Final Scope

BACKGROUND

Airports today face an increasingly complex landscape characterized by a few challenges, such as operational inefficiencies, fluctuating passenger demands, and the ever-growing need to enhance the customer experience. These challenges are exacerbated by the dynamic nature of air travel, which demands rapid adaptation to changing conditions, whether due to unexpected surges in passenger numbers, shifts in travel patterns, or the need to respond to sudden disruptions. Traditional approaches to managing these issues relied on human inputs, which can cause delays, increased operational costs, and suboptimal passenger experiences. Large Language Models (LLMs) have the ability to interpret diverse forms of user textual inputs and generate contextual responses on demand. By processing vast amounts of data in real-time and efficiently delivering responses, LLMs have the potential to revolutionize the way airports interact with passengers and enhance operational efficiencies. Recognizing this potential, some airports have begun integrating this technology into their operations. However, it remains unclear how the broader airport industry can fully leverage LLMs. The potential costs and risks associated with adopting LLMs have yet to be thoroughly explored.

OBJECTIVE & AUDIENCE

The objective of this synthesis is to document how Large Language Models (LLMs) are being incorporated  into the airport enviornment to enhance passenger experience. The audience for this synthesis are airport practitioners that are responsible for passenger experience and those involved in technology evaluation.

INFO TO BE GATHERED

Information to be describe in a concise report includes (but is not limited to):

•         A literature review of the application of LLM’s and how they can be incorporated into the airport environment.

o   The airport enviornment may include opertations, maintenance, security, etc. which can ultimately effect the passenger experience.

•        A literature review of the application of LLM’s in adjacent industries that could be applicable to airports.
•        Documenting challenges that airports have faced during the adoption of LLMs, including the establishment of governance and security, planning, and implementation and scalability.
•         Documenting airports goals for implementing LLMs, and the benefits asscoiated with the adopton.
•         Documenting the unanticipated risks associated with adopting LLMs.
•         Documenting the issues around adoptability based on organizational size and complexity.
•         Case examples of typical and unique airport practices that have integrated, or are planning to adopt, Large Language Models (LLMs) into their operations.
•         Identifying knowledge gaps and suggestions for future research.

Information will be collected through literature review, a survey of airports, and interviews with selected airports for the development of case examples. Knowledge gaps and suggestions for future research to address those gaps will also be identified.

STATUS: A research agency has been selected for the project. The contracting process is underway.