AI in Aviation Safety Management: Part 2 – Data & Trust

Your Data Is Your Safety Story: AI, Ownership, and Information Risk

We talk about data constantly - yet rarely stop to think about what it actually represents.

Entire industries exist to collect data about us: our behaviours, preferences, routines, and interests. That data is valuable because it tells a story. It allows others to predict how we think, how we act, and how we might respond.

In our personal lives, that value can be benign - tailored services, recommendations, convenience. It can also be harmful, whether through cybercrime, manipulation, or simply being separated from our money more efficiently than before.

In aviation, the stakes are higher.

Operational and safety data tells a far more sensitive story - one about vulnerabilities, system weaknesses, human performance, and organizational decision-making. It is not just information. It is a safety asset.

And like any valuable asset, it carries risk.

Data as a Safety Asset - Not a By-Product

In many organizations, safety data is treated as something that accumulates as a by-product of operations:

  • reports are submitted

  • audits generate findings

  • trends appear on dashboards

But safety data is not neutral.

It reflects:

  • where systems strain

  • where defences are thin

  • where people adapt to make things work

  • where risk is tolerated - intentionally or otherwise

Handled well, this data supports learning, prioritization, and informed decision-making.

Handled poorly, it can:

  • be misinterpreted

  • be taken out of context

  • expose organizations to unnecessary risk

  • erode trust internally and externally

Recognizing safety data as an asset is the first step toward governing it responsibly.

Why AI Raises the Stakes - Without Creating the Risk

Artificial intelligence does not create information risk.

What it does is intensify it.

AI systems:

  • aggregate data

  • connect previously separate datasets

  • identify patterns humans may miss

  • learn from what they are exposed to

This makes AI powerful - and also unforgiving of weak data governance.

If data is poorly controlled, loosely shared, or inadequately protected, AI does not correct those issues. It accelerates their consequences.

The question, then, is not whether AI is risky.

The real question is whether organizations truly understand, control, and protect the data that AI may touch.

Ownership, Residency, and Boundaries

When demonstrating safety management software, one of the most common and telling questions is:

“Where is the data stored?”

That question reflects instinctive understanding that data has value - and risk.

For many Canadian aviation organizations, data residency matters. Data stored on Canadian soil is subject to Canadian laws, protections, and expectations. That matters not only for compliance, but for trust.

But storage location is only one part of the picture.

Executives should also be asking:

  • Who owns the data once it enters a system?

  • Who can access it - and under what conditions?

  • Is it segregated by organization, or pooled in any way?

  • Can it be reused, learned from, or repurposed?

  • What happens to it if systems change or contracts end?

These are not IT questions.
They are governance questions.

Confidentiality and the Human Side of Trust

Safety Management Systems rely on trust.

People report hazards, errors, and concerns because they believe:

  • the information will be handled responsibly

  • it will not be misused

  • it will not come back to harm them unfairly

If staff are unsure where their data goes, who sees it, or how it might be reused, reporting behaviour changes - often quietly.

AI doesn’t need to be misused for trust to erode.
Perceived loss of control is enough.

This is why confidentiality, access control, and transparency about data use are foundational to both safety culture and effective SMS.

Information Risk Is an Executive Responsibility

Information risk sits alongside:

  • operational risk

  • financial risk

  • reputational risk

  • safety risk

It is not something that can be fully delegated to vendors or technical teams.

Executives should be able to clearly articulate:

  • what safety data the organization collects

  • where it resides

  • who governs its use

  • how confidentiality is protected

  • how boundaries are enforced

If those answers are unclear, introducing AI into the system does not improve insight - it magnifies uncertainty.

What This Means for Aviation Safety Management

In the context of SMS, governing data effectively means:

  • treating safety data as a protected organizational asset

  • establishing clear rules for access, use, and retention

  • ensuring AI-enabled tools operate within defined boundaries

  • maintaining transparency with staff and regulators

  • preserving trust as systems evolve

AI can support insight and learning - but only within a framework where data ownership, confidentiality, and boundaries are already understood.

What’s Coming Next in This Series

In the next installment of this series, we’ll turn to a question that inevitably follows data and trust:

Accountability.

When AI-supported systems influence decisions, identify risks, or shape priorities:

  • who remains accountable?

  • how are decisions defended?

  • and what does auditability look like in practice?

As always, the focus will remain on leadership, governance, and defensible safety management - not technology for its own sake.

Because in aviation, safety is not just about what we know.
It’s about what we protect, how we govern it, and who we trust with it.

Let’s Talk About Your Safety Data

For many aviation organizations, the questions raised in this article are not about artificial intelligence itself - they’re about understanding, protecting, and governing the safety data that already exists.

If you’re unsure how your organization:

  • defines ownership of safety and operational data

  • governs access and confidentiality

  • establishes boundaries around how data is used or shared

  • would explain these practices to leadership, staff, or regulators

that uncertainty is a valuable signal - and an opportunity.

At Acclivix, we work with airport executives and safety leaders to:

  • review how safety data is collected, stored, and protected

  • assess information risk within the context of SMS

  • support executive-level discussions on data governance and trust

  • ensure evolving tools and technologies strengthen, rather than undermine, safety management

Whether you’re preparing for future AI use, reviewing existing systems, or simply want an independent perspective on how your safety data is governed, we’d welcome the opportunity to continue the conversation.

👉 Reach out to Acclivix to discuss how your organization manages and protects its safety data.

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Tâches critiques pour la sécurité : le travail discret qui maintient les aéroports sécuritaires

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L’IA dans la gestion de la sécurité de l’aviation : Partie 2 - Données et confiance