From Paper Logs to AI- and Blockchain-Enabled

By nature, aviation is documentation-heavy. Even a single aircraft generates a significant volume of records that must be maintained to demonstrate continued airworthiness. For decades, paper records have been the primary method. They are still widely accepted and operationally valid, but they carry inherent risks: physical degradation over time, exposure to damage, and practical limitations during audits and reviews.

As the industry sought improvements, electronic records began to emerge. Early adoption was largely limited to digitizing paper for archiving and backup purposes, using formats such as microfilm, CDs, and later scanned PDFs or JPEGs. However, these formats offered limited functional improvement, as most remained effectively unsearchable and no more operationally useful than their physical counterparts.

More recently, records management platforms have introduced OCR to enable text searchability and basic efficiency gains. That said, OCR is generally effective only for clean, typed documents. More advanced platforms now incorporate AI/ML to automate document classification, and as other aspects of aviation adopt digital solutions as well, support integration with other systems, such as ERP or maintenance software. One of the latest developments we observed in this space is the use of blockchain, primarily to provide immutable audit trails and an additional layer of data integrity and security.

Big Promises, Big Challenges

Digital records platforms promise clear benefits, including more streamlined operations, reduced risk of human error, mitigation of data silos, easier audit readiness, and support for broader digital initiatives such as predictive analytics. That said, implementation comes with its own set of challenges.

First, as with most digital transformation initiatives, the upfront cost is significant. This can be difficult to justify, not only for large fleets that must scale the solution across multiple aircraft, but also for smaller organizations with limited capital.

Internally, resistance from personnel is also common during the transition. Personnel may be deeply accustomed to legacy workflows and not yet digitally ready, which can lead to skepticism toward new systems. The tool may be perceived as a threat rather than an enabler, a reaction that is understandable and should be addressed through change management rather than ignored.

The Issue of Data Gaps during Digital Migration

Even if cost and human challenges are addressed, realizing the benefits is not as simple as installing an app. The inherent nature of manually created records means data gaps and inconsistencies are common. This becomes a critical issue when records are used for more than archival purposes, for example when integrated with an ERP for maintenance planning, where the data directly underpins calculations such as life limits

1. Interpretation and Terminology

This is not always pure error, but human variation. Data becomes difficult to standardize and process when the same issue is described differently by mechanics, engineers, and planners, each working from their own perspective and operational context.

Differences in terminology further compound the problem. Variations can exist across departments, between organizations performing similar functions, or across regions. For example, “oil leaking,” “engine oil leak,” and “ENG oil leaking” describe the same condition, yet their free-text nature makes them harder to structure and analyze.

2. Non-Standard Data Formatting

As with human communication, documentation practices vary. Different operators and document types record data in different formats. Some systems rely on coded fields and structured inputs, while others depend heavily on free text. In practice, certain records may be coded, while AML entries are handwritten, unstructured, and inconsistent in format.

3. Siloed Departments and Data Fragmentation

Data is often distributed across multiple platforms. Information may reside in SAP, maintenance systems, spreadsheets, PDFs, emails, and physical logbooks. A defect may appear in the AML, the removal in SAP, and the analysis in an emailed report. This fragmentation complicates migration efforts, as data must either be reconciled across sources or cross-validated where multiple departments record the same event from different perspectives.