May 18, 2024

GBTA report shows AI impact on business travel

A report based on a session at last year’s GBTA Europe Conference in Hamburg has identified how Artificial Intelligence is impacting business travel management.

Co-produced by GBTA and BCD Travel, the report summarises the collaborative feedback from 700-plus travel industry professionals across Europe and APAC who took part in The Big Idea session at the conference.

It identifies areas where travel programmes may be transformed by AI, which include:

Sourcing and contracting

In the AI-driven landscape of travel sourcing and contracting, sourcing strategies dynamically adapt based on market conditions and company objectives.

Traveller servicing

AI revolutionises traveller servicing, automating for example the identification for visa needs and applications, and dynamically managing risks in evolving situations. It introduces language translation, crucial for conferences and emergency alerts for example, ensuring seamless communication tailored to individual preferences.

Distribution and booking

Distribution undergoes a transformation with multi-channels. The Online Booking Tool (OBT) is not the unique point of entry anymore. AI’s predictive capabilities anticipate travel needs, enabling policy-compliant suggestions even in the absence of an OBT. Multi-channel booking becomes more efficient, predominantly for simple bookings, emphasising the cost benefits of increased online transactions.

Booking enhancements

AI redefines the booking experience with seamless anticipatory capabilities (not OBT related), simplifying the process for travellers. The prevalence of online bookings rise, reducing costs through fewer offline transactions. The integration of conversational solutions (chat) and personalised recommendations further enhances the user experience. Chat takes over voice.

Strategy implementation

AI interprets voice, messages, and data for valuable insights into the travel experience, providing actionable feedback for strategy refinement.

Analytics and data integration

In the digital era, AI links disparate data points to identify issues. It brings together digital information to provide comprehensive analytics, enhancing decision-making capabilities.

Governance dynamics

AI introduces flexibility into policy application, allowing for real-time adjustments based on market conditions or corporate objectives. It adapts contracts, sourcing approaches, and overall processes to align with evolving business needs.

The report also identified the following challenges:

Technology maturity and trust dynamics

As technology matures, the acceptance of technology being able to comprehend enquiries (including tone of voice, body language) and technology-driven decisions, and the tolerance for occasional mistakes, just like humans make mistakes, are two concerns.

Authenticity and human touch integration

Preserving authenticity and integrating a human touch remains pivotal to enhance the users’ experience.

Data copyright and IP rights

The use of copyrighted material in training datasets leads to questions on the ownership of the content generated.

Corporate policy

The interplay of corporate policies, regional differences, and sector-specific needs becomes evident. A deeper understanding of these nuances is crucial for tailoring the technology to diverse organisational landscapes.

User privacy and confidentiality

There is an inherent tension between harnessing the capabilities of AI and safeguarding user privacy.

Information security and regulatory landscape

Addressing cyber threats, confidentiality, and regulatory gaps is critical for reliable usage. Legal frameworks that adapt to the evolving landscape of AI technology are needed.

Integrity and Ethical Considerations

Guarding against data manipulation and external influences: ensuring the integrity of data and responses, avoiding potential manipulation and external influences (bias). For example, how does user feedback or paid content influence the output?

Accountability and liability

Clear protocols for addressing mistakes and assigning responsibility must be considered.

Transparency in data usage and ownership

Ensuring clarity about data sources: what data is being used or shared, who owns the data, and what are the sources of outputs?

Job security

Programmes should emphasise an AI focus on improving the traveller experience rather than solely economising the supply chain

The report outlines key lessons for the industry:

Find effective business applications

Are there places in your programme where AI can start to make a difference?
Top tip: it doesn’t have to be a high impact scenario nor a huge effort. Don’t just implement AI for the sake of it.

Testing is key

AI is an ongoing journey; it is in constant evolution. Start small by implementing AI supported by human touchpoints, with processes in place to make sure of the accuracy of the technology.

Adoption will depend on a few key factors:

  • Corporate culture
  • Traveller culture
  • Risk tolerance.

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