransomware and phishing findings point to a larger question: What risk decision is the assurance report actually supporting?

Organizations often need assurance artifacts because evaluating every control at every vendor independently is not scalable. A reusable assurance report can reduce significant duplication for both vendors and TPRM teams.

But reuse only works when the artifact is fit for the decision.

The burden is placed on the person consuming the report. That person must determine what was tested, whether it is relevant, and whether the report provides the information needed to make a risk decision. For teams responsible for hundreds or thousands of third parties, performing that level of interpretation across every report can quickly become difficult to scale.

This is where the assurance gap emerges. A familiar report label can create confidence, but the underlying evidence may not necessarily address the service, threat, dependency, or risk decision that matters to the recipient.

The Assurance Gap paper outlines five questions organizations can use when evaluating any assurance artifact:

• Does the scope cover the provided service?
• Is the assurance responsive to the expected risks and threats?
• Who prepared and quality reviewed the work?
• What service providers are included, and are they assessed?
• Can two reports be measurably compared?

These questions shift the focus from whether a vendor simply has an assurance report to whether the evidence in that report is sufficient for the decision being made.

Move from assurance labels to evidence that supports the decision

SOC 2, HITRUST, ISO 27001, PCI DSS, NIST CSF, questionnaires, and other assurance mechanisms were designed for different purposes. Treating them as interchangeable can create gaps between what an organization believes has been validated and what the underlying evidence actually supports.

The goal is not to collect more assurance artifacts. It is to understand what each artifact proves, what it leaves open, and whether additional evidence is necessary.

The Assurance Gap expands on the findings discussed by AJ and Ryan, including threat-landscape coverage, quality, supply chain coverage, measurable outcomes, and the questions TPRM teams can use to evaluate the evidence they rely on.

Download The Assurance Gap to explore the complete analysis and learn how to identify where assurance may fall short of the risk decision you need to make.

Introduction

For years, sharing a HITRUST assessment report has been a manual exercise. An organization earns its certification, then spends time downloading files, attaching them to emails, and uploading them to portals, one recipient at a time. As the list of teams and individuals asking for reports grows, so does the administrative burden, and so does the difficulty of knowing who has which report and version.

Report Center gives assessed organizations a controlled, secure, and trusted way to share assessment status and reports with third-party risk management (TPRM) teams, compliance stakeholders, and other approved recipients.

Report Center replaces manual report sharing with a streamlined, secure, trusted way to share HITRUST assessment status and authorized reports, straight from the source you trust.

What is HITRUST Report Center?

Report Center is a secure online location for sharing HITRUST assessment status and authorized assessment reports. Every HITRUST assessment now has its own Report Center dashboard that displays key details, including the assessed organization name, assessment name and type, assessment status, certification status, report and expiration dates, and a brief assessment scope. Where applicable, the dashboard also references associated Insights Reports and additional certifications, such as the AI Security Assessment and Certification and NIST 2.0 Certification.

Assessed organizations manage everything from the Report Center Access Administration page in MyCSF. From there, admins can invite recipients to a dashboard, review and approve or deny access requests, choose which reports each recipient may download, update report-level permissions, and revoke access at any time. Recipients reach the dashboard through a Completion Letter link, a QR code, or a direct invitation, then register or sign in to view assessment status and download the reports they have been approved to access.

As part of this release, HITRUST is also simplifying report types. Going forward, HITRUST issues two primary reports: the Certification Summary, a shorter report confirming the assessment outcome with enough scope to judge relevance, and the Certification Report, the full assessment report with scope, results, and supporting content. Access is granted by report type, so each recipient sees only the level of detail they need. More details are available in HITRUST Advisory HAA 2026-004.

Why Report Center matters

Report Center is built around three ideas that address the real friction in report sharing today.

• Streamlined report sharing
  Automated dashboards and on-demand access requests replace manual email and file transfers, so sharing a report is a matter of granting access rather than juggling emails, attachments, and tracking spreadsheets.
• Centralized control and visibility
  A single, unified view shows who has access to which reports and versions, giving organizations control even as their ecosystem grows more complex.
• Report security and trust
  Every report downloaded from Report Center comes directly from HITRUST and is watermarked with recipient-specific details, reinforcing authenticity and creating an accountable, traceable distribution model.
• Less manual work
  Share assessment information without relying on manual methods like email and file transfers.
• Granular access management
  Approve or deny requests, set report-level permissions, and modify or revoke access at any time, so only the right recipients see the right reports and versions.
• Improved governance and accountability
  Centralized access management and watermarked downloads strengthen accountability and give a clear record of how assessment information is distributed.
• One place to request and access reports
  A centralized dashboard replaces chasing PDFs forwarded over email, with on-demand access to the reports shared with you.
• Confidence in authenticity and currency
  Reports come straight from HITRUST, and the dashboard shows current assessment and certification status tied directly to the correct assessment, not a possibly outdated file.
• Clear scope to judge relevance
  The Certification Summary and Certification Report provide enough scope detail to determine whether the assessed services, systems, or environments are relevant to your risk decisions.

Learn more and get started

Whether you are an assessed organization looking to streamline how you share your results, or a an organization that depends on HITRUST reports to manage third-party risk, Report Center offers a faster, more secure, and more trustworthy path.

Ready to see it in action? Connect with HITRUST to learn how Report Center fits into your assessment and report-sharing workflow.

Key Takeaways

• AI risk in regulated industries requires governance and controls that protect confidentiality, integrity, and availability of AI systems and the underlying infrastructure.

• AI systems need clear ownership, review based on risk, secure limits on data and access, human oversight for important actions, and ongoing monitoring.

• Agentic AI needs tighter safeguards because it may access enterprise data, use business systems, and take action with increasing autonomy.

Introduction

AI is moving from experimentation into the work that regulated organizations rely on every day. For example, healthcare organizations use AI systems to support documentation, communications, coding, and operations. Financial services firms apply it to fraud detection, identity verification, customer service, and internal work. Business services firms are embedding it in client delivery, research, analysis, and knowledge work.

When AI systems handle sensitive information, influence business decisions, or connect to enterprise applications, they create new cybersecurity risks and new challenges for protecting information. In simple terms, the risk increases when AI has access to sensitive data, can shape decisions, or connect to tools used to run the business. Agentic AI means AI that can do more than answer a question. It can retrieve data, use software tools, and start actions across systems with increasing autonomy, sometimes without a person approving each step.

For leaders in regulated industries, the goal is not to stop adoption. It is to understand the risk, decide what level is acceptable, and apply the right safeguards. AI governance is the way an organization decides where AI can be used, who is responsible for it, and what safeguards are required. A practical governance program should answer three basic questions: Is sensitive information protected? Can people trust the output? Will the system be available when it is needed?

AI Changes the Risk Profile

Existing privacy, cybersecurity, and oversight obligations still apply when an organization adopts AI. It does not replace these responsibilities. It changes how they need to be applied. In practice, AI can introduce new ways for sensitive information to be exposed, business information to be changed, or critical operations to be disrupted. The systems that support AI, such as identity tools, data platforms, and connected applications, also need to be governed and secured.

Confidentiality is about keeping sensitive information from being seen or used in the wrong way. It is at risk whenever sensitive information enters prompts, uploaded documents, retrieval systems, or logs. A connected system may retrieve more information than a task requires, and data may be retained in ways teams don't fully understand. Governance should make clear what data is allowed, is restricted, and prohibited, who can access it, and how use will be monitored.

Integrity is about making sure information and outputs are accurate, complete, and trustworthy. It is at risk when an AI system produces inaccurate, incomplete, manipulated, or misleading output. For example, an AI tool might rely on bad source material, misunderstand a prompt, or be manipulated by an attacker. The risk is greater if the system can update records, create communications, or change a workflow.

Availability is about keeping systems and operations working when people need them. AI systems depend on infrastructure, identity services, data sources, integrations, and applications. A cyberattack, outage, or misconfiguration can quickly become an operational problem. For higher-impact uses, organizations need continuity plans, escalation procedures, and practical ways to keep working safely when AI systems are unavailable.

What Governance Must Do

AI governance turns these decisions into consistent business practices. It starts with a simple inventory, or list, of AI systems and use cases. Organizations need to know where AI is being used, what data it touches, what decisions or actions it influences, and who is accountable for each use.

Risk tiering means grouping AI uses by how much impact they could have. An application used for graphic design is not equivalent to an AI system that processes protected health information, produces customer communications, or supports a financial decision. Higher-impact use cases should require documented approval, security and privacy review, defined human oversight, testing before deployment, ongoing monitoring, and reassessment when the system or workflow changes.

Accountability should be explicit. Each AI use should have a named business owner who is responsible for why the system is used and what outcome it is expected to support. Security, privacy, risk, legal, and compliance teams should define the limits for acceptable use. Employees need clear guidance on what they can use AI for, when they should escalate a concern, and what to do when an AI system produces unexpected results. Governance succeeds when it supports informed adoption rather than merely adding policy documents.

Cybersecurity Focus by Industry

Healthcare: AI governance and security must protect sensitive health information while preserving workflows that support care. Controls should limit exposure of protected health information, require review of AI-generated documentation, coding, patient messaging, and other outputs that may affect a record or care journey, and make sure operations can continue safely if an AI-enabled workflow or connected application is disrupted.

Financial services: Organizations must protect customer and transaction information while managing fraud and operational risk. Controls should prevent inappropriate exposure of account, identity, and transaction data, address impersonation, synthetic identity, manipulated inputs, and misleading AI-generated communications, and plan for disruption to fraud review, customer support, identity verification, and other time-sensitive activities.

Business services: Organizations must protect client trust and confidential work product. Controls should prevent client information, intellectual property, and sensitive personal information from entering unapproved AI systems, require review of AI-generated research, analysis, client materials, and changes to business records, and avoid relying on AI for critical client-delivery processes without a tested alternative.

Managing Agentic AI

Agentic AI needs more deliberate governance because it can interact with data and systems, not just generate content. Organizations must define what information an agent can retrieve, what applications it can access, and what actions it can take. They also need to decide which actions require a person’s approval, who can override or stop the agent, and whether the organization can review the records and determine what happened after an incident.

Least-privilege access is essential. This means an agent should receive only the data and permissions it needs to complete a defined task. IBM’s Cost of a Data Breach Report 2026 makes this abundantly clear. The report indicates that 92% of the organizations that experienced an AI-related breach lacked proper AI access controls!

Actions that could significantly affect customers, records, operations, or transactions should require approval before they happen. The organization should log all important inputs, actions, and outcomes. Organizations also need a tested way to disable or isolate an agent when its behavior is unsafe or unexpected.

Bring Confidence to Your AI Adoption

Strong AI risk management combines governance and security throughout the AI lifecycle, from early planning to day-to-day use. Organizations should identify AI uses, classify their risk, define what data each AI system can use and who can access it, test controls before deployment, monitor for failures and misuse, and reassess systems when their purpose, data, permissions, or connected workflows change.

Putting these practices into operation can be difficult, especially when different teams use different methods to evaluate AI risk. A common risk and security assurance approach can help create consistency.

HITRUST AI Risk Management can support this discipline by helping organizations identify and manage risks across the AI lifecycle. It provides a structured way to connect AI use to accountability, safeguards, and risks to confidentiality, integrity, and availability. HITRUST AI Security Assessment and Certification can help AI system providers demonstrate that their security controls have been independently assessed, validated, and certified.

Together, these approaches support a clear objective for regulated organizations: use AI with the confidence that it is governed, secure, accountable, and resilient. That foundation allows leaders to adopt AI systems in ways that support innovation without compromising the information and operations that matter most.

Reach out today to learn how HITRUST can help your organization manage AI risk and strengthen AI security.