Credit: Adobe Stock Golden Sikorka
GETTING IT DONE
Target Areas for AI Prompting
- Data queries and analysis—no
more downloads and pivot tables
- Policy – Reformat as a Q&A
so a chatbot can answer policy questions accurately
Success Strategies
- Zero-shot prompts—have a clear
objective from the outset; be precise and provide context as well as a format
for the output you want.
- Prompt stacking—approach like a
recipe; each step builds on the other
- Role playing—giving the AI a
professional point of view like “you are an HR professional” provides context
clues and direction for the output
Amazon CEO Andy Jassy, in a June interview with CNN, said AI “will
change how we all work and live,” including “billions” of AI agents “across
every company and in every imaginable field…. Many of these agents have yet to
be built, but make no mistake, they’re coming, and coming fast.”
Corporate travel management, of course, is not immune. During a BTN Hot Topics 2026 webinar, travel buyers
emphasized that effective communication with AI—known as AI prompt
engineering—is a crucial skill for travel managers who want to remain relevant.
“Learning prompts [and] learning how to interact with AI is chief,” said
ServiceNow senior manager of global travel and expense Heather Allegrina. “Being able to ask questions of data and get answers without having
to do downloads and pivots… that has been a gamechanger for us.”
For travel managers looking to
integrate AI into their programs, Allegrina recommended restructuring travel
policy information it into a Q&A format “so an AI bot can read and answer
questions… that will help when employees are asking native questions”.
At the GBTA Europe Conference in Hamburg in November, PredictX CEO Keesup Choe
led an AI session titled 'Rise of the Agents', where he described prompt
engineering as the foundation for mastering AI agents.
“Prompt engineering is how to communicate to large language models to
get them to do what you want,” said Choe. “It’s more a language than a code.”
He shared the following techniques:
Zero-shot Prompt Engineering
When you ask AI to handle a task without providing any prior examples,
training or detailed instructions. “It’s like asking a colleague to write a
report on a topic they’ve never covered before,” Choe explained. Clear
instruction is therefore critical and should comprise:
- Subject: State main topic or focus of
task (e.g. hotel spend)
- Action verb: Use a clear command to direct
the AI, such as ‘analyze’ or ‘list’ instead of simply saying “give me”
- Task description: Specify what needs to be done
with the subject (e.g. provide key financial metrics)
- Context (optional): Add details like audience,
purpose or scope (e.g. for a business analyst preparing a report)
- Tone/format: Define the tone and output
format (e.g. bullet points, table)
- Constraints (optional): Include
limits like word count or specific requirements (for the period 2024-2025)
For example, instead of simply writing “tell me about my hotel spend”, Choe
suggested the following:
I need you to analyze our hotel
spend and give me these metrics for YTD 2025 only: total spend with hotels, the
total number of room nights. Then a table of the top 5 hotels by spend, show me
the spend, number of room nights and the average daily rate.
“The more specialized AI gets, the more capable and better it is,” he
said. While OpenAI’s Chat GPT model was “designed to do everything as well as
possible, and to be creative,” Choe advised that in business, AI models should
be constrained to be “as literal as possible”.
Prompt Stacking
Another technique that gives AI a list of step-by-step instructions to
follow, like a recipe. Each step builds on the one before it, like stacking
blocks to build a tower.
Example: Using hotel property spend data from 2204 and 2025, first
provide a year-over-summary of total spend and room nights. Then, analyze how
the average negotiated rate and average daily rate have changed over these
years. Finally, calculate the average spend per traveler for each year and
identify which year had the highest efficiency in spend per traveler relative
to room nights. Please present all findings in a clear table format and summarize
key insights.
“This is how you might instruct an intern or junior member of your team
who may not know exactly what to do,” Choe explained. “This is a good technique
to get the answers you need and reduce hallucinations.”
Role Playing Prompt Engineering
This approach involves asking the AI to act like a specific person or
character, such as a teacher, or manager or expert to response to the question
in a way that fits the role. This technique should equip the AI with a
particular perspective or expertise in order to provide a tailored answer.
Example: Your role is a spend and compliance performance analyst.
Your job is to analyze our KPIs and find ways to make savings. You can analyze
travel data and output a short report. Perform this task.
“If you are a good manager, you are a good role-playing prompt
engineer,” Choe explained. Like a job description, this technique should
outline a clear task and goal, and a clear expectation of the outcome.
“Asking the model to constrain and take this role means it can’t do
other things, so it won’t be able to write a poem or give you a recipe for
chicken, like ChatGPT can,” Choe said.
The role-playing prompt is the “bridge” to an autonomous agentic AI
configuration.
“Most of what people are calling ‘agentic’ is not really because it’s a
single thing working in isolation. Agentic AI really has to be in collaboration
because agents are programmed to be highly specialized. Alone they can’t do much
but working as a team they can execute a goal based on your strategy,” Choe
said.
According to Choe, overseeing a team
of AI agents will become an increasingly critical responsibility for travel
managers.
“The biggest application of AI moving forward is doing work that’s not
being done at all right now because we don’t have the time or the people,” he
said. “The workload is not just replacing humans—that will have the least
impact—it’s about adding resources and capabilities… you need to be a manager
of a virtual workforce. That’s the role.”
Some travel managers are already stepping
up to the plate. McKinsey & Company’s director of travel and events
technology Jamie Stewart was named BTN’s
2025 Travel Manager of the Year for introducing AI-powered, large language
model booking technology into existing workflows for the company’s travelers
and travel arrangers.
Salesforce senior travel manager for North America and JAPAC Ryan Pierce
has also introduced a Slack-based AI bot that instantly addresses queries
related to the software company’s travel program. This initiative, which he
said lays the foundation for an agentic travel program, earned him BTN’s
2025 Best Practitioner recognition.
“We want to move away from managing trips to orchestrating outcomes,”
Pierce said during the Hot Topics webinar. “In 2026, we’re focusing on
automation—shifting [prompts] from ‘can you help me?’ and ‘assist me’, to ‘do
this for me.’” The goal, he added, is to create frictionless traveler
experiences and to redefine the travel team to become a strategic function
rather than a service function.
Similarly, ServiceNow’s Allegrina expects AI data
analysis tools in 2026 to improve future predictions and strengthen her
department’s role as “the trusted advisor” for corporate travel procurement.
AMEX GBT SURVEY: AI A BIG PRIORITY FOR SMEs
A solid majority of small and midsize enterprises say adopting
AI is a key priority over the next year, according to a survey of 500 SME
business leaders in the U.S. and U.K. published by American Express Global
Business Travel.
The survey, conducted by Ipsos UK over a week in mid-October
with respondents split evenly between the U.S. and U.K. showed 78 percent of
SMEs are eager to adopt AI technology over the next year. Improving
productivity and operational efficiency were top priorities for SMEs, both
listed by about nine out of 10 respondents who rated AI as a priority.
"AI has moved from a 'nice-to-have' to a business
imperative," Amex GBT VP of SME client management Becky Power said in a
statement. "The companies leading this shift are those building and
implementing AI-operations to solve the talent gap, while doubling down on
impactful human connections and relationships that drive new business."
The survey indicated that U.S. SMEs are slightly ahead of
their U.K. counterparts in preparing for AI adoption. Thirty-six percent of
U.S. respondents said they have designated AI personnel and teams, compared
with 25 percent of U.K. respondents, according to Amex GBT.
The difference, however, could be a result of the size of
the companies queried. Respondents’ companies in the survey ranged in size from
20 to 500 employees in the U.S. and from 10 to 250 employees in the U.K.
SMEs this year also see face-to-face interaction with
clients and customers on the rise. Eighty-three percent of respondents said
such meetings were a key part of their growth strategies. Conferences, trade
shows and exhibitions topped the list of reasons for travel in the survey,
listed by 61 percent of respondents, followed by training and development (56
percent) and client relationship building (53 percent).
— By Michael B. Baker