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Automating risk management: from spreadsheets to real-time oversight

Written by Maiky | Sep 29, 2025 10:57:28 AM

Why traditional risk management methods no longer work

For years, security and compliance teams have relied on spreadsheets, static reports, and manual reviews to capture and monitor risk. While familiar, these tools are slow, error-prone, and unsuited for today’s reality: attackers using automated tools, regulators (such as with NIS2 in the EU) demanding continuous proof of compliance, and boards expecting clear visibility into risk at all times.

In this environment, change happens too quickly for manual methods to keep up. Automated risk management and real-time monitoring are no longer “nice-to-haves”; they are essential for resilience, compliance, and business continuity. By replacing static oversight with dynamic, AI-driven insights, organisations can move faster, reduce uncertainty, and align security decisions with business goals.

This article explores why traditional approaches fall short, how AI and automation reshape Governance, Risk & Compliance (GRC), and what future-ready organisations can expect when adopting adaptive, real-time practices.

The foundations of a modern security program


Every effective security program rests on three pillars:

  • Governance (how) → defining policies and responsibilities.
  • Risk (why) → understanding threats and their business impact.
  • Compliance (what) → meeting legal, contractual, and regulatory obligations.

This framework is universal, whether aligning with NIS2, ISO 27001, or industry-specific audits. But the classic manual approach is no longer sufficient. Spreadsheets and one-off reviews fail to capture how quickly threats and requirements evolve.

The path forward requires designing the right controls, validating their implementation continuously, and improving them dynamically. A cycle that AI and automation can accelerate.

Why spreadsheets fail in risk oversight

CISOs and compliance leaders know the challenges well:

  • Human error is inevitable → typos, missed updates, and outdated entries reduce confidence in the risk picture.
  • Risks evolve too quickly → threat actors don’t wait for quarterly reviews. By the time data is updated, it may already be obsolete.
  • Static visibility → spreadsheets provide a snapshot, but no real-time understanding of trends, deviations, or early warning signals.

This approach creates gaps in assurance, which is exactly what regulators, auditors, and boards can no longer accept.

 

AI as an accelerator, automation as a validator

AI and automation together change risk management from a reactive process into a continuous, intelligence-driven discipline:

  • AI during design → detects patterns in incidents, enriches risk analyses with broader data, and highlights compliance gaps. It can even review policy documents against the latest standards, such as NIS2 or the AI Act.

  • Automation during validation → continuously monitors control effectiveness with minimal operational impact. Deviations are flagged immediately, preventing small issues from escalating.

  • Real-time dashboards → provide leadership with live risk scores, compliance health, and clear visibility without waiting for static reports.


The combination ensures that organisations are not just documenting risks for auditors; they are actively reducing them in real-time.

Prioritising threats: from data to actionable insights

Automation helps teams cut through noise and focus on what matters most:
  • Context-aware risk scoring → factoring in asset criticality, exposure, and exploitability to highlight top-priority risks.
  • Automated workflows → a vulnerability on a critical server can trigger alerts and assign remediation tasks instantly.

  • Continuous improvement → insights from recurring incidents feed back into updated controls and smarter prevention.


This reduces alert fatigue, ensures the right risks get the right attention, and enables risk management to drive daily decision-making.

 

Maiky in Action: real-time oversight at your fingertips

We developed Maiky to help organisations step into this new world of adaptive risk management without disrupting existing processes. With Maiky, you can:

  • Receive proactive alerts → risks are detected and communicated in real time
  • Access live dashboards → boards and CISOs see risk and compliance status instantly, not weeks later.
  • Integrate with existing frameworks → whether you align with NIS2, ISO 27001, or others, Maiky connects seamlessly.
  • Automate the heavy lifting → repetitive reporting and manual updates are eliminated, freeing teams to focus on strategy and governance.


By continuously capturing and validating control data, Maiky builds a knowledge base that facilitates compliance, enhances security, and enables faster decision-making.

The pitfalls of AI and automation

The promise of AI and automation is significant, but not without risks. CISOs remain cautious about:

  • Bias and data quality → poor data can mislead algorithms.
  • Transparency and explainability → AI-driven risk scores must be defensible to auditors and regulators.
  • Ethical and governance concerns → without frameworks, AI may introduce risks as it mitigates others.


That is why emerging standards like ISO 42001 (AI governance) are crucial, providing guidance on ethics, transparency, and accountability in AI-driven security programs.

The future: adaptive, continuous, and AI-enhanced

Risk management is moving from a checkbox activity to a continuous, adaptive process where:

  • Automation provides ongoing monitoring.

  • AI delivers insights and recommendations.

  • Human expertise focuses on governance and strategy.


This partnership transforms security from a reactive cost centre into a proactive enabler of resilience and trust.

 

Key Takeaways

  •  
  • Spreadsheets and manual risk registers can no longer keep up with the speed of today’s cyber threats.

  • AI accelerates risk design by detecting patterns and compliance gaps, while automation validates controls continuously.

  • Continuous, real-time oversight reduces alert fatigue and enables faster, better decisions.

  • Ethical and governance frameworks (e.g., ISO 42001) are essential to manage AI responsibly.

  • With Maiky, organisations gain real-time visibility, proactive alerts, and seamless integration with frameworks like NIS2 and ISO 27001.

  • The future of risk management is adaptive, continuous, and AI-enhanced with humans in control and automation as a force multiplier.