From Reactive to Predictive: How AI Is Rewriting Risk Management and Organisational Resilience

AI is transforming the foundations of risk management. What was once a manual, reactive discipline is rapidly evolving into a dynamic and predictive capability, driven by real-time insight and automation. This evolution is reshaping the expectations placed on GRC leaders and forcing organisations to re-examine how they monitor threats, manage suppliers, and ensure resilience.

These findings sit within Axiom GRC’s landmark white paper, The Future of Governance, Risk and Compliance: 2026 Trends.

Download the full white paper here:

AI-driven insights are becoming the norm

Axiom GRC’s research shows that almost 60% of global organisations are planning to invest in AI and automated workflows for their compliance and GRC functions. The specific investment priorities highlight the scale of change:

• 34% plan to invest in automation and workflow tools
• 25% in AI-based tools
• 22% in policy and training management software
• 13% in data analytics
• 6% in other technologies

AI is now central to how modern risk teams operate. By integrating AI into risk management platforms, organisations can move from traditional static reporting to continuous, real-time monitoring. This enables teams to analyse far larger datasets, identify emerging threats earlier, and allocate resources more effectively.

Paul Cadwallader, Strategy Director at Axiom GRC’s leading risk management platform, CoreStream GRC, explains the shift:

AI integration allows risk management platforms to move beyond static reporting into dynamic, predictive analysis. Platforms should offer true customisation, flexing to how each organisation works and scaling with them as they grow. The focus will shift from tick-box compliance to delivering real business value, helping teams stay aligned, act faster, and make better-informed decisions. For GRC leaders, this creates a real opportunity to anticipate risks, respond faster, and demonstrate the value of governance and compliance as enablers of business growth, not just safeguards.

This predictive approach is already being realised in CoreStream GRC’s platform, which includes an optional AI integration module designed to streamline and strengthen the risk management lifecycle. The module parses vendor documentation, leverages trust centre data, and maps insights against industry frameworks. Where gaps remain, teams can send targeted questionnaires only where necessary. By streamlining reporting and generating improved insights for GRC leaders, AI makes risk management faster, more agile and demonstrably valuable.

AI as a resilience challenge: new risks and new dependencies

As AI becomes more deeply embedded in critical operations, organisations must treat AI as a third-party service within their risk frameworks. Most AI tools rely on external model providers. They depend on cloud infrastructure, data centres and compute resources that sit outside the organisation’s direct control.

This introduces a new category of business continuity risk.

AI outages, grid updates, capacity shortages or failures in cooling centres can disrupt essential operations without warning. The global concentration of AI computing power across a small number of providers also creates systemic risk. A single large-scale outage has the potential to cascade across multiple industries and geographies at once.

Shmuli Goldberg, Head of AI at Axiom’s compliance eLearning platform, VinciWorks, reinforces the need for structured resilience:

Effective GRC frameworks should incorporate robust resilience strategies: supplier risk assessments, multi-vendor approaches, and contingency plans to maintain operational stability during AI service disruption.

Dependencies on external large language models also create exposure to model degradation and performance variance when providers release updates or change underlying architecture. As organisations lean more heavily on AI for first-line triage, data analysis and automated reporting, the need to manage these fluctuations becomes critical.

Using global standards to govern AI responsibly

AI cannot be governed through ad hoc policies or voluntary controls. It requires recognised frameworks that demonstrate clear and credible governance. This is why international standards are becoming essential tools for organisations adopting AI at scale.

ISO 42001, published in 2023, is the first global AI management system standard. It provides a structured framework to manage AI risks including bias, explainability and oversight. It also guides how organisations should monitor AI performance and manage cross-functional accountability.

Olumide Alade, Lead Auditor at Axiom’s ISO certification specialists, IMSM, explains the importance of certification:

Certification is often viewed as the finish line, but in reality it is the foundation. The value of ISO frameworks lies in embedding continuous improvement into the organisation, creating a culture where AI risk is monitored, learned from, and adapted to in real time. Organisations that treat standards as living systems rather than checklists will be the ones that maintain trust as technology evolves.

ISO 27001 remains equally important. AI models rely heavily on secure data flows and strong information integrity. Embedding ISO 27001 controls into AI-enabled systems strengthens resilience, supports compliance with global data laws, and reduces exposure to model drift or data-driven inaccuracies.

Together, these standards allow organisations to demonstrate maturity, transparency and accountability in the use of AI. They also prepare businesses for the evolving regulatory landscape including the EU AI Act and the emerging UK and US frameworks.

The future of AI in risk and resilience

The direction of travel is clear. AI is rapidly shifting GRC from static oversight to real-time, evidence-based decision-making. It gives organisations the ability to anticipate risks rather than react to them, and it elevates the role of compliance and risk as strategic enablers of organisational resilience.

Yet this progress also demands stronger governance, clearer accountability and frameworks that recognise AI’s inherent complexity and interdependencies.

These insights form one part of Axiom GRC’s broader research into the forces shaping the 2026 GRC landscape.

Download the full white paper, The Future of Governance, Risk and Compliance: 2026 Trends, here: