MRO-PRO has been named winner of the Aviation Innovation Award at the 2026 Aviation Industry Awards UK, recognising the company’s pioneering use of artificial intelligence to transform aircraft maintenance through its Maintenance Intelligence Learning Engine (MILE™).
The award, presented at the Aviation Industry Awards UK gala ceremony in London on 22 September, recognises innovation that is helping to reshape the aviation industry. For MRO-PRO, it represents significant recognition of its work to bring AI and advanced data intelligence into aircraft maintenance, repair and overhaul (MRO).
Recognition for a new approach to MRO
This award follows MRO-PRO’s earlier success at the 2026 National Technology Awards, where the company was recognised with the Best AI Tech award.
Its latest recognition demonstrates the growing relevance of MRO-PRO’s approach to the wider aviation industry, as airlines and MRO providers look for ways to increase efficiency while managing increasingly complex fleets, rising operational pressures and growing volumes of maintenance data.
Scott Wells, Managing Director of MRO-PRO said:
“I am thrilled and incredibly proud of the whole MRO-PRO team in winning our second major award in 2026. There is so much hard work that goes on behind the scenes to turn ideas and ambitions into reality, so achieving industry recognition like this makes you stop and realise just how far we’ve come. MRO-PRO is genuinely making an impact across the aircraft maintenance sector, and we are helping shape the industry’s future. Winning this award in front of your peers is a fantastic achievement for the entire team.”
From maintenance data to maintenance intelligence
At the heart of the innovation is MILE™, MRO-PRO’s proprietary Maintenance Intelligence Learning Engine, which has been developed specifically to understand the language, processes and operational realities of aircraft maintenance.
Rather than simply digitising existing maintenance processes, MILE is designed to understand maintenance intent, turning fragmented maintenance data into actionable intelligence that can continually improve how future aircraft checks are planned and executed.
However, much of this information has traditionally remained fragmented.
For third-party MROs, the challenge is particularly significant. Different airline customers can use different maintenance programmes, terminology, task structures and descriptions, even when the underlying maintenance activity is essentially the same.
Traditional systems can struggle to recognise these relationships because they are often dependent on exact task references, labels or manually created mappings.
MILE takes a fundamentally different approach.
Using AI, semantic analysis and machine learning, it analyses the meaning and context behind maintenance information rather than simply matching words or reference numbers. It can recognise relationships between tasks, defects, aircraft, parts, tools and historical outcomes, helping to create a common intelligence layer across complex maintenance environments.
The result is a move away from simply asking “What happened last time?” towards being able to ask “What is likely to happen next?”
Predicting what an aircraft will need before it arrives
One of the most significant applications of MILE is predictive maintenance planning.
By analysing historical maintenance activity, aircraft characteristics, task history and defect patterns, the platform can forecast probable requirements before a maintenance check begins.
This can include:
- Probable non-routine defects
- Parts and material requirements
- Tooling and equipment
- Specialist services
- Labour and man-hours
- Work-pack requirements
- Potential resource constraints
This intelligence gives MRO planners the opportunity to identify potential issues before an aircraft enters the hangar, rather than discovering them once the check is already underway.
For an industry where aircraft availability, turnaround time and resource utilisation are critical commercial considerations, this represents a fundamental shift from reactive planning towards probability-driven maintenance intelligence.
AI that learns from engineers
Importantly, MILE is not designed to replace the knowledge and experience of aviation engineers and maintenance planners. Human expertise remains an essential part of the process.
The system generates probable matches, relationships and predictions which can be reviewed by experienced personnel. When planners and engineers confirm, refine or correct the system’s interpretation, those decisions can be captured and fed back into the learning process. This creates a continuous feedback loop, so every maintenance check has the potential to make the next check more intelligent. Over time, this creates a compounding knowledge base in which the organisation’s maintenance experience becomes increasingly valuable and accessible.
It is this combination of artificial intelligence and human engineering expertise that sits at the centre of MRO-PRO’s approach.
Moving MRO from reactive to predictive
The implications extend beyond individual maintenance tasks.
MILE is designed to connect planning, execution and learning across the MRO operation, providing a more complete picture of what is happening and what is likely to happen next. The objective is a continuous cycle of improvement rather than a series of disconnected maintenance events.
Its capabilities include intent-based task and defect understanding, AI-assisted work-pack planning, predictive non-routine defect forecasting, resource intelligence, real-time operational visibility and closed-loop learning from completed checks.
This creates the potential for MRO organisations to improve the way they:
Plan – understand the likely workload before a check begins.
Prepare – identify parts, tooling, services and resources in advance.
Execute – provide engineers with real-time digital information at the point of maintenance.
Monitor – track progress and emerging issues throughout the check.
Learn – feed completed maintenance activity back into the intelligence engine.