Travel services are increasingly shaped by digital platforms, data-driven decision making and connected devices. This conceptual paper examines how Artificial Intelligence (AI) and the Internet of Things (IoT) can jointly improve the travel experience, with particular attention to personalised ticket discovery, recommendation, dynamic pricing, baggage visibility and service retention. The paper is grounded in the ideas reported by Hindustan Times in March 2021 from an interaction with Aamir Junaid Ahmad, then CEO of BusAndTicket.com, and extends those ideas through a focused review of tourism technology literature. The source case proposed AI-supported search and recommendations that become more personalised as service-use information accumulates; it also discussed a proposed dynamic bus-ticket pricing approach using variables such as weather, events and seat availability, subject to stakeholder approval. For IoT, the case proposed sensor-based baggage monitoring that could notify travellers when luggage is loaded, adjusted, unloaded or accessed. Based on these use cases, the paper develops a conceptual AI-IoT travel-experience framework linking data capture, intelligent processing, context-aware service delivery and feedback. The analysis suggests that the strongest value arises when AI converts connected data into timely decisions while IoT supplies reliable real-world signals. The paper also identifies implementation issues involving data quality, privacy, cybersecurity, cost, interoperability, transparency and human oversight. The framework provides a basis for future empirical research on smart travel services in bus, rail, air and hospitality contexts.
Artificial Intelligence; Internet of Things; Smart Tourism; Travel Experience; Personalisation; Dynamic Pricing; Baggage Tracking; Recommender Systems