US-12626315-B2 - Systems and methods for identifying travel options for users consistent with corporate travel policies

US12626315B2US 12626315 B2US12626315 B2US 12626315B2US-12626315-B2

Abstract

Systems and methods are provided for identifying travel options, for users, consistent with corporate policies. One example computer-implemented method includes receiving, from a user, a travel request for travel from an origin to a destination and retrieving additional input data including environmental, social and/or governance (ESG) goals of a first entity, with which the user is associated, and a carbon offset program of the first entity. The method also includes applying a generative artificial intelligence (AI) model to the travel request, the ESG goals of the first entity and the data representative of the carbon offset program, to generate an output travel recommendation that includes a travel itinerary and a carbon offset purchase option. The method then includes presenting the travel recommendation to the user and purchasing the carbon offset option from the recommendation, from a participant, in response to acceptance of the travel recommendation by the user.

Inventors

Justin Harnish
Mohit Taneja
Natesh Babu Arunachalam
Nick Baguley
Nolan Fillet

Assignees

MASTERCARD INTERNATIONAL INCORPORATED

Dates

Publication Date: 20260512
Application Date: 20240724

Claims (18)

1 . A computer-implemented method for identifying travel options, for users, consistent with corporate policies, the method comprising: receiving, from a user, at an intelligence platform computing device, a travel request for travel from an origin to a destination, the user associated with an entity; retrieving, by the intelligence platform computing device, from a data structure, additional input data, the additional input data including one or more environmental, social and/or governance (ESG) goals of the entity and a carbon offset program of the entity; and then (1) applying, by the intelligence platform computing device, a generative artificial intelligence (AI) model to the travel request, the retrieved one or more ESG goals and the data representative of the carbon offset program, to generate an output travel recommendation, the output travel recommendation including a travel itinerary and a carbon offset purchase option; (2) presenting, by the intelligence platform computing device, the output travel recommendation to the user; (3) receiving, by the intelligence platform computing device, an acceptance of the output travel recommendation by the user; and (4) purchasing the carbon offset purchase option from the output travel recommendation, from a participant, in response to the acceptance of the output travel recommendation by the user.
2 . The computer-implemented method of claim 1 , wherein the travel request further includes a departure date and a return date; and wherein the itinerary is consistent with the departure date and the return date.
3 . The computer-implemented method of claim 1 , wherein the carbon offset program includes: a number of carbon offset participants; ones of the corporate policies, which are indicative of eligible ones of the carbon offset participants; and/or a budget for purchase of carbon offsets for the carbon offset program.
4 . The computer-implement method of claim 1 , wherein the additional data further includes a user profile, the user profile including a selection of one of multiple carbon offset participants.
5 . The computer-implement method of claim 1 , further comprising: converting, by the intelligence platform computing device, the travel request and the additional input data to embeddings representative of the travel request and the additional input data, prior to applying the generative AI model; and converting the output travel recommendation from the embeddings into natural language, prior to presenting the output travel recommendation to the user.
6 . The computer-implemented method of claim 5 , further comprising: applying, by the intelligence platform computing device, one or more output controls, prior to presenting the output travel recommendation to the user.
7 . The computer-implemented method of claim 1 , wherein the travel request is for airline travel; and wherein the itinerary includes at least one flight from the origin to the destination.
8 . The computer-implemented method of claim 1 , further comprising: receiving, by the intelligence platform computing device, a decline of a prior output travel recommendation; and wherein applying the generative AI model includes applying the generative AI model to the decline of the prior output travel recommendation.
9 . A non-transitory computer-readable storage medium including executable instructions for use in identifying travel recommendations, which, when executed by at least one processor, cause the at least one processor to: receive, from a user, a travel request for travel from an origin to a destination, the user associated with an entity; retrieve, from a data structure, additional input data, the additional input data including one or more environmental, social and/or governance (ESG) goals of the entity and a carbon offset program of the entity; and then (1) apply a generative artificial intelligence (AI) model to the travel request, the one or more ESG goals and the data representative of the carbon offset program, to generate an output travel recommendation, the output travel recommendation including a travel itinerary and a carbon offset purchase option; and (2) present, via an output device, the output travel recommendation to the user, thereby permitting acceptance of the output travel recommendation and purchase of the carbon offset purchase option from the output travel recommendation, from a participant, in response to an acceptance of the output travel recommendation by the user.
10 . The non-transitory computer-readable storage medium of claim 9 , wherein the travel request further includes a departure date and a return date; and wherein the itinerary is consistent with the departure date and the return date.
11 . The non-transitory computer-readable storage medium of claim 9 , wherein the executable instructions, when executed by the at least one processor, further cause the at least one processor to: convert the travel request and the additional input data to embeddings representative of the travel request and the additional input data, prior to applying the generative AI model; and convert the output travel recommendation from the embeddings into natural language, prior to presenting the output travel recommendation to the user.
12 . The non-transitory computer-readable storage medium of claim 9 , wherein the carbon offset program includes: a number of carbon offset participants; policies indicative of eligible ones of the carbon offset participants; and/or a budget for purchase of carbon offsets for the carbon offset program.
13 . The non-transitory computer-readable storage medium of claim 9 , wherein the executable instructions, when executed by the at least one processor, further cause the at least one processor to receive a decline of a prior output travel recommendation; and wherein the executable instructions, when executed by the at least one processor, cause the at least one processor, in applying the generative AI model, to apply the generative AI model to the decline of the prior output travel recommendation, as part of the additional input data.
14 . A system for identifying travel options, for users, consistent with corporate policies, the system comprising at least one computing device configured to: receive, from a user, a travel request for travel from an origin to a destination, the user associated with an entity; retrieve, from a data structure, additional input data, the additional input data including one or more environmental, social and/or governance (ESG) goals of the entity and a carbon offset program of the entity; and then (1) apply a generative artificial intelligence (AI) model to the travel request, the one or more ESG goals and the data representative of the carbon offset program, to generate an output travel recommendation, the output travel recommendation including a travel itinerary and a carbon offset purchase option; and (2) present, via an output device, the output travel recommendation to the user, thereby permitting acceptance of the output travel recommendation and purchase of the carbon offset purchase option from the output travel recommendation, from a participant, in response to an acceptance of the output travel recommendation by the user.
15 . The system of claim 14 , wherein the travel request further includes a departure date and a return date; and wherein the itinerary is consistent with the departure date and the return date.
16 . The system of claim 14 , wherein the at least one computing device is further configured to: convert the travel request and the additional input data to embeddings representative of the travel request and the additional input data, prior to applying the generative AI model; and convert the output travel recommendation from the embeddings into natural language, prior to presenting the output travel recommendation to the user.
17 . The system of claim 14 , wherein the carbon offset program includes: a number of carbon offset participants; ones of the corporate policies, which are indicative of eligible ones of the carbon offset participants; and/or a budget for purchase of carbon offsets for the carbon offset program.
18 . The system of claim 14 , wherein the at least one computing device is further configured to: receive a decline of a prior output travel recommendation; and apply the generative AI model to the decline of the prior output travel recommendation, as part of the additional input data.

Description

FIELD The present disclosure generally relates to systems and method for use in identifying travel recommendations and associated offsets, for users, consistent with corporate environmental, social and/or governance (ESG) policies, through generative artificial intelligence (AI). BACKGROUND This section provides background information related to the present disclosure which is not necessarily prior art. Corporate travel is provided to enable employees, executives, contractors, etc. (broadly, users), to be in places pertinent to job situations, duties, etc. In selecting travel, users are known to have options in specific travel for corporate purposes, such as, for example, mode of travel, time of day, day of week, etc. In connection therewith, corporations are known to impose travel policies, which limit certain options, including, specifically, the cost associated with the travel, travel class, modes of travel, etc. Corporations often employ platforms that offer options to users, where the options are consistent with one or more policies. DRAWINGS The drawings described herein are for illustrative purposes only of selected embodiments and not all possible implementations, and are not intended to limit the scope of the present disclosure. FIG. 1 illustrates an example system of the present disclosure suitable for use in identifying travel recommendations and associated offsets, for users, consistent with corporate environmental, social and/or governance (ESG) policies; FIG. 2 is a block diagram of an example computing device that may be used in the system of FIG. 1; and FIG. 3 is an example method for identifying travel recommendations and associated offsets, for users, consistent with corporate ESG policies. Corresponding reference numerals indicate corresponding parts throughout the several views of the drawings. DETAILED DESCRIPTION The description and specific examples included herein are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. Users employed or otherwise associated with corporations may be limited to corporate travel by policies of the corporations. In some instances, the corporations often employ platforms that offer travel options to the users, where the options are consistent with one or more policies. In this way, alternate options are often hidden, along with the policies, whereby users are not offered insights into the alternate travel options. What's more, corporate policies are limited, generally, to cost, eligibility for tax treatment, etc., while goals, policies, etc., related to environmental, social, and/or governance (ESG) are omitted. Uniquely, the systems and methods herein provide a generative artificial intelligence (AI) platform, which is configured to rely on ESG data and offset programs, in identifying travel recommendations and associated offsets, for corporate travel by users. FIG. 1 illustrates an example system 100, in which one or more aspects of the present disclosure may be implemented. Although the system 100 is presented in one arrangement, other embodiments may include systems arranged otherwise depending, for example, on travel options, transit options, accessibility of transit data, accessibility of user data, processing of purchase options for travel, etc. The system 100 generally relates to travel planning for a corporation 102, and includes a communication device 104 of a user 106 and an intelligence platform 108 (in communications with and/or including a data structure 116). The intelligence platform 108 is coupled in communication with a travel management platform 110 of the corporation 102, a travel provider 112, and a program participant 114, via one or more networks. The networks are represented by the arrowed lines, and may include, without limitation, a local area network (LAN), a wide area network (WAN) (e.g., the Internet, etc.), a mobile network, a virtual network, and/or another suitable public and/or private network capable of supporting communication among two or more of the parts illustrated in FIG. 1, or any combination thereof. The corporation 102 (broadly, an entity) is a business entity in this example embodiment, which engages with customers to provide services, products, etc., to the customers. The corporation may be organized under any applicable law, regulations, etc., and is not limited to a legal definition of corporation. The corporation 102 may be for profit or nonprofit, and/or may be a governmental agency, a partnership, etc. The user 106, in this example embodiment, is an employee of the corporation 102, and is assigned responsibilities that require travel, from time to time. The term “employee” is intended to be broad and includes any person that is hired, appointed, or associated with the corporation 102 to perform one or more tasks on behalf of the corporation 102. As such, the user 106 may be a worker, staff person, contractor, board member, executive, etc. of (or ass