Transforming Airport Operations with Agentic AI

Ambition: Improve customer experience 

Managing real-time passenger information across dynamic environments requires speed, precision, and constant coordination. A leading airport authority operating a major Tier-1 international airport hub in North America—serving millions of passengers annually—faced operational challenges managing its terminal display ecosystem.

The airport’s flight information display systems (FIDS) and baggage information display systems (BIDS) span more than 850 screens across terminals, processing over 1.1 million daily API calls and handling 10,000+ flight updates each day.

Despite robust underlying infrastructure, daily operations encountered several pain points:

• Manual Operational Interventions: Routine disruptions—such as missing check-in counter allocations or stale gate displays caused by missed staff logouts—required complex manual overrides using specialized administrative tools.
• Cross-Team Coordination Friction: Resolving minor display discrepancies required step-by-step coordination across multiple teams, including the resource management unit (RMU), integrated operations control center (IOCC), and electronic display devices (EDD) teams.
• Rigid Legacy Workflows: Modifying existing system setups was slow and vendor-dependent, making it difficult for operational teams to adapt quickly to last-minute flight schedule changes.
• Resolution Delays and Passenger Risk: Gate status updates took between 30 and 40 minutes to resolve manually, increasing the risk of passenger confusion and boarding area friction.

Action: Empowering with Agentic AI

To streamline operations and eliminate manual bottlenecks, Wipro designed and deployed an Agentic AI Operational Assistant. Moving beyond basic informational chatbots, Wipro implemented a task-oriented, goal-driven agentic framework that allows non-technical staff to execute end-to-end operational actions through natural language.

Built on cloud-native AWS infrastructure using Amazon Bedrock, Anthropic Large Language Models, and Wipro’s WEGA framework, the solution acts as an intelligent co-pilot for airport staff.

Core Agentic AI Capabilities

• Autonomous Action Execution: Powered by specialized AI action groups, the agent doesn't just answer questions—it autonomously calls APIs, validates sector rules, and updates live operational databases.
• Natural Language Command Interface: Operational personnel can query system states, check flight allocations, and trigger status updates using plain language commands, eliminating the need for specialized application training.
• Automated Counter Allocation: The AI agent proactively detects missing check-in counter allocations for upcoming flights. If predefined sector rules are met, it updates display screens automatically; if human oversight is needed, it immediately routes targeted alerts to the responsible teams.
• Real-Time Gate Status Management: Staff can instantly query gate display statuses and trigger display resets to clear errors caused by missed logouts, keeping information shown to passengers accurate and up to date.
• Human-in-the-Loop Governance: Built-in enterprise guardrails ensure role-based permissions, execution logs, and seamless human escalation when rule boundaries are reached.

Ambition Realized 

By shifting from manual intervention to Agentic AI automation, the airport achieved significant gains in operational agility and passenger experience:

• 85%+ Faster Issue Resolution: Gate display status resolution time dropped from 30–40 minutes to under 5 minutes, virtually eliminating passenger confusion at boarding gates.
• 50 Hours Saved Monthly: Automating counter updates and gate resets saved 50 hours per month of effort across RMU, IOCC, and EDD operational teams.
• Prevented Operational Disruptions: Rapid status checks and automated workflow corrections prevented approximately 5 gate-related incidents per month.
• Simplified Operations: Non-technical operators can now handle complex routine tasks effortlessly, reducing reliance on specialized technical staff.
• Innovation Benchmark: Deployed a pioneering, task-driven Agentic AI solution within a high-throughput airport operational environment.