Cyber threats are escalating. AI systems are becoming more prevalent in regulated environments. Digital networks and critical infrastructure are becoming increasingly interconnected. Meanwhile, according to the Organisation for Economic Co-operation and Development’s (OECD) Regulatory Policy Outlook 2025, many regulators are still taking a “regulate and forget” approach to policy development, highlighting the need for adaptive regulation and investment in institutional capacity and digital tools to improve responsiveness amid rapid innovation and ongoing digitalization. That said, regulators must move beyond manual, ad hoc processes and toward sovereign oversight and evidence-based assurance, enabling secure technology adoption that supports national cyber resilience and economic growth.
Translating regulatory objectives such as preserving national security, privacy, and critical service continuity into day-to-day supervisory operations remains challenging, with many regulators still constrained by traditional workflows and oversight models:
Instead of focusing on emerging threats, systemic weaknesses, or uplift programs, regulatory teams often spend their time collecting documents, reconciling data, and preparing reports.
This creates a persistent gap between regulatory intent and regulatory execution.
As cyber risk and AI adoption accelerate, regulatory assurance must evolve from static compliance to continuous, data-driven oversight.
Modern supervision requires a shift:
To redefine how assurance is delivered at scale, regulators need operational models that support real-time insight, consistent supervision, and defensible decision-making while ensuring sensitive data, evidence, and assurance processes remain within their jurisdictional control.
Traditional regulatory models rely heavily on scheduled reporting cycles and retrospective analysis, providing a baseline level of oversight but struggling to keep pace with today’s dynamic risk environments. Continuous assurance introduces a different paradigm.
Instead of waiting for submissions, regulators gain ongoing visibility into compliance posture, control performance, and emerging risks. Evidence is centralized. Assessments are structured. Supervisory activity becomes proactive rather than reactive.
With the right foundations in place, regulatory teams can:
AI further accelerates this shift by automating resource-intensive tasks such as framework mapping, analysis, and reporting, freeing teams to focus on judgment, intervention, and policy development.
Transitioning to risk-based, fit-for-purpose oversight models requires regulators to assess current supervisory maturity and operational readiness. It typically starts with asking the following questions:
A clear, step-by-step roadmap includes concrete frameworks, maturity benchmarks, and proven operating models tailored to regulatory environments. To help regulators in their journey to sovereign and continuous assurance, our Regulator Resource Pack offers a practical toolkit designed to enable supervisory authorities to improve and scale oversight across cyber resilience, regulatory compliance, and AI governance. It includes:
This resource is specifically made for supervisory authorities modernizing oversight models, expanding mandates across cyber and AI governance, or seeking sovereign control over regulatory data and assurance processes, delivering actionable guidance grounded in real regulatory challenges.
Modern regulatory oversight demands more than compliance checklists. It requires structured evidence, continuous visibility, and scalable assurance models built for today’s threat landscape.
Download the Regulator Resource Pack to access practical frameworks, maturity diagnostics, and guidance designed to help regulators reduce administrative burden, strengthen assurance, and deliver greater supervisory impact.