GCAA Enhanced Risk-Based Oversight Framework — Multi-Level Dashboard and AI Capabilities concept, covering Executive, Management, and Operational views with platform integrations.





Executive view — DG / ADG / Senior Leadership
UAE National Aviation Safety Score
94.2%
ICAO SSP compliance index · Updated daily

Active AOCs
47
+3 since Q1

Fleet size
912
Aircraft registered

Daily flights
3,850
Rolling 30-day avg

Critical risk operators
3
▲ 1 vs last month

Enforcement actions YTD
18
▼ 4 vs prior year

Audits completed YTD
84
92 planned

Open safety recs
12
4 overdue

National risk heat map — operator distribution Live
22
Low risk

15
Medium risk

7
High risk

3
Critical

Domain Low Med High Critical
Flight ops 14 7 3 1
Airworthiness 17 5 2 0
AVSEC 18 4 1 0
ANS 11 6 2 0
AI predictive alerts AI
⬤
Fatigue reporting surge — 3 operators
AI detected 47% increase over 45-day rolling window · Trigger: ROSI feed
⬤
Unstable approach rate rising — Operator A
Trend exceeds amber threshold for 2 consecutive months · FDM source
◆
Repeat SMS non-compliance — Operator B
4th recurrence within 12 months · Recurrence weight = ×3 · UAP finding
▲
Training deficiency trend — sector-wide
5 operators showing simulator currency gaps · VORSI + audit correlation
Powered by NLP + ML risk scoring engine · Risk = Severity × Occurrence × Recurrence weight

Oversight performance
Audits planned
92
Audits completed
84
91%
Ramp checks
134
Total findings
126
▲ 12%
Critical findings
7
Enforcement & safety recs
Active warnings
3
Operational restrictions
1
Suspensions
0
Open safety recs
12
Overdue recs
4
National SPIs Live
Unstable approaches
1.6/1k
▲
FDM exceedances
3.1/1k
→
Fatigue reports
26/mo
▲
Training deficiencies
5 cases
▲
Runway excursions
0
✓

Management view — Directors / Section heads / Principal inspectors
Avg operator risk score
18.4
Medium band

Inspector utilisation
78%
Optimal range

Repeat findings
23
▲ systemic risk flag

CAPA closure rate
71%
Target: 85%

Operator risk ranking AI scored
Operator A
48
Critical

Operator B
32
High

Operator C
21
Medium

Operator D
9
Low

Operator E
7
Low

Score = Severity × Occurrence × Recurrence weight · Sources: UAP + ROSI + VORSI + EAP

Repeat findings monitor Risk flag
Operator Finding area Count Score impact
Operator A SMS 4× –48 pts
Operator B FDTL 3× –27 pts
Operator C Training 2× –12 pts
Operator F Maint. control 2× –12 pts
Recurrence weight escalates ×2 at 2nd occurrence, ×3 at 3rd+. Auto-escalates to enforcement review at ×4.

Inspector workload
Al Mansouri
6 open
Rahman
4 open
Al Zaabi
5 open
Khalid
3 open
AI auto-assigns tasks by qualification + current load

Oversight cycle status
Low risk (24-mo cycle)
On track
✓
Medium risk (12-mo)
2 overdue
!
High risk (6-mo)
On track
✓
Critical (immediate)
Action req.
CAPA overdue
9 items
Enforcement pipeline EAP
Action type Count Status
Warning letter 3 Active
Restriction 1 Monitoring
Suspension 0 None
Safety directive 2 Active

Source: Enforcement Action Platform (EAP)

Operational view — Inspectors / Oversight officers
My assigned tasks
6
2 due this week

My open findings
14
3 awaiting CAPA

Next scheduled audit
Operator B
Apr 22 · FDTL focus

AI checklist suggestions
3
Based on ROSI flags

My operator risk profiles AI scored
Operator B
32
High

Operator C
21
Medium

Operator H
14
Medium

AI-generated checklist focus — Operator B audit
Focus: FDTL compliance (3 repeat findings)
Source: UAP findings × ROSI cross-reference
Check: Fatigue reporting process effectiveness
Source: VORSI volunteer reports — 4 fatigue events

My task board
Task Operator Due Priority
Targeted audit Operator B Apr 22 High
CAPA review Operator C Apr 24 Med
Ramp check Operator H Apr 28 Med
Profiling Q2 Operator D May 1 Low
Ramp check Operator E May 5 Low
Tasks auto-prioritised by risk score + due date. AI scheduling considers inspector load and expertise.

ROSI / VORSI flags Live
MOR — Operator B unstable approach (Major, ×2)
Received Apr 14 · Score: –6 pts applied
VORSI — Fatigue report (3 crew, Operator B)
Received Apr 10 · Correlated with MOR trend
ROSI — Training deviation (Operator C)
Received Apr 12 · CAPA requested

Safety recommendations SafetyRec
Total open recs
12
Assigned to me
3
Overdue
1
Due this month
2

Linked to Safety Recommendation Platform

Operator self-assessment queue
Awaiting review
4
CAPA auto-closed
11
Escalated to inspector
2
Tiered model: low-risk findings auto-close after CAPA submission + 30-day monitoring. High-risk: inspector mandatory review.

AI capabilities — integrated across all three dashboard tiers
AI risk score engine
Active
Severity × Occ × Recurrence

NLP reports processed
1,842
This month

Predictive alerts issued
27
14 acted on

Auto-checklists generated
38
This quarter

Core AI capability map
NLP report classification
Automatically categorises ROSI, VORSI, and audit narratives by severity, domain, and operator. Eliminates manual triage. Feeds risk scoring engine.

Predictive risk modelling
ML model detects emerging safety trends before threshold breaches. Identifies accident precursors from multi-source data patterns. Issues early alerts.

Auto checklist generation
Dynamically generates audit checklists tailored to each operator’s risk profile, recent ROSI/VORSI events, and domain-specific findings history.

Inspector workload AI
Optimises assignment of oversight tasks based on inspector qualifications, operator risk level, aircraft type expertise, and current workload balance.

Recurrence detection
Tracks repeat findings across operators and audit cycles. Automatically escalates recurrence weight in risk scoring and triggers enforcement review flags.

CAPA effectiveness scoring
Evaluates quality of operator CAPA submissions against historical re-occurrence data. Flags superficial corrective actions before inspector closure approval.

Safety intelligence reports
Auto-generates monthly safety intelligence briefings for management with trend charts, top-risk operators, sector-wide SPI movements, and recommended oversight actions.

Cross-platform correlation
Correlates data across ROSI, VORSI, UAP, EAP, and SafetyRec to detect multi-signal risk patterns invisible in any single platform. Feeds unified risk profile.

AI data flow — how intelligence is produced
ROSI
VORSI
UAP Audit

EAP Enforce.
SafetyRec
FDM / SPIs

↓
Unified Aviation Data Platform
↓
AI Risk Scoring Engine
NLP · ML prediction · Recurrence tracking
↓
Executive alerts
Mgmt risk board
Inspector tasks

AI maturity roadmap
Phase 1 — Foundation
Live
Risk categorisation, dynamic dashboard, inspector training
Phase 2 — AI core
In progress
NLP filtering, ML risk scoring, auto checklist generation
Phase 3 — Integration
Planned
Full cross-platform correlation, predictive oversight planning
Phase 4 — Predictive governance
Future
Digital twin integration, autonomous alert-to-action

Platform integration — ROSI · VORSI · UAP · EAP · Safety Recommendation Platform
Platforms integrated
5
Unified risk profile

Real-time feeds
3
ROSI · VORSI · FDM

Cross-platform events
184
This month

AI correlations found
27
Cross-platform signals

Platform directory
ROSI
Reporting of Safety Incidents
43
reports this month

VORSI
Voluntary Safety Reporting
28
reports this month

UAP
Unified Audit Platform
84
audits YTD

EAP
Enforcement Action Platform
18
actions YTD

Safety Recommendation Platform
Tracks ICAO / investigation recommendations
12
open recommendations

Integration detail
Click a platform card on the left to see how it integrates with the ERBOF dashboard and AI capabilities.

How the unified risk profile is constructed AI
ROSI finding → severity score → deducted from operator profile
VORSI report → NLP classification → correlated with ROSI patterns
UAP audit finding → scoring formula → recurrence tracking
EAP enforcement → risk escalation → oversight frequency trigger
SafetyRec overdue → risk weight added → inspector task auto-created
FDM / SPI trend → AI alert → targeted audit scope generation
All platform events flow into the Unified Aviation Data Platform → AI Risk Scoring Engine → refreshes operator risk profile → cascades to all three dashboard tiers in real time.