---
title: Are you ready to have the AI boardroom conversation?
description: Customs compliance validation is the systematic check of declaration data, classification, and valuation before filing.
image: https://www.customaite.ai/hubfs/pexels-mikhail-nilov-7988207.jpg
---
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# Are you ready to have the AI boardroom conversation?
[](https://www.customaite.ai/blog/author/wim-van-emelen)
by [Wim Van Emelen](https://www.customaite.ai/blog/author/wim-van-emelen)
4 min read
Oct 26, 2026
Open your mailbox, LinkedIn or any newspaper and AI is everywhere. So are the headlines about layoffs driven by AI efficiency gains.
For a long time, I believed most of this was a corporate excuse. Cutting headcount is never popular, and AI makes a convenient scapegoat.
Lately, I have started to see it differently. Not because I now believe AI is wiping out jobs, but because I have seen what happens when it doesn't.
**The biggest risk of AI is not that it costs jobs. It is that it delivers nothing at all, while your competitor reaps the benefits.**
### **The gains are real**
At Customaite, we automate customs declarations. Our analytics show what happens on the floor once teams adopt a new way of working.
Traditionally, an experienced customs declarant handles somewhere between 15 and 20 declarations a day. We see plenty of declarants using Customaite handle 50 in less than half a day. That is a five- to sixfold increase in productivity.
For any organisation, that should be an enormous success.
And yet, not one of our customers has let people go at scale. They stop replacing people who leave, but that is a marginal effect. Most of them count on something else: winning market share without adding headcount.
That is a sound ambition. But with today's geopolitical tensions and markets under pressure, volumes are more likely to shrink than to grow. The capacity you freed up will not be absorbed by growth on its own.
### **A sawmill in fast-forward**
Picture a sawmill in the early 20th century. Workers saw planks by hand in teams, and each team has a daily quota of planks.
Overnight, they get electric power tools. The tools are many times faster and produce better planks. But the pile of wood hasn't changed. By mid-morning, the work is done.
In the first days and weeks, there is plenty to do: maintenance, cleaning, all the tasks that had been postponed for years. Then that work is done too.
What do you expect will happen next?
### **Back to the hand saw**
In the customs world, we have seen it happen. Teams put their power tools aside and pick up the hand saw again, just to stay busy.
It is tempting to call that resistance to change. It isn't. It is self-protection. If you are done by eleven and there is nothing left to do, you start wondering how long your job will last. Going back to the old way of working is the most rational response there is.
That makes it a management problem, not an adoption problem. The technology works. The value evaporates anyway.
### **Meanwhile, next door**
Your competitor bought the same power tools. The difference is that they decided upfront what to do with the time. Now they deliver better planks, in a fraction of the time, at a fraction of the price.
By the time that shows up in your numbers (lost tenders, pressure on your rates, customers moving on), it is too late to change course.
### **The boardroom conversation**
If you take AI seriously, you have a plan for the freed-up capacity before you roll it out. That means making choices, and some of them are hard. At a minimum, a management team should be able to answer four questions.
1. **Where does the capacity go?**
Growth, new services such as origin, tariff and compliance advice, bringing outsourced or interim work back in-house, or a smaller team. Each option is valid. Not choosing is not.
2. **What do we measure?**
Occupancy and hours worked stop meaning anything. Declarations per FTE, cost per declaration and first-time-right rate tell you whether the value is actually landing.
3. **What happens to our pricing?**
If your competitor passes their cost advantage on to the customer, your price per declaration comes under pressure, whether you adopt AI or not.
4. **What do we tell our people, and when?**
Uncertainty sends people back to the hand saw. A clear and honest story, including what you expect from them next and where there will no longer be a role, is what keeps the power tools running.
The impact of AI on the shop floor is enormous. The impact on management teams is just as big, and far more often underestimated. They too have to work, measure and decide differently.
### **Look around the room**
Take a moment and look at the furniture in the room you are sitting in. None of it was made with hand saws. And yet, good carpenters haven't disappeared. They are scarce, and they are worth more than ever. But most of the people who sawed planks by hand in 1920 did not become furniture makers. The power tools did not make that switch for them, and neither did time.
Customs is heading the same way. The sector already struggles to find experienced declarants, and that scarcity will only grow. But capacity freed up on the floor does not turn into expertise by itself. Advising on origin, tariffs and compliance is a different job, and not everyone who is good at today's job will grow into it. Assuming they will is the most comfortable choice a management team can make. It is also the most expensive one, because it is not a choice at all.
Not ready for that conversation? Then don't invest in AI. It will cost you twice: once for the technology, and once for the market share you lose to those who were ready.
## Frequently asked questions
How much does AI increase a customs declarant’s productivity?
An experienced [customs declarant](https://www.customaite.ai/glossary#customs-declarant) traditionally handles 15 to 20 declarations a day. With [customs declaration automation](https://www.customaite.ai/glossary#customs-declaration-automation), many Customaite users handle 50 in less than half a day. That’s a five- to sixfold increase in productivity.
Does AI in customs lead to layoffs?
Not at scale. Most companies stop replacing leavers and aim to grow without adding headcount.
Why do teams fall back on old ways of working after adopting AI?
If the work is done by eleven, people worry about their jobs and slow down to stay busy. It’s a management problem, not an adoption problem.
What should management decide before rolling out AI?
Where the freed-up capacity goes: growth, advice on [rules of origin](https://www.customaite.ai/glossary#rules-of-origin), [tariff classification](https://www.customaite.ai/glossary#tariff-classification) and [customs compliance](https://www.customaite.ai/glossary#customs-compliance), insourcing, or a smaller team. Management also needs to decide what to measure, what happens to pricing, and what to tell staff.
Which KPIs show whether AI is paying off?
Declarations per FTE, cost per declaration and first-time-right rate, which depends on [customs data quality](https://www.customaite.ai/glossary#customs-data-quality). Occupancy and hours worked stop meaning anything.
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Previous story
[← AI Myths in Customs Compliance - debunked.](https://www.customaite.ai/blog/ai-myths-in-customs-compliance-debunked)
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