Frustrations Shared By The Cyber Security Community
The FIVE Major Concerns Are:
1. Overlapping Regulations Create Control Confusion
2. Audit Evidence Is Still Manual and Fragile
3. Third-Party Risk Reviews Are Shallow and Manual
4. Risk Registers Feel Disconnected From Reality
5. True Compliance Buy-In Is Hard to Achieve
1. Overlapping Regulations Create Control Confusion
Modern GRC programs operate in a regulatory maze. GDPR, ISO 27001, SOC 2, NIS2, sector-specific rules—the list keeps growing, and the overlaps aren’t clean. The same control may satisfy multiple requirements, yet each framework words it differently.
Teams spend enormous time mapping controls to obligations, often debating interpretation rather than improving security. This creates confusion, slows progress, and increases the risk of gaps or duplication. Instead of focusing on managing risk, GRC teams become translators, constantly reconciling frameworks that were never designed to work neatly together.
2. Audit Evidence Is Still Manual and Fragile
Despite advances in security tooling, audit evidence collection often feels stuck in the past. Screenshots are emailed, spreadsheets are manually updated, and folders multiply across shared drives.
This approach is fragile and stressful, especially as audit deadlines approach. One missing file or outdated screenshot can trigger last-minute scrambles and uncomfortable conversations. Worse, the process depends heavily on individual knowledge and heroics rather than repeatable systems. When key people are unavailable, evidence gathering slows or breaks entirely, exposing how brittle many GRC processes really are.
3. Third-Party Risk Reviews Are Shallow and Manual
Everyone knows third parties represent significant risk—yet assessments rarely reflect that reality. Questionnaires are long, generic, and often completed with optimistic answers.
Reviews become checkbox exercises rather than meaningful evaluations. With hundreds or thousands of vendors, teams simply don’t have the time to go deep. As a result, assessments remain superficial, offering limited insight into real exposure. When a breach occurs through a supplier, hindsight makes the weakness painfully obvious: the risk was “assessed,” but not truly understood.
4. Risk Registers Feel Disconnected From Reality
Risk registers are meant to guide decision-making, yet they often feel abstract. Risks are described in high-level language, scored subjectively, and updated infrequently.
Meanwhile, security operations deal with concrete alerts, incidents, and vulnerabilities every day. When the two worlds don’t connect, risk management loses credibility. Operational teams don’t see how their work influences risk posture, and leadership doesn’t see how risks map to real-world activity. The register becomes a reporting artifact rather than a living management tool.
5. True Compliance Buy-In Is Hard to Achieve
Perhaps the hardest challenge in GRC is culture. Policies can be written, controls documented, and training completed—but genuine buy-in is elusive.
Many employees view compliance as something to “get through” rather than something that protects the business. Without clear relevance to daily work, controls feel imposed rather than shared. This mindset leads to minimal adherence and quiet workarounds. Changing that requires consistent messaging, leadership example, and showing how governance and risk management support, rather than hinder, real business goals.
A Question Back to the Community
These frustrations reflect a foundational tension in governance, risk, and compliance (GRC).
Traditional GRC frameworks remain essential, but they are misaligned with the unique risks, pace, and opacity of AI systems—from ethical risks that fall outside traditional controls to supply-chain vulnerabilities and the unpredictable nature of black-box models.
The gap between the rapid deployment of AI technologies and the evolution of compliance standards, audit procedures, and risk quantification frameworks is widening.
GRC professionals navigate this uncertainty daily, balancing innovation with accountability.
So the pivotal question is this: do these AI GRC challenges resonate with your governance experience?
Are these the central concerns—or are there other critical gaps the community should prioritize, such as developing transparent AI audit trails, establishing ownership for AI risk, adapting third-party risk management for AI-as-a-Service, or creating measurable ethical compliance metrics?
As AI becomes integrated into regulated industries, these conversations will define whether our governance frameworks act as effective guardrails or merely as retrospective documentation of failure. They shape whether innovation proceeds with accountability or exposes organizations to unprecedented strategic and regulatory risk.
In Summary
GRC frustrations stem from complexity, legacy processes, and human behavior. Confusing regulatory overlaps, manual evidence collection, shallow third-party assessments, and abstract risk models all weaken effectiveness.
When compliance becomes a checkbox rather than a shared responsibility, culture suffers. Strong GRC programs bridge these gaps by simplifying control mapping, automating evidence, grounding risk in operations, and fostering genuine engagement—turning governance from an obligation into a meaningful driver of resilience.