Aviation operations team using governed AI and integrated data to support operational decisions.
ビジネストーク

航空分野における人工知能

Turn fragmented aviation data into governed intelligence that helps teams make faster decisions, automate routine work and improve operational performance at scale.
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AI creates value when data, decisions and execution are connected
WHY THIS AI FOR AVIATION CHALLENGE?
Airlines, airports and aviation service providers also need reliable data, clear ownership and workflows designed to use AI outputs responsibly.

A governed foundation brings relevant operational and business information together, applies the right controls and creates a repeatable route from experimentation to adoption. This allows teams to use predictive and generative AI where it can support a defined operational outcome, while people retain oversight of decisions that affect safety, service and performance.

主なメリット
Move from disconnected insight to practical, governed action across aviation operations.
チェックアイコン
Faster, more consistent decisions

Bring relevant signals together so teams can understand conditions and act with greater confidence.

チェックアイコン
Less manual effort

Automate repeatable information gathering, classification and workflow steps while preserving human control.

チェックアイコン
Earlier operational visibility

Use predictive models to identify emerging disruption, demand and asset patterns sooner.

チェックアイコン
AI that can scale responsibly

Apply data quality, access, monitoring and governance controls from pilot through production.

NTTデータのサポート体制は？

01
Prioritize the decisions that matter

Assess operational pain points, data readiness and value potential to select use cases with a clear owner, baseline and success measure.

Airline passenger using a smartphone while looking at an aircraft through the terminal window.
02
Build a trusted data foundation

Connect the authorized operational and enterprise data needed for each use case, with shared definitions, quality controls, security and traceability.

Integrated aviation data platform connecting operational and enterprise systems.
03
Apply the right AI pattern

Combine predictive analytics, optimization and generative AI according to the decision, workflow and risk involved rather than treating every challenge as the same technology problem.

Dashboard for monitoring aviation AI performance, governance and adoption.
04
Embed intelligence into aviation workflows

Integrate AI outputs into the tools and processes teams already use, with clear escalation paths and human validation for consequential decisions.

Commercial aircraft flying through a clear sky.
05
Govern, monitor and improve

Track data quality, model behavior, operational outcomes and adoption so the capability can be refined and extended with control.

Passenger using a smartphone while watching an aircraft in flight.
Aircraft maintenance technician inspecting an open commercial aircraft engine.
実証済みの効果
Measure operational outcomes, not model activity

AI creates value when it changes the performance of a real workflow. Establish the baseline before implementation and agree the target range, measurement period and data owner for each selected use case.

重要な結果
Move from isolated AI pilots to governed aviation intelligence
チェックアイコン
意思決定サイクル時間

Faster preparation and response for the selected operational decision.

チェックアイコン
Manual handling

Lower effort in repeatable information and workflow tasks.

チェックアイコン
Prediction quality

Improvement against the approved operational baseline.

チェックアイコン
Adoption and reuse

Active use by the intended teams and extension to additional approved workflows.

Scale AI with control

Connect your data, priority use cases and operating workflows in a practical roadmap for AI at scale, with measurable outcomes and human oversight built in from the start.

話しましょう

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