As regulatory demands continue to multiply, many organisations are finding that their compliance frameworks have grown larger, more complex and harder to manage, rather than more effective.
Susan Palm, chief revenue officer at 4CRisk.ai, says this growing sprawl of overlapping controls is one of the most persistent challenges facing IT, security and compliance teams today, particularly as firms operate across multiple jurisdictions and regulatory regimes. Palm argues that control harmonisation, supported by AI-powered tools such as 4CRisk’s Compliance Map, offers a practical way out of this inefficiency.
Across global organisations, compliance teams are tasked with meeting requirements from frameworks such as ISO 27001, PCI DSS, SOC 2, NIST, GDPR and DORA. Historically, each new obligation triggered the creation of additional controls, even when similar controls already existed elsewhere in the business. Over time, this has resulted in compliance frameworks where the same control is tested multiple times under different names. When these controls are managed in silos, organisations experience what many professionals refer to as compliance drift, where conflicting test results obscure the true compliance and risk position.
This challenge is widely known as control redundancy. It includes duplicate, overlapping and unnecessary controls that consume time and resources without improving outcomes. While control redundancy has long been accepted as unavoidable, advances in AI have made control harmonisation a practical alternative, Palm said.
The benefits of this approach are clear. Harmonised controls allow evidence to be collected once and reused across standards, supporting a “test once, comply many” model, Palm noted. Harmonisation also cuts down on repeated evidence requests from audit, governance and risk teams, easing operational friction. When new regulations emerge, organisations can map them against existing controls rather than rebuilding frameworks from scratch, enabling faster and more confident responses to regulatory change.
Traditionally, control harmonisation has relied on manual processes, spreadsheets and extensive cross-referencing. These methods are slow, error-prone and increasingly unfit for scale. AI is now changing that dynamic. 4CRisk’s Compliance Map uses natural language processing to interpret the intent behind internal controls and external regulatory requirements. Rather than relying on simple keyword matches, the platform identifies meaningful relationships between controls and standards, flags redundancies and highlights genuine compliance gaps as regulations evolve.
By adopting AI-powered control harmonisation, organisations can move away from reactive compliance practices, Palm explained. The result is a leaner, faster and more reliable compliance function that lowers costs while delivering a single, accurate view of regulatory and risk posture. As regulatory expectations intensify towards 2026, AI-enabled harmonisation is emerging as a practical way to turn compliance from a burden into a strategic advantage.
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