How AI can boost passenger services at Kenyan airports

In 2023, the number of global air passengers reached nearly 8.5 billion, or 27 percent above 2022 levels, and 94 percent when compared to 2019 figures, according to Airports Council International.

What that means is that on any given day, more than 20 million air travellers underwent the most basic airport processes of check-in, security screening, and border control.

For the average international air traveller, those processes would lead them to a shopping experience filled with pleasant scents from the latest fashion houses, appealing food and beverage offerings, gifts shops and the like. And soon after that the all-too-familiar rush to find the right boarding gate to catch the flight.

However, the increasing anxiety associated with air travel has prompted airports to invest in improving passenger experiences. Artificial intelligence (AI) and machine learning (ML) have emerged as transformative tools with numerous applications to enhance airport operations. These technologies optimise resource allocation, improve security measures, while promising to elevate passenger experiences.

How can airport operators harness the power of AI to create unique value propositions to remain competitive?

Airports operate in intensely competitive environments. For many travellers and visitors’ airports seem to be large, complex entities with alternatives sometimes located hundreds of miles away. In truth airports are in the service business in very competitive regional and international market place.

In that economic space success is assessed by an airport’s ability to attract and retain customers as well as other service providers such as airlines, retail service providers, real estate developers and even freight forwarders. As a result, airports are largely assessed on established service quality metrics like value for money and customer satisfaction. As AI and ML revolutionise airport functions, it is crucial for airports to embrace these advancements to stay efficient and competitive.

AI enhances airport security by improving threat detection, identifying suspicious behaviours, and mitigating risks in real time. Additionally, AI-powered analytics personalise passenger services, optimising the journey from check-in to boarding.

AI and machine learning can enhance airport security by analysing past incidents to recognise patterns linked to prohibited items or suspicious behaviour. These algorithms process real-time data from security cameras, metal detectors, and screening equipment to automatically flag potential threats, supporting human security personnel with real-time alerts for closer inspection.

Additionally, AI-powered facial recognition systems compare passenger images against databases of registered travellers or persons of interest, streamlining identity verification, improving security, reducing wait times, and enhancing passenger flow through the airport.

AI can optimise baggage handling by tracking bags with radio frequency identification tags or barcodes, using ML to predict baggage flow, identify congestion points, and detect issues like misplaced luggage. This improves efficiency, reduces delays, and minimises lost baggage, enhancing the passenger experience.

Additionally, AI-powered chatbots and virtual assistants provide personalised assistance, answering questions, offering real-time flight updates, and recommending airport services. By automating tasks, these tools improve the passenger experience and ease the workload on airport staff.

AI and ML can significantly enhance airport operations by analysing historical flight data, weather forecasts, and air traffic patterns to optimise flight schedules and routes, minimising delays, reducing fuel consumption, and improving airspace usage. This benefits both passengers and the environment.

AI can also optimise resource allocation by analysing passenger traffic, flight schedules, and resource availability. Algorithms can dynamically assign gates, check-in counters, optimise staffing levels, and adjust security procedures to reduce wait times. These improvements boost operational efficiency, reduce costs, and enhance the passenger experience.

Airports are data rich environments. As such AI and ML are essential and cannot be overlooked in the pursuit of improving the customer experience. The foundational principles include data collection, data processing, selecting the right algorithms to effectively AI train models.

At the back end it is also crucial to ensure seamless integration with various systems within the environment to enable analysis and prediction. By leveraging AI algorithms, airports and airport operators can make proactive decisions, predict bottlenecks, and optimise daily operations for improved efficiency and enhanced customer satisfaction in a competitive environment.