The GRC Skills Gap Is Real: Automating SOC 2 Evidence Collection with Screenshots (Average Skill 5.4/10)
The State of GRC 2026 survey reveals the average compliance practitioner's technical skill is 5.4 out of 10. This explains why teams struggle with SOC 2 evidence automation. When platforms require custom API scripts to capture screenshots and documentation, mid-skill practitioners get stuck.

Preparing for a SOC 2 audit requires concrete evidence that your controls actually operate as designed. While basic infrastructure checks are relatively straightforward, capturing application-level screenshots and workflow documentation remains a massive bottleneck for most teams.
The industry assumes the solution to this problem is simply buying more automation software. But we are ignoring the root cause of why these implementations fail. The people managing compliance tools do not always have the technical background required to configure them.
According to The State of GRC 2026 report by Ayoub Fandi at GRC Engineer, the average technical skill of a compliance practitioner is just 5.4 out of 10. This single data point explains why so many organizations buy expensive platforms but still spend weeks manually dragging and dropping files into folders before an audit.
What Does the GRC Skills Gap Actually Look Like?
The State of GRC 2026 survey polled 795 practitioners, making it the largest independent dataset on how compliance professionals actually work. When asked to rate their technical skills on a 1-to-10 scale, the results revealed a massive, underserved middle class in the compliance industry.
The median score is 5.5. The distribution breaks down into three distinct groups:
- Low (1-3): 20.5% of practitioners
- Mid (4-6): 50.4% of practitioners
- High (7-10): 29.1% of practitioners
Half of the industry sits right in the middle. A practitioner with a 5.4 skill level knows exactly what an auditor wants. They understand SOC 2 Trust Services Criteria, they know how to map controls, and they can navigate a commercial GRC platform's user interface.
What they cannot do is write a Python script to query a custom internal database, configure a complex Jira webhook to trigger upon a specific deployment status, or write policy-as-code rules.
Why Does the Flat Seniority Ladder Prevent Technical Growth?
You might assume that as practitioners get promoted, their technical skills improve. The data proves this false. The GRC career ladder is almost entirely flat regarding technical capability.
| Seniority Level | Average Technical Skill (Out of 10) |
|---|---|
| Entry Level | 3.9 |
| Intermediate | 5.1 |
| Manager | 5.2 |
| Senior Manager | 5.0 |
| Director | 5.4 |
| CISO / VP+ | 6.5 |
A practitioner can experience a full decade of career progression—moving from an intermediate analyst to a Senior Manager—and their technical skill will actually drop slightly from 5.1 to 5.0. Promotion in compliance is tied to risk management, stakeholder communication, and project management. It is almost never tied to technical execution.
The only significant jump happens at the CISO level (6.5). But this is a composition issue, not an upskilling issue. CISOs score higher because they usually cross over from security engineering backgrounds, not because they climbed the traditional audit ladder.
This creates a structural problem for the industry. We have a workforce that manages highly technical audits but lacks the engineering background to automate the evidence collection themselves.
How Does the Skills Gap Affect SOC 2 Evidence Collection?
The skills gap manifests as a "capability gap" during audit preparation.
According to the survey, 62.3% of mid-skill practitioners already own a commercial compliance tool. They have the budget. They bought the software. But they cannot unlock its full value.
Take SOC 2 CC6.1 (Logical Access). Your auditor needs evidence that access to your production environment is restricted and reviewed quarterly. If you use a standard identity provider like Okta, your compliance platform might pull that data automatically via API.
But what if you have a proprietary admin panel for customer support? Or a legacy application that doesn't support SSO?
To automate that evidence in a traditional platform, you have to build a custom API integration. The platform expects the user to read API documentation, generate tokens, and write a script to format the JSON response so the tool can digest it.
A practitioner with a 5.4 technical skill hits a wall here. They look at the API documentation, realize they need engineering help, and submit a Jira ticket. The engineering team ignores the ticket because they are shipping product features. Three weeks before the audit, the compliance manager gives up, logs into the admin panel, takes a screenshot, and pastes it into a Word document.
The tool didn't fail. The user didn't fail. The vendor built a product for a persona that doesn't exist in the average compliance department.
Where Traditional SOC 2 Automation Stops
This disconnect defines where traditional SOC 2 automation stops. Platforms like Drata and Vanta are exceptional at monitoring cloud infrastructure. They connect to AWS, check if your S3 buckets are encrypted, and turn a dashboard widget green.
But cloud infrastructure is only one part of an audit. Auditors also require proof of human processes and application-level controls. They want to see the actual interface where a manager approved a pull request (CC7.2). They want to see the exact settings page where MFA is enforced for your specific internal tool.
When APIs cannot reach these application-level workflows, traditional GRC platforms require you to build custom integrations. This is where the persona cliff becomes obvious.
At a skill level of 8 or higher, a security engineer will just write the custom integration. They might even bypass the commercial tool entirely and build their own open-source solution. But for the 50.4% of the market sitting at a 5.4 skill level, a custom integration is a dead end.
Because they cannot bridge this gap with code, they bridge it with manual labor. They spend 80 hours a year capturing screenshots, redacting sensitive customer data, formatting PDFs, and mapping those files back to control IDs.
How Can Mid-Skill Teams Automate Evidence Without Engineering Help?
If the average compliance professional is a 5.4 out of 10, the software they use should be designed for a 5.4 out of 10. We cannot expect the entire industry to suddenly learn how to write Python scripts.
The solution is shifting the technical burden away from the user and onto the tool. Instead of requiring API integrations for custom applications, modern compliance tools use AI agents to replicate what the auditor actually wants to see: the user interface.
When an auditor asks for evidence of an access review, they are perfectly happy with a timestamped screenshot showing the user list and the reviewer's approval.
Tools like Screenata automate this exact process. Instead of writing code, the compliance manager simply records themselves performing the control test once. The AI agent learns the workflow, navigates the interface, captures the necessary screenshots automatically, redacts sensitive information, and generates a formatted PDF evidence pack.
This approach matches the reality of the GRC workforce. It allows a practitioner with average technical skills to achieve the same level of automation as a senior security engineer, without writing a single line of code or begging the engineering team for API favors.
The GRC skills gap is real, and it isn't going away. The vendors who win will be the ones who stop building tools for the engineers they wish were running compliance, and start building tools for the practitioners who actually are.
Learn More About GRC Platform Integration
For a complete guide on how to bridge the gap between your existing tools and the reality of manual evidence, see our guide on integrating application-level evidence automation with Drata, Vanta, and GRC platforms, including how to capture the exact UI screenshots your auditors require without writing custom API scripts.
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