Do periodic, manually assembled access reviews and related audits still provide credible assurance in IT environments that change rapidly?
Large organizations are dealing with hybrid infrastructure, sprawling SaaS estates, inherited systems, contractor churn, internal role changes, and continuing workforce reductions. At the same time, the identity surface is widening to include service accounts, application identities, OAuth-connected services, and AI agents. The review model many teams still rely on was built for a smaller, slower, more legible environment than the one they have now. For GRC professionals at large enterprises, this is familiar ground.
GRC and cybersecurity leaders are often accountable for access and control outcomes across systems run by IT, engineering, DevOps, cloud teams, and business owners. They’re being asked to stand behind claims they did not personally implement and often cannot directly verify from current system reality.
The risk isn’t just missing a review, but it’s being left to defend stale or weak evidence after an audit challenge, customer escalation, or breach.
Key Takeaways for Access Reviews
| Challenge | Traditional Approach | Modern Solution |
|---|---|---|
| Evidence Freshness | Point-in-time, manual collection (spreadsheets) | Continuous, machine-verifiable evidence capture |
| Identity Scope | Focus on human employees/contractors | Includes non-human identities (Service Accounts, AI Agents) |
| Audit Efficiency | Redundant evidence gathering per framework | Centralized evidence layer mapped to multiple frameworks |
Periodic access reviews produce stale evidence
A quarterly or annual review can look complete on paper and still be weak as assurance.
Permissions change. Teams reorganize. Managers leave. Contractors roll on and off projects. Cloud configurations shift. Identity policies get updated. Privileged access expands temporarily and then never gets revoked. By the time a reviewer gets a spreadsheet, an exported user list, or a segmented set of screenshots, some of what they are looking at may already be old. That turns access certification into a historical exercise. It gives the organization the appearance of control without the same level of confidence.
In many enterprises, that still means exporting user and entitlement data from multiple systems into spreadsheets, routing those files to managers or application owners for signoff, then chasing down questions, exceptions, and missing context over email, tickets, and meetings. By the time responses come back, some of the access picture has already changed. Any resulting review decisions may still have to be translated into manual cleanup steps across different systems.
That is one reason periodic access reviews often are harder than they look on paper. The review itself is only one part of the work. The real effort sits in assembling the data, validating who owns what, interpreting what a reviewer is actually being asked to approve, and then making sure any resulting action is carried through.
That’s why access reviews are becoming part of a broader continuous assurance conversation.
The deeper problem is not review cadence by itself. The deeper problem is the gap between how quickly access conditions change and how slowly many organizations verify them.
Ayoub Fandi describes the situation:
“I could just call an API and get the data every week or every day if I wanted to, which meant I could monitor like how things were operating more on a continuous basis instead of like once or twice a year”
That line gets to the heart of it. The technical signals already exist in many environments. The challenge is whether the GRC operating model is built to use them in a timely, repeatable, defensible way.
Passed access reviews can hide live systems risk
A clean quarterly review does not help much if privilege drift began months earlier. A completed certification does not carry enough weight if the underlying evidence is stale. And a ‘passed’ control can quickly become difficult to defend when an incident, audit question, or executive review forces the team to explain what was true outside the audit window.
A review may show that access was appropriate at the moment evidence was assembled. That does not mean the same access remains appropriate now. In fast-moving environments, the lag between change and verification matters.
Abhay Kshirsagar captures the issue well:
“You have near real checks so that it's not like if the control fails in February you'll get to know that in August because that's when you do the audit. That's wrong, right? You want the moment a control fails that it's flagged, so you're going in and remediating that right away.”
The same logic applies to access assurance.
There is also a quality problem hidden inside many completed reviews. When managers are asked to assess large volumes of access with too little context and too little time, the exercise can become fast approval rather than real scrutiny. A completed certification is not the same as meaningful assurance if the reviewer never had enough clarity to make a strong decision.
This is one reason the GRC focus is shifting from visibility to verification.
Dashboards, monitoring, and centralized views have value. But observation and verification are different things.
Observation shows signals.
Verification produces evidence that can be traced back to source systems and explained under scrutiny.
That distinction matters more as enterprises rely on assurance data for audits, customer commitments, board reporting, and incident response.
Better evidence for auditors also helps GRC and security leaders explain residual risk to executives and boards with more confidence.
Layoffs, reorganizations, and inherited complexity make access reviews harder
The increasing ease and speed that people, processes and technology can change adds more pressure.
Large enterprises are still cutting roles, consolidating teams, flattening management layers, and shifting budgets toward efficiency and AI-related priorities. In that kind of environment, identity governance gets harder for structural reasons. Approver chains change. Ownership becomes less clear. People inherit systems they did not implement. Teams certify access for users, applications, or environments they only partly understand. Recent broad corporate job cuts have kept that pressure very real across large organizations.
This raises serious security risks:
- Delayed deprovisioning
- Orphaned access
- Stale approvals
- Privilege accumulation
It also exposes a practical weakness in many review programs: they still assume stable managers, stable teams, and stable system boundaries.
Large enterprises rarely have that luxury. Access control reality is spread across cloud, on-prem, SaaS, identity systems, CI/CD pipelines, and inherited workflows that do not line up neatly. Standardized review processes tend to break at exactly those seams.
The problem goes well beyond review administration as a lot of the work happens outside the review itself.
Engineering and security teams get pulled into repeat evidence requests.
GRC teams spend time reconstructing proof instead of working from current evidence.
GRC and Security leaders are left to make commitments from information they may not fully trust outside audit windows.
In most enterprises, the evidence needed to explain access and control behavior is spread across identity platforms, cloud environments, security tools, ticketing systems, and audit workflows. Beyond the challenge of just collecting it, the hard part is correlating it into a coherent, traceable account of what was true, what changed, and whether the control is working.
Ayoub Fandi said it directly:
“By having an engineering approach, what you do is, like, you acknowledge that your GRC work is creating toil for everyone else”
That’s a useful way to see the issue. Manual access assurance does not just consume GRC time. It spills friction into adjacent teams across the enterprise.
Access reviews now need to cover non-human identities and AI agents
Many access review programs still center on employees, contractors, and privileged human users.
Today, that is no longer enough. We have to consider non-human entities that can hold broad permissions across enterprise systems, often with persistent access and weaker day-to-day visibility.
- Service accounts
- Application identities
- OAuth-connected services
- Agents
Microsoft’s current Defender guidance explicitly treats these non-human identities as material security subjects because they can hold elevated permissions and access sensitive resources.
Cloud Security Alliance reported this week that 68% of organizations cannot clearly distinguish AI-agent activity from human activity.
That changes the scope of access assurance.
A modern access review program has to ask more than WHO has access. It has to ask:
- Which identities are active
- What they can do
- Who owns them
- Whether that access still reflects current business need
- How that access is monitored over time.
The governance principle is straightforward. An AI agent should be treated as an identity with permissions, actions, ownership, and blast radius. Static approval is not enough for that class of access. Continuous verification becomes more important because those identities can act quickly, broadly, and persistently across systems shifts.
| Governance Area | What this means for AI agents | The AI Agent Risk |
|---|---|---|
| Identity status | An AI agent should be treated as a real identity in the environment, not as a background feature or simple automation | It may be active across systems while escaping the same scrutiny applied to human users and service accounts |
| Access permissions | The agent’s permissions should be explicitly defined, limited, and tied to a valid business purpose | Excess or poorly scoped access can give the agent reach far beyond what its task requires |
| Allowed actions | The actions the agent is permitted to take should be clearly bounded | An agent may execute tasks quickly, repeatedly, and across multiple connected systems |
| Human ownership | A named person or team should be accountable for the agent’s access, behavior, and review | Access can persist without meaningful review when ownership is unclear or dispersed |
| Blast radius | The potential downstream impact of the agent’s access and actions should be understood in advance | A highly connected agent can affect data, workflows, controls, and systems well beyond its apparent role |
| Review model | Point-in-time approval should not be treated as sufficient governance | Agent access can drift out of alignment as tools, data sources, workflows, and business needs change |
| Verification method | The agent’s access and activity should be continuously verified against current system reality | Static approval creates false confidence when the agent operates continuously and at machine speed |
The move now is from periodic collection to continuous verification for continuous assurance
Evidence is being captured more continuously. Verification is being designed for reuse. And teams are trying to work from shared context rather than disconnected files and screenshots.
| Shift in operating model | Older approach | Emerging approach | GRC Impact of the New Approach |
|---|---|---|---|
| Evidence collection | Point-in-time collection | Continuous capture | Evidence is more likely to reflect current conditions rather than a delayed snapshot |
| Verification | Repeated evidence requests | Reusable verification | Teams do not have to recreate similar proof across reviews, frameworks, and audit cycles |
| Evidence handling | Disconnected spreadsheets and screenshots | Shared operational context | Evidence becomes easier to trace, interpret, and act on across teams |
This shift matters for access reviews because most enterprises already generate the underlying signals. Identity and access logs exist. Policy changes happen in systems. Privileged access events leave traces. CI/CD and infrastructure changes create timestamps and state changes. The challenge is rarely the absence of raw data. The challenge is turning that data into current, traceable, machine-verifiable evidence that can support assurance.
The same access evidence rarely answers to just one framework. It may need to support PCI DSS, DORA, NIS2, internal policy, customer reviews, and audit questions at the same time. That’s why a current evidence layer and reusable verification matter. They also make it easier to absorb new requirements as they arrive, including proposed changes such as the HIPAA Security Rule updates, instead of pushing teams back into another round of manual evidence collection.
Trupti Shiralkar described the direction clearly:
“Instead of reaching out for, you know let's say compliance evidence, how can we autogenerate that evidence so that we don't even have to bother our people”
That does not eliminate human judgment. It changes where judgment is used.
Mosi Platt made that point well:
“I think the value of it comes from elevating people to a higher level of work so for example instead of just collecting - like the mundane task of collecting evidence - from a system to elevate them to doing evaluation of the evidence”
That is the better model for large-enterprise GRC. Less energy spent chasing proof. More energy spent evaluating risk, exceptions, remediation, and control health.
Traceable control evidence improves audit defensibility
For access reviews, the practical goal is no longer just to complete a review cycle.
IT’s to maintain defensible assurance that can answer a tougher set of questions:
- Does this identity still have a valid business reason for its current access?
- Can that access be traced to live system behavior and current policy state?
- Is ownership clear?
- Would this evidence still hold up outside the audit window?
- Does the same verification logic cover overlapping frameworks without sending teams back through the same collection loop again?
That’s a more serious standard and also the one large enterprises increasingly need.
Where ComplianceCow fits as Security GRC requirements evolve: a verification and evidence layer
Most enterprise teams already have GRC platforms like ServiceNow, Optro (formerly AuditBoard), and Archer as systems of record for governance, along with identity platforms, ticketing systems, cloud infrastructure, collaboration tools, and audit workflows.
Many enterprises also use IGA platforms such as SailPoint and Saviynt to manage identity lifecycle, access policy, and certification workflow. But IGA mainly governs who should have access, how that access is requested or approved, and how review campaigns are administered. It does not, by itself, solve the broader evidence problem of proving from current system reality that access and related controls are working as intended across the environment.
What is still often missing, especially in proprietary, on-prem, and hybrid environments that templated automations cannot handle, is a way to evaluate live control behavior, trace the resulting evidence back to source systems, and feed verified results into the workflows and platforms the organization already uses. In access assurance, that gap tends to show up in a few familiar ways:
- Evidence goes stale because it is separated from the live systems it is meant to represent.
- Teams reconstruct proof by hand across GRC, security, engineering, and system owners.
- Non-human identities, connected services, and AI agents sit outside a review model built mainly for people.
- Overlapping frameworks and audit requests trigger repeated collection work against the same underlying controls.
ComplianceCow fits in that gap as a verification and evidence layer between operational systems, including IGA, and the GRC system of record. For access assurance, that means keeping evidence closer to the live environment, producing verification that traces back to source systems, reducing repeated manual collection across teams, extending review coverage beyond human users, and making the same underlying verification more reusable across audit and compliance demands.
The result is access review evidence that is current, traceable, and more defensible when auditors, regulators, or internal stakeholders ask teams to show how access is actually being controlled.
Periodic access reviews no longer provide enough assurance
Periodic access reviews are still necessary.
They are no longer enough on their own. Enterprises today are too fast-changing.
What’s needed now is maintaining current, defensible assurance across a mixed population of human and non-human identities, in environments where ownership shifts, access changes quickly, and stale evidence creates false confidence. That is why access reviews are becoming part of a larger move toward continuous verification and machine-verifiable evidence.
The teams getting ahead of this are treating access assurance as a real-time operational systems control problem.
That matters not only for compliance operations, but for the people who have to stand behind those claims when an auditor, customer, executive, or board member asks how current and defensible the evidence really is.
Frequently Asked Questions (FAQ)
Why do traditional access reviews fail in modern IT environments?
Traditional access reviews rely on point-in-time snapshots and manual spreadsheet tracking. In rapidly changing hybrid clouds and SaaS estates, this creates stale evidence, masking privilege drift and leaving organizations vulnerable between audit cycles.
How should non-human identities and AI agents be audited?
Non-human identities should be treated like human users, requiring explicit boundaries, business justification, and human ownership. Because they operate continuously at machine speed, static point-in-time approval is insufficient; they require continuous verification.
What is continuous control verification?
Continuous control verification replaces manual evidence collection by automatically monitoring and validating security controls in real-time. This provides current, traceable evidence that can be reused across frameworks like SOC 2, HIPAA, and PCI-DSS without redundant effort.
Regulations Reference Footnotes:
(1) PCI Security Standards Council, PCI Data Security Standard (PCI DSS). https://www.pcisecuritystandards.org/standards/pci-dss/
(2) European Union, Regulation (EU) 2022/2554 on digital operational resilience for the financial sector (DORA). https://eur-lex.europa.eu/eli/reg/2022/2554/oj
(3) European Union, Directive (EU) 2022/2555 on measures for a high common level of cybersecurity across the Union (NIS2 Directive). https://eur-lex.europa.eu/eli/dir/2022/2555/oj/eng
(4) U.S. Federal Register, HIPAA Security Rule To Strengthen the Cybersecurity of Electronic Protected Health Information (proposed rule). https://www.federalregister.gov/documents/2025/01/06/2024-30983/hipaa-security-rule-to-strengthen-the-cybersecurity-of-electronic-protected-health-information