GRC Tool Sprawl: Why More Software Hurts Assurance

More GRC software hasn't produced stronger assurance for the organisations spending the most on it. Boards keep investing, procurement keeps approving, and vendors keep multiplying, yet the same problems keep surfacing.

Evidence collected in four systems tells four different stories. Compliance, audit and third-party risk teams map controls independently, with no shared logic between them. And teams assemble board reports by hand each quarter, because no platform holds the full picture.

This is a case for buying GRC technology deliberately, judging each tool by what it actually contributes to the programme. A tool that solves one problem in isolation can create a new one at the programme level, and when isolated tools multiply, the costs compound: duplicated effort, inconsistent risk ownership, fragmented evidence, and reporting that auditors and regulators struggle to rely on. Frameworks like DORA, NIS2 and the EU AI Act all require demonstrable, connected accountability, so the real question for GRC, risk, compliance, audit and security leaders is whether the tools in their stack work together well enough to assure the business.

GRC tool sprawl is the predictable result of how regulated organisations grow their compliance programmes: one framework at a time, one team at a time, one procurement decision at a time. The GRC software market keeps growing to match.

Mordor Intelligence puts current GRC software spend at $23.32 billion in 2026, growing to $39.01 billion by 2031 at a 10.84% compound annual growth rate.

Boards are investing, procurement teams are approving, and vendors are multiplying to meet the demand. Gartner forecast a 50% rise in legal and compliance department investment in GRC tools between 2023 and 2026, the year we're now in.

A financial services firm might start with an ISO 27001 compliance tool, add a separate TPRM platform when supply chain risk becomes a board concern, bring in a dedicated audit management system, then acquire a point solution for DORA reporting. Each decision makes sense on its own. The aggregate is a fragmented architecture that nobody designed and nobody fully owns.

The most visible symptom is time. Research by Hyperproof found that 52% of GRC professionals spend 30 to 50% of their working time on administrative tasks like manual data entry. That time goes to data re-entry, evidence chasing and reconciling outputs that should have matched in the first place, and it comes directly at the expense of analysis and judgement.

The less visible symptom is reliability. When three systems map the same control independently, each with its own owner and its own evidence artefact, none of those artefacts is trustworthy as authoritative on its own. Auditors ask for evidence and receive a spreadsheet assembled from six sources. Regulators ask for accountability and find it spread across teams with no clear chain.

The underlying problem is a missing shared evidence model. Teams that cut tools before defining one create a false simplification: multiple owners still report on the same control in different ways, just with fewer logins to reconcile it across. Reducing tool count without fixing the evidence model just relocates the problem.

The assurance cost of tool sprawl shows up in three distinct, compounding ways. Each one damages the programme alone; together, they produce a programme that looks active but can't actually demonstrate control.

1. Duplicate Controls, Inconsistent Ownership

When risk, compliance and audit teams each maintain their own control libraries, each team defines the same control on its own terms, often with different scope, different testing criteria and different owners. Nobody intends this; it's the natural result of teams working in separate systems. The deeper problem surfaces when a regulator asks which team is accountable for a given control outcome and there's no clean answer, because the tool stack scatters accountability across teams instead of assigning it to one.

2. Fragmented Evidence That Has to Be Collected Again

A-LIGN's 2026 State of Compliance report found that 97% of organisations conduct at least two audits a year, and 74% of enterprise organisations run four or more. Each audit cycle pulls teams back into manual collection when the underlying tools don't share data: the same screenshots, the same access logs, the same policy documents, gathered again and stored in a different system. A 50 to 65% reduction in manual evidence collection is achievable when controls are mapped once and shared across frameworks, and that figure becomes meaningless the moment each tool keeps its own evidence repository.

3. Reporting That's Hard to Trust

Board-level risk reporting needs a single, reliable view of the control environment. In a fragmented stack, someone has to build that view by hand, usually whoever knows which system to trust for which data point. The result is reporting that reflects the effort of assembly more than the current state of risk: boards see a version of the truth that's already dated by the time it lands, and regulators receive assurances that can't be traced back to a clean evidence chain.

Fragmented control evidence carries the weight of a governance risk, well beyond routine audit friction. When controls live in separate systems, organisations compensate with duplicate processes and inconsistent reporting, which weakens the assurance they're trying to provide.

The fragmented tool problem has existed for years. What's changed is the regulatory environment's tolerance for it.

Connected Controls Are Now a Regulatory Expectation

DORA's five pillars require financial entities to demonstrate ICT risk management, incident reporting, resilience testing, third-party oversight and information sharing as one integrated programme, and constructing those connections by hand for every regulatory submission is both slow and unreliable. See our Five Pillars of DORA Explained for the full breakdown. NIS2 places equivalent cross-domain demands on critical infrastructure operators; our NIS2 Compliance Guide covers what that means in practice.

The EU AI Act adds a further layer. ISACA's 2026 research found that a third of organisations don't require employees to disclose when AI has been used in a work product, leaving real gaps in visibility over where and how the business uses AI. The Act requires AI risk to sit inside the broader organisational risk framework, so a standalone AI governance tool that doesn't connect to the risk register or control library recreates the same accountability gap regulators are already scrutinising elsewhere.

The Cost of Getting It Wrong Is Rising

The FCA issued £15.7 million in fines in Q1 2026 alone, and that figure only covers enforcement action already concluded. Each of those cases traces back to a control environment that failed under pressure, often because the assurance function lacked the full picture in time to act.

A wholesale replacement programme is rarely the answer; most organisations have existing investments, workflows and contracts that make a clean-slate approach impractical. A more useful starting point is an honest assessment of what each tool actually contributes to the assurance programme.

A tool that fails two or more of these questions is weakening the programme, adding cost, complexity and fragmentation.

Multi-framework support matters more as regulatory portfolios grow. An organisation running ISO 27001, DORA, NIS2 and the EU AI Act at once needs controls mapped once and tested across all four, which only works if the underlying platform holds every framework in a single, shared control library. A tool that supports only one framework forces teams to rebuild the same compliance exercise from scratch for every other one.

The Evidence Model Test

The programme-level test sits beyond individual tools: does a common evidence model exist? For each control, that means one authoritative definition, one owner, one evidence source and one place to track exceptions, with every tool in the stack either feeding that model or sitting outside it. When the model doesn't exist yet, tool consolidation is premature: define it first, then assess which tools support it.

The Third-Party Risk Dimension

Third-party risk is where fragmentation is most costly and least visible. TPRM programmes that operate apart from the enterprise risk register can't surface supplier risk in the context of organisational risk appetite; assessment results sit in the TPRM tool while risk decisions sit in the risk tool, connected only by someone's memory or a spreadsheet. ProcessUnity and the Ponemon Institute’s 2026 State of Third-Party Risk Assessments research found organisations experience an average of 12 third-party breaches a year, a gap that a questionnaire sitting outside the broader assurance programme has no mechanism to catch.

Connected assurance is a state where risk, compliance, audit, third-party risk and AI governance share a common data layer, a common control library and a common evidence trail. An organisation can legitimately run several tools and still achieve connected assurance, provided those tools integrate properly and feed a shared model; a different organisation can consolidate to three tools and still have fragmented assurance, if those three don't share data.

1. One control definition, used everywhere: A control tested for ISO 27001 produces evidence automatically available for DORA, NIS2 and any other applicable framework. Testing happens once, and reuse is the default.
2. One risk register, visible to every domain: Risk identified in a third-party assessment surfaces in the enterprise risk register without a manual handover, and risk the audit team finds is visible to compliance in real time.
3. One evidence chain, trusted by auditors and regulators: Every control test, exception and remediation action lives in a single, auditable trail, and board reporting draws from the same source as regulatory submissions.
4. Clear ownership at every point: Each control has one owner, each risk has one owner, and the answer is immediate and traceable whenever accountability gets challenged.

SureCloud is built around this model: one platform spanning risk management, compliance, internal audit, third-party risk, Continuous Controls Monitoring, AI governance, data privacy and business continuity, with every domain sharing the same risk register, control library and evidence trail. A control mapped for ISO 27001 becomes immediately available for DORA, NIS2 and the EU AI Act; audit findings connect to the compliance programme without a manual handover; audit preparation time drops by up to 75%.

The organisations that navigate this well will be deliberate about how their tools connect, regardless of budget size, holding every procurement decision to a harder standard than "does this solve the immediate problem": whether the tool connects to the programme they're actually trying to build.