By Benadeta Mwaura - Reporter
Kenya, January 30 2026 - As air travel continues its strong post-pandemic recovery, airports around the world are increasingly deploying artificial intelligence (AI) technologies to manage surging passenger volumes and enhance operational efficiency.
Passenger traffic is forecast to reach 10.2 billion in 2026, a 3.9 per cent year-on-year increase over 2025, creating pressure on airport infrastructure, staffing and customer service systems that traditional methods alone struggle to handle.
Industry leaders say AI systems are now being embedded into virtually every aspect of airport operations, from predicting crowding at security and immigration checkpoints to optimising baggage handling and powering personalised passenger experiences.
Analysts at the Airport AI Exchange event highlighted how AI-powered analytics are shifting airports away from reactive crowd management toward predictive and proactive operations that can anticipate congestion before it occurs.
Across major global hubs, AI is already delivering results:
Passenger Flow and Congestion Management: AI-based analytics help airports forecast bottlenecks at security, immigration and boarding gates, enabling better allocation of staff and resources and minimizing delays.
For example, emerging technologies are giving airports a real-time view of passenger density so they can optimise queue flows and reduce peak-hour congestion, a crucial capability as global air travel rebounds.
Predictive Maintenance and Safety Enhancements: Beyond crowds, AI supports predictive runway and equipment maintenance, helping operators detect potential issues with infrastructure before they cause disruptions.
Some airports use drones paired with computer-vision systems to spot foreign object debris (FOD) on runways and alert ground crews for rapid removal, enhancing both safety and reliability.
Biometric and Contactless Processing: Biometric e-gates and AI-enabled identity verification systems let passengers move through immigration and boarding with minimal physical interaction, improving both speed and hygiene.
Airports increasingly use these systems to streamline border control processes and deliver a smoother security experience.
Baggage Handling and Lost-and-Found Solutions: AI is transforming baggage operations as well.
Autonomous baggage tractors and optimisation systems can transport luggage more efficiently, while AI-driven lost-and-found services, such as those trialled at Jaipur International Airport, have reported up to 85 per cent recovery rates by automatically logging and tracking misplaced items with camera and sensor networks.
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Personalised Passenger Experience: Some airports have adopted multilingual AI passenger assistants and concierge services that help travellers with flight information, wayfinding and real-time service queries, boosting satisfaction and reducing pressure on human staff. Strategic partnerships, like the one between Adani Airports and AIONOS, illustrate how airports are blending AI with customer service to provide tailored support at scale.
Airports that adopt AI technologies see a range of business and operational gains:
Operational Efficiency: AI-driven turnaround and gate allocation systems have been shown to cut ground delays and aircraft taxi times, reducing fuel consumption and improving punctuality.
Security and Safety: Integrated AI systems can analyse vast amounts of security data instantly, detecting anomalies and potential threats faster than manual monitoring alone.
Revenue Growth: By creating smoother, more enjoyable travel experiences, airports can boost retail and non-aero revenues as passengers spend more time and money in terminals. AI’s ability to personalise offers and services helps support ancillary revenue streams alongside core operational improvements.
Despite its transformational potential, AI implementation faces structural and cultural barriers within the aviation industry.
Many airport systems still rely on legacy infrastructure that is difficult to integrate with modern AI platforms, and the sector’s safety-critical nature means that regulation and caution often slow adoption, a reality echoed by AI experts who note that aviation’s use of advanced AI remains “comparatively limited” relative to other sectors.
Additionally, issues around data interoperability, privacy and cybersecurity must be carefully managed as airports integrate AI across jurisdictions and legacy technologies, a challenge highlighted in global industry surveys.
As global air travel rebounds and continues to grow, AI is poised to become a standard element of airport operations rather than an experimental add-on.
Aviation stakeholders, from airport operators and airlines to technology partners, are increasingly investing in machine learning, predictive analytics, biometric processing and robotics to build “smart airports” that can handle capacity, complexity and customer expectations without proportional increases in staff or physical infrastructure.
In regions like the Middle East, Europe and North America, AI integration into airport systems is already supporting more efficient, resilient and passenger-friendly travel networks, a model that other regions, including Africa, are watching closely as they expand their own aviation sectors.
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