Scott Gillespie says AI is making a meal out of business fundamentals - including trust and travel.
Seems everyone is talking about AI-powered travel tools.
Meanwhile, AI is shaping forces well beyond our industry, with far greater implications
for when and why we travel.
AI Is Eating the White-Collar Workforce
The U.S. white-collar workforce is forecast to shrink due to
demographic trends and immigration policies. AI adoption is accelerating this
decline. Witness the recent layoffs at Amazon, Intel, Microsoft, Nestlé, UPS
and Verizon, each affecting more than 10,000 workers, many if not most of them
white-collar.
Last year, Ford's CEO said, "Artificial intelligence is
going to replace literally half of all white-collar workers in the U.S."
Let that sink in.
AI is Eating Meetings
Fewer white-collar workers mean fewer meetings. Many of the
remaining office workers are using AI to plan, coordinate, research, analyze,
prioritize and decide.
What used to take a few meetings can now be done in one or
none, with the right agentic workflows.
AI Is Eating Low-Value Business Travel
Fewer white-collar workers mean fewer business travelers.
Fewer low-value meetings mean fewer low-value business trips. My research found
that in 2023, 25 percent to 30 percent of business trips were low-value.
Unsurprisingly, corporate travel agencies saw a 3.6 percent
decline in passenger trips in 2025, according to ARC data, while US GDP grew by
2.9% in the first three quarters of 2025, adjusted for inflation.
Did AI’s recent incursion into the workforce cause this 'more
GDP with fewer trips' datapoint? Not all of it, but not none of it, either. And
AI is just getting started.
Short-sighted CFOs will use their headcount reductions to
cut the travel budget and call it an attrition dividend from their AI
investment. Long-sighted CFOs will see a bigger problem looming.
AI Is Eating Trust
Not because LLMs hallucinate. They do, and that erodes trust
in their output. But that's a known problem, solved with guardrails and
vigilance.
The bigger problem is AI's invisible decay of trust within
the enterprise and between enterprises, customers and suppliers.
Think of any organization as a network of
lights—people—connected by wires of trust. Some lights burn brighter than
others. Lights grow or dim over time based on the trust capital they've earned
or lost with their connections.
We want brighter networks of trusted people within and
between enterprises, right?
If you buy the assertions above, you see the trust problem:
More people leaving the network means more lights go out.
More reliance on AI-generated black box outputs means less
transparency, less understanding, and less trust across the network.
Fewer in-person meetings mean fewer opportunities to
establish relationships, gain insights, resolve disagreements and build trust.
When trust erodes, the lights grow dimmer.
This isn't about distrusting AI. It's all about fearing the
loss of a very precious resource—one that AI cannot replenish.
AI Can't Do “Trust” with a Capital "T"
A highly cited academic paper (Mayer et al., 1995) defines
trust as the combination of ability, integrity and benevolence, modified by
perceived vulnerability. The key factor is benevolence—freely choosing to
advance or protect another person's interests.
When your boss shares highly sensitive information with you
or sticks her neck out for you, that's showing trust with a capital T.
LLMs have far greater capabilities than humans in many
respects. They can produce outputs with integrity by faithfully conforming to
the user's expectations.
To a large extent, we can trust LLMs to do what's expected.
Sure, they can be designed to appear caring, but artificially evoked care is,
by definition, not benevolence.
We can't and don't count on LLMs to freely choose to advance
or protect our interests. That would be earning trust with a capital T, and AI
can't do it. So we must look to people as the only way to build high-value
trust.
AI Will Increase the Need for Apprenticeships
A senior partner at a major law firm told me that LLMs can
handle much of the work currently done by first-year attorneys.
"But," he said, "if we don't hire first-years, where will our
partners come from?"
Exactly. AI is designed and deployed to reduce headcount.
Many AI apps are currently aimed at junior roles across the enterprise. So how
do we develop people's skills in an AI-driven world and keep the lights burning
bright in our trust networks?
The answer is intentionally crafting AI-adjacent
apprenticeships. Get those responsible for applying AI's outputs to teach the
young'uns what to look for, how to judge, and whom to trust.
Long-sighted CFOs will see the value of reinvesting some of
the AI attrition dividend back into the workforce. It's the only long-term way
to keep the lights on.
AI Will Increase Demand for High-Value Business Trips
Executives must get ahead of this impending AI-driven
trust-decay curve. It will require a new discipline—intentional trust
management. Sensing changes in the trust network. Adding new apprentice-type
bulbs. Replacing burned-out bulbs. Rewiring critical links. Amping up the power
of trust across the grid.
Business travel will play a critical role because its core
value is enabling trust.
It's not the only way, and it doesn't guarantee success. But
business travel justifies the cost when the stakes are high enough, which
pretty much defines the high-value business trip.
Long-sighted executives will use business travel
judiciously, reserving most of their travel budgets for high-value trust-building
efforts.
Short-sighted executives will see the problem when their
trust lights dim and go dark. By then, the best talent will have left, critical
partnerships will have fractured, and the travel budget they saved will look
like a rounding error compared to the value they lost.
The question isn't whether this happens. It's whether it
happens to your company.
________________________________________________________________________
About the Author: Scott Gillespie is CEO of tClara, providing strategic
advisory services to the business travel industry.