When our technology team proposed using AI to generate our Minimum Equipment List, we were skeptical.
MELs are among the most complex regulatory documents in aviation. Every item requires cross-referencing the manufacturer's DDG/MMEL, Transport Canada's Master MEL, supplemental type certificates, and any temporary revisions. Getting one wrong means aircraft don't fly. Could AI really handle this?
Transport Canada approved our clean-sheet, AI-generated MEL following a collaborative review process.
The Operator's Problem
The traditional MEL process is broken.
Creating or updating a Minimum Equipment List takes hundreds of hours. For a growing operator like Great North Airlines, this documentation bottleneck slowed our ability to add aircraft and respond to market opportunities.
The dirty secret nobody talks about: operators rarely write MELs from scratch. We inherit them from previous certificate holders, layer amendments onto documents passed around for years. Every operator in the industry is working with files that carry forward legacy issues: formatting problems, reference errors, inconsistencies that compound with every amendment cycle. The same mistakes get copied from operator to operator, generation after generation.
This isn't a Pivot problem. It's an industry-wide problem. And nobody had a good solution. Until now.
We needed a fresh start, but the traditional process couldn't deliver one.
What We Built Together
Working with our technology partner, we developed an AI extraction engine specifically for aviation technical documents. The system parses the complex nested table structures that break standard tools, cross-references multiple regulatory sources automatically, and generates complete Word documents ready for submission.
What impressed us most: during validation, the AI found dozens of errors in existing approved manuals. Mistakes inherited from manufacturer source documents. Errors that had passed through multiple human review cycles undetected. We went from "let's double-check the AI's work" to "the AI is catching things the industry has been missing for years."
Results
- Clean-sheet MEL creation: Hundreds of hours → Less than 1 day
- Regulatory collaboration: Streamlined review through consistent, accurate documentation
- Cross-reference accuracy: Exceeds manual review
Human Oversight Still Essential
The AI handles extraction, cross-referencing, and initial assembly. But our subject matter experts reviewed every page before submission. This combination of AI efficiency with human oversight is what gave Transport Canada confidence to approve the result.
The real benefit: our SMEs could finally focus on what they're trained for. Operational procedures and safety implications. Not drowning in administrative work like formatting tables and manually cross-referencing documents. The AI handles the tedious, error-prone stuff. The humans focus on the judgment calls that actually matter.
This also reduces dependence on specialized technical writers. When the AI handles formatting and cross-referencing, your ops experts can review and approve documentation directly.
We're not replacing aviation professionals. We're giving them better tools.
What This Means for Future TC Reviews
This changes our relationship with regulatory compliance.
Previously, MEL amendments were a reactive exercise. Something changes, we scramble to update documentation, we wait weeks for approval. Now we can be proactive. When a manufacturer issues a DDG change, Transport Canada releases a Temporary Revision or Master MEL update, or a new advisory circular comes out, we can have our updated documentation ready for review in minutes, not weeks.
Any regulator could use this approach. The entire regulatory ecosystem moves faster when operators can respond to changes from any source (manufacturer, regulator, or advisory) in minutes instead of the traditional weeks-long cycle.
More importantly, the consistency this brings should streamline future reviews. Documentation that's accurate, properly formatted, and fully cross-referenced every single time means less back-and-forth and faster approvals for everyone.
Our Take: Aviation Needs to Lead on Safe AI Adoption
Aviation has always been at the forefront of safety culture. We don't take shortcuts. We verify. We document. We learn from every incident.
That same mindset should apply to AI adoption.
Too many industries are rushing to deploy AI without thinking through the implications. Aviation can't afford that approach, and shouldn't want to. But the opposite extreme, waiting until everyone else has figured it out, means falling behind on tools that actually improve safety and efficiency.
Nobody's talking about this reality: AI is almost certainly already being used quietly across the industry. Operators drafting documents. Consultants preparing submissions. Probably even regulators processing approvals. The question isn't whether AI will be part of aviation's future. It's whether we're going to be transparent about it or pretend it's not happening.
Pivot wants to lead on transparency. We told Transport Canada exactly what we were doing and how. We documented our methodology. We invited scrutiny.
The Review Process Needs to Evolve
The problem: the traditional random sampling approach to manual review is fundamentally broken in the age of AI.
The current system was designed for a world where humans created documentation and humans reviewed it. Regulators can't check everything. There's too much volume. So they random sample and hope to catch errors. That approach assumes errors are randomly distributed. They're not. The same inherited mistakes propagate through the same sections across the entire industry, and random sampling misses them for years.
We know this because we found them. Dozens of errors in existing approved manuals that had survived years of review cycles. If the current process was working, those errors wouldn't exist.
Worse, the current process is vulnerable to exploitation. Regulators could use AI to find errors first, then re-roll the randomizer until it lands on those sections. The system is already evolving. The question is whether we're going to acknowledge it and build proper guardrails, or pretend nothing has changed.
When AI can generate documentation that's consistent and cross-referenced every single time, and when AI can help review it just as thoroughly, the entire verification model needs to change.
We recently conducted a live demonstration with TC where we showed how the AI can track the exact history of any MEL item: why changes were made, what source documents drove the revision, the complete audit trail. Instead of random sampling and hoping to catch errors, regulators could validate the AI's methodology once and then review at a higher level, focusing on operational judgment and safety implications. That's a better use of everyone's time.
We've started this conversation with TC, and we're eager to continue it by sharing our validation tools and methodologies. If AI can help operators produce better documentation faster, it can help regulators review it more efficiently too.
We believe operators have a responsibility to explore AI thoughtfully. That means:
- Starting with low-risk, high-verification tasks like documentation, where every output gets human review before it matters
- Being transparent with regulators about what we're doing and how
- Sharing what we learn so the industry moves forward together
The MEL project was our test case. Transport Canada's approval validated the approach. We're continuing to improve accuracy through methods like running outputs through multiple AI engines for cross-validation. We're also planning a white paper to share what we've learned.
Now we're looking at what else this methodology can improve: training documentation, operations manuals, compliance tracking.
Aviation should be leading the conversation on responsible AI adoption, not watching from the sidelines.
What This Means for Operations
When we add a new aircraft type or a manufacturer releases a service bulletin, we can now update documentation in minutes instead of the hundreds of hours it used to take. Compliance happens fast. Our operations team spends less time on paperwork and more time on what matters: safe, reliable flights.
That's what matters. Not the technology itself, but what our people can focus on instead.
For the technical deep-dive, see the companion post from our technology partner ForIT.
Interested in how Great North Airlines uses technology to improve operations? Contact us to learn more.