Why governance, risk and compliance needs a new operating model built for scale

Boards have spent the past two decades asking governance, risk and compliance (GRC) departments to do more with less. That phrase has now stopped being a challenge and become mathematically impossible.

Across regulated sectors, the GRC agenda has expanded faster than any corresponding increase in budget or headcount. External pressures have forced operational resilience, third-party risk, cyber-assurance, privacy obligations and AI governance to all move up the board agenda at the same time.

 

Yet many organisations are still trying to manage that burden through manual processes and overstretched specialist teams. SureCloud’s own research last year found that 60 per cent of UK enterprises continue to use spreadsheets daily alongside their paid tools, while over half struggle to keep up with more than five major regulations.

 

This is the business problem at the heart of modern GRC. It is not that organisations lack expertise. Most already have capable risk, compliance and audit professionals who understand the regulations and the operational realities of the business. The challenge is that there are never enough of them to execute every assessment, review every control, chase every document, test every process and produce every report at the pace now required.

 

The capacity problem behind compliance fatigue

 

For years, that gap has been tolerated. Work has been delayed, de-scoped or distributed to less experienced colleagues. Spreadsheets have stood in for systems. Inboxes have become workflow engines. Shared drives have become evidence repositories. But in an environment of rising scrutiny, more complex supply chains and increasing digital dependence, that operating model is beginning to break down.

 

Most GRC leaders are not struggling because they lack insight. They are struggling because they lack the capacity to execute. A risk manager knows how to run an effective assessment but cannot personally complete each one across a growing estate. A compliance lead understands multiple frameworks in detail but cannot sit in on every workflow where compliance decisions are made. An internal auditor knows which areas deserve deeper testing but cannot expand coverage indefinitely without more time or more people.

 

This is where compliance fatigue begins. Teams are asked to deliver broader coverage, faster reporting and stronger assurance without a matching increase in resources. Backlogs grow and review cycles slow. Inevitably, the business starts to experience GRC as a brake, rather than as a strategic capability.

 

The instinctive answer is often to hire. In some cases this is necessary, but hiring alone is unlikely to solve the structural challenge.

 

Experienced GRC professionals are expensive, difficult to find and slow to onboard. Outsourcing can plug specific gaps but adds cost and oversight of its own. Meanwhile technology investments have focused on improving visibility rather than transforming execution. Dashboards help leaders see problems, but they do not remove the manual effort required to address them.

 

From software to a virtual team

 

For many organisations, AI in GRC has so far meant assistants that summarise policies, draft documents or answer questions. Those capabilities are useful, but they do not fundamentally change the workload. They still rely on a human expert to drive the process from start to finish.

 

A more meaningful model is one in which AI could fill defined roles across the programme. Instead of a generic assistant, it would operate as your same risk or compliance owners, auditors or vendor managers, carrying out specific tasks in line with the organisation’s own workflows and governance rules.

 

That distinction matters. Business leaders do not need software that produces content faster. They need operating leverage: a way to run more assessments, review more evidence and maintain audit readiness without stretching already-constrained teams beyond breaking point.

 

Why codified expertise matters

 

One of the biggest business benefits in this model is not just automation. It is the codification of expertise.

 

In most organisations, a great deal of GRC capability lives in people rather than in systems. Senior team members know how to interpret policy, what good evidence looks like, how to score a third party and how to prepare for an audit. That knowledge is valuable, but difficult to scale and vulnerable to turnover.

 

When that expertise is captured as repeatable methods and embedded into workflows, it becomes a business asset that ensures continuity and reduces dependency on individual knowledge. The function becomes less reliant on heroic effort, and institutional knowledge can be applied more broadly across the enterprise.

 

Governance cannot be an afterthought

 

Of course, no board will accept a more automated model unless it is confident the governance is sound. If AI is going to participate in regulated workflows, organisations must be able to explain what AI did, what authority it had and where human oversight remained in place.

 

Role-based permissions, clear limits on authority, a transparent record of reasoning and human confirmation for higher-stakes decisions should not be optional extras. They should be built into the architecture from the start. The business value of that governance is straightforward. It gives leaders confidence that they can increase execution capacity without weakening accountability.

 

The next phase is no longer about documenting what should happen but ensuring it actually does, to the right standard and at the right scale.

 

When execution capacity improves, the business no longer has to make the same compromises. It becomes easier to expand audit coverage, complete vendor reviews on time and respond to regulatory change with less disruption. GRC becomes better able to support growth, transformation and resilience, rather than trying to keep pace with them.

 

The organisations that move first are not necessarily those with the largest risk teams, but those that recognise the limits of the old model earliest.

 

The question for boards is no longer whether GRC teams are under pressure. That is already clear. It is whether the organisation is prepared to keep managing a modern risk landscape with an operating model built for a very different era.

---

To explore how SureCloud and its new Gracie AI are helping GRC teams meet the next decade of regulatory and business complexity, click here.

---

Confidence isn’t a strategy. Discover how to fix the risk and compliance operating model. Access SureCloud’s 10X GRC playbook.

---

By Nick Rafferty, CEO, SureCloud