As Artificial Intelligence (AI) becomes increasingly embedded in Customs operations, it is reshaping the way Customs professionals work, improving efficiency, compliance and decision-making. However, as organizations introduce AI-driven solutions, they face a critical challenge: users often hold AI to impossibly high standards while being more forgiving of human colleagues. This paradox affects adoption and trust, yet understanding and addressing it can unlock the full potential of AI as an empowering tool rather than a source of frustration.

In many industries, people expect AI to be infallible. If an AI system makes an error, users may quickly lose trust in the system. Yet, when a human colleague makes a similar mistake, there is room for understanding and correction. This double standard is well documented. Research in different sectors has shown that, while AI-assisted work improves accuracy, users become less receptive to AI-generated recommendations once they realize they come from an AI algorithm.

A striking example of this double standard can be found in self-driving cars. Human drivers are responsible for thousands of road fatalities every year, yet we accept these risks as an inherent part of human fallibility. On the other hand, a single accident involving a self-driving car can lead to widespread public backlash and calls to ban the technology altogether.

This mindset is something our product and customer success teams at Customaite experience firsthand. Over the past few years, we have implemented AI solutions to automate the declaration processes in Customs teams across various organizations. Time and time again, we see that, if even the smallest detail is overlooked by the AI system or a limited piece of information is missing, this can be enough for people to reject the AI solution entirely, even though the benefits are undeniably significant.

However, there is no reason for concern, as with the right approach – one that focuses on transparency, user involvement, and continuous improvement – these challenges can be effectively addressed, ensuring that the significant benefits of AI can still be realized.

While AI adoption comes with challenges, it is important to recognize the significant benefits it brings. The benefits of AI in Customs operations are undeniable. AI-driven solutions not only improve efficiency and compliance, they also significantly enhance the daily work of Customs professionals, allowing them to focus on higher-value tasks rather than being bogged down by repetitive, manual processes like copying information from documents.

AI-powered solutions provide significant advantages to Customs operations by enhancing efficiency and compliance. Such solutions can process vast amounts of data far more quickly than humans can. This speeds up declaration processes, reduces manual workload and the risk for errors, and minimizes bottlenecks. Furthermore, by automatically checking declarations against complex and evolving regulations, AI helps ensure compliance, which reduces the risk of costly penalties and fines.

If done in the right way, supporting declarants in their work is at the core of AI-driven solutions. Far from replacing professionals, AI augments their capabilities by automating repetitive tasks, allowing declarants to focus on higher-value activities such as complex classification decisions, optimizing duty savings strategies and ensuring accurate valuation and origin determination. Furthermore, by reducing mundane workload, AI enhances job satisfaction and reduces stress.

Declarants often spend significant time copying information, cross-referencing documentation, checking tariff codes, and validating declarations. The job requires careful attention to detail, and mistakes can have significant financial and legal consequences. Supporting declarants with AI allows them to work more efficiently, while minimizing fatigue and overall cognitive load. This leaves more room to spend time on making more informed decisions for the most critical or complex cases.

One of the major obstacles to AI adoption is the initial trust deficit that often accompanies its introduction. Users may perceive AI as a tool designed to control or replace them, which can lead to resistance. However, when AI is positioned as a supportive assistant rather than an overseer, trust is more likely to develop.

A collaborative approach is particularly effective in overcoming this trust gap. In this approach, AI does not fully automate decisions but, instead, provides recommendations that users can review, refine, and approve. By ensuring that human expertise remains central to the process, users are more likely to see AI as a reliable companion rather than a threat.

Another important factor in building trust is transparency. When people understand how and why a system makes decisions, they are more likely to accept and rely on it. In contrast, when AI operates as a “black box”, where decisions are made without clear explanations, users tend to be sceptical or reject its conclusions outright.

A good comparison to fully understand the importance of transparency can again be found in cars and, more precisely, the use of a GPS system. Imagine you are driving and suddenly your GPS tells you to take a completely different route than usual. It doesn’t explain why, no traffic warnings, no construction alerts, just a new path. You hesitate. Do you follow it blindly, or do you ignore it and stick to what you know? Most people would distrust the GPS and take their familiar route instead. Now, imagine the same scenario but, this time, the GPS provides context: “Heavy congestion ahead, estimated delay of 25 minutes. Taking an alternative route to save time.” Suddenly, the decision makes sense, and you’re much more likely to trust and follow the new path.

The same principle applies to AI in Customs operations. If an AI-driven system suggests a new tariff classification or flags a discrepancy but doesn’t explain why, declarants are likely to reject it. However, if the system provides reasoning – such as highlighting key attributes of a product that influenced the classification – users are far more likely to trust and integrate the AI-driven process into their workflow. Transparency is the difference between a system that feels like a helpful guide and one that feels like an unpredictable, untrustworthy black box.

While collaborative models and transparency are crucial, they are not sufficient on their own. Successful AI adoption requires a well-defined strategy that addresses both technical and organizational factors. Organizations must plan for success by implementing a continuous improvement cycle, which includes:

• Defining Impact Goals – Clearly outline the desired outcomes for AI adoption. This involves setting realistic expectations around return on investment (ROI) and determining how success will be measured.
• Execution and Rollout – Deploy AI solutions with a focus on phased implementation, ensuring that users receive adequate training and support during the transition.
• Measuring Impact – Regularly evaluate the effectiveness of AI solutions using predefined metrics. This helps identify areas where adjustments are needed to improve performance and user satisfaction.
• Adapting and Learning – Continuously refine AI systems based on feedback and performance data. This iterative approach ensures that both technical and user experience improvements are incorporated over time.

Throughout this entire process, special attention must be given to change management. Management buy-in, user involvement, and clear communication are critical to fostering a culture of trust and acceptance around AI technologies.

AI is transforming businesses around the world in all sectors. Customs operations are no exception to this. Its success, however, depends on more than just technological capabilities. It requires a comprehensive strategy that combines collaborative approaches, transparency, and continuous improvement cycles. Organizations must plan for success by setting clear impact goals, engaging stakeholders, and committing to ongoing learning and adaptation.

By embracing this approach, we can move beyond the instinct to put the blame on AI when expectations are not met and, instead, recognize its role as a valuable ally. Declarants stand to benefit not only from increased efficiency and compliance, but also from a work environment where AI enhances their expertise rather than replacing it. The future of Customs lies not in choosing between human expertise and AI, but in harnessing the strengths of both to build smarter, more resilient Customs processes.

More information
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