Beyond Automation: AI as the Catalyst for Connected Travel and Transport

The travel and transportation industry is at a pivotal moment. As global supply chains grow more complex and customer expectations rise, organizations must evolve beyond traditional models to remain competitive. Artificial Intelligence (AI), the Internet of Things (IoT), and real-time analytics are no longer emerging technologies—they are essential tools for driving integration across customer experience, operations, and supply chains. 

This theme was powerfully echoed during the Empowering Beyond Summit 2025, where Carlos Hernandez, Managing Partner at Avasant, led a compelling panel discussion titled “Reinventing the Passenger Experience: The Future of Smart, Connected Travel.” Joined by Sunny Bajaj of BNSF Railway, Mustafa AlAusaje of the Greater Toronto Airports Authority (GTAA), and Richard Kabrt of WNS Global Services, the panel explored how digital transformation is reshaping the movement of people and goods across the globe.  

The discussion highlighted how AI and IoT are enabling predictive decision-making, seamless mobility, and hyper-personalized engagement—transforming not just operations, but the entire passenger journey. From rail to air to logistics services, panelists emphasized the need for real-time data integration, cross-industry collaboration, and sustainability-driven innovation. 

This article explores how leading organizations in travel and transportation are embracing AI to accelerate digital integration. From predictive maintenance and dynamic pricing to intelligent baggage handling and multimodal travel coordination, AI is reshaping the industry’s future—one data-driven decision at a time. For C-level executives, the imperative is clear: adopt a comprehensive digital strategy that leverages AI to unlock new value, enhance resilience, and align with sustainability and regulatory goals. As Carlos Hernandez noted, “Digital integration is no longer optional—it’s the foundation for future-ready transportation ecosystems.” 

Business Challenge

A global logistics company and a major international airport faced similar challenges: fragmented systems, siloed data, and increasing pressure to deliver seamless, efficient, and personalized services. The logistics firm struggled with unpredictable freight movement, leading to customer dissatisfaction and supply chain disruptions. Meanwhile, the airport grappled with baggage handling inefficiencies, aircraft turnaround delays, and limited real estate for expansion. 

To address these issues, both organizations launched AI-driven digital transformation initiatives. The logistics company implemented predictive analytics to optimize freight routing and improve service reliability. By integrating GPS data, IoT sensors, and customer feedback, they created a real-time visibility platform that enabled proactive decision-making and improved customer communication. 

The airport deployed AI-powered computer vision and sensor-based monitoring to track baggage systems and apron operations. Predictive maintenance algorithms helped achieve 99.5% baggage system availability, while AI analytics ensured efficient aircraft turnaround, maximizing limited gate capacity and enhancing passenger flow. 

These initiatives marked a shift from reactive to proactive operations. By embracing AI and real-time analytics, both organizations built scalable, secure, and responsive systems that improved performance, reduced costs, and elevated customer satisfaction. 

Observed Trends

The integration of AI, IoT, and real-time analytics delivered transformative results across several key areas: 

1. 1. Predictive Maintenance
      IoT sensors embedded in vehicles, baggage systems, and infrastructure enabled continuous monitoring of asset health. AI algorithms analyzed sensor data to predict failures before they occurred, reducing unplanned downtime by up to 20% and improving asset availability to over 99%. This proactive approach minimized service disruptions and extended equipment lifespan1. 

1. 2. Dynamic Pricing
      AI models processed real-time data on demand, weather, and customer behavior to optimize pricing strategies. Transportation providers could adjust fares dynamically, maximizing revenue while maintaining competitiveness. This was particularly effective during peak periods or in response to disruptions, enabling agile pricing decisions that aligned with market conditions. 

1. 3. Seamless Mobility
      Integrated digital platforms connected airlines, railways, hotels, and car rental services. In the event of a disruption, AI systems automatically rebooked passengers, offered hotel accommodations, and adjusted car rental schedules. This reduced refund rates by 20% and improved Net Promoter Scores (NPS) by 15%, demonstrating the value of interconnected, customer-centric ecosystems. 

1. 4. Hyper-Personalized Engagement
      AI-driven platforms used customer data to deliver personalized travel recommendations, real-time updates, and tailored services. This enhanced passenger experience, increased loyalty, and opened new revenue streams through targeted cross-selling and upselling. 

1. 5. Key Technologies and Data Sources
      • Technologies: Machine learning, edge computing, computer vision, and blockchain.
      • Data Sources: GPS, IoT telemetry, customer service logs, biometric systems, and operational feedback.

These technologies ensured scalability and security while supporting sustainability goals. For example, AI-optimized routing reduced fuel consumption and emissions, aligning with environmental targets. Blockchain enabled secure, transparent data sharing across partners, enhancing trust and compliance. 

Takeaway 

For C-level executives, the message is clear: AI-powered digital integration is not a future ambition—it’s a present necessity. To build a scalable, secure, and sustainable strategy: 

• • Invest in AI and IoT Infrastructure: Establish platforms that support real-time data ingestion, processing, and decision-making. 

• • Break Down Data Silos: Integrate customer, operational, and supply chain data into a unified ecosystem. 

• • Foster Cross-Functional Collaboration: Align IT, operations, and customer experience teams around shared digital goals. 

• • Prioritize Sustainability and Compliance: Use AI to optimize resource usage and ensure adherence to evolving regulatory frameworks. 

By taking these steps, organizations can transition from fragmented operations to intelligent, interconnected ecosystems that deliver superior customer experiences, operational resilience, and long-term growth. 

Conclusion 

AI is redefining the travel and transportation landscape. From predictive maintenance and dynamic pricing to seamless mobility and hyper-personalized engagement, AI, IoT, and real-time analytics are unlocking new value across the enterprise. 

For C-level leaders, the opportunity is to lead this transformation with a bold, integrated digital strategy. Those who act now—investing in the right technologies, building the right partnerships, and aligning with the right values—will not only stay competitive but set the standard for the industry. 

The future is seamless, intelligent, and sustainable. The time to accelerate is now. 

By Lu Esan, Director, Supply Chain & Procurement