The recent changes in trade compliance has created a need for better tools that allow enterprises to abide by international laws and regulations. Artificial intelligence has become one of the most important pieces of this puzzle. Used for broad tasks such as mapping supply chains down to classifying Harmonized System (HS) codes, AI offers an opportunity to improve how logistics service providers and enterprises approach compliance, and how governments can improve each of their enforcement measures.

Customs compliance became a specialty industry in the 1990s, when international trade companies began hiring teams to preserve their import and export privileges, and ensure smooth, lawful exchanges of goods across borders. Groups of Customs brokers and specialized staff were hired to address discrete compliance activities necessary to exercise reasonable care, including HS code classification and adherence to certain global treaties, among others. However, onboarding these disparate groups created silos within organizations that, even 30 years later, they are still struggling to integrate.

To add to the complexity, compliance was – and continues to be – managed through manual processes, resulting in resource-intensive and error-prone operations. Many companies still use questionnaires to understand with whom they are doing business, spreadsheets to manage data, and elaborate workflows to comply with a broad spectrum of trade regulations.

These are insufficient tools being used to solve complex problems. A value chain encompasses the entire lifecycle of a product, from the raw materials to the assembly, to the sales and shipping – and it includes aspects of finance, logistics, marketing and legal. Compliance professionals are tasked with identifying all risks lurking upstream and downstream in their global value chains. They must detect counterfeit goods, distill the consequences of geopolitical fallout, monitor human rights violations, and develop protocols for supply chain security, cross-border e-commerce, and sustainability. Even if an organization has all the data to make these calculations, they usually lack the tools to analyze it, and so remain in the dark about their risk and levels of compliance.

The proliferation of new global trade regulations such as the Uyghur Forced Labor Prevention Act, “The Green Deal”, and the EU Deforestation Regulation, not to mention evolving security protocols, technological advancements, and rising standards for environmental and ethical practices have all compounded the challenge.

Yet this is an opportunity. Artificial intelligence possesses the ability to share insights from huge sets of data. processing billions of messy commercial and logistics data points, cultivating a unified, dynamic, and clean view of the global supply chain network. The trade community can finally understand and manage the connections between risk and the measures of compliance in one, centralized work space. AI had been deployed for rudimentary oversights but is now ready to become the engine of full compliance.

At its simplest level, trade compliance professionals must understand – and trust – what the shipments are telling them: an ability to see inside every level of the value-chain, marry the data with the movement of each product, and map the journeys to every intended market. The old playbook provides some guidance, but it lacks the specialized navigation and collaboration necessary for enterprises and governments in the modern compliance environment.

We are now able to build artificial intelligence models that can generate actionable insights out of this problem.

AI learns by being “trained” on vast quantities of data. Repeatedly seeing the association between two points teaches the system they are related, and after enough additional context, how. This gives AI the incredible capacity for analysis and insights we see today, allowing the AI to not only produce answers but provide degrees of confidence in its accuracy and trustworthiness.

In the context of trade compliance, AI systems learn by assimilating supply-chain data set. This requires collecting data on million of companies, connected by billion shipments, across million distinct supply chain linkages. Each of those connections creates an interdependency that no department of humans, much less one single human, could begin to compute. Yet not only can AI break down each product and condition within the global value to actionable insights, but using smart design techniques it can present the information to compliance officials in a clean, easy-to-use interface.

AI has the ability to reveal what really matters about a shipment: which parties are involved, which products are contained, and whether the interaction is safe, compliant, and trustworthy. This “voice” gives customs authorities and the trading community a more resilient global system of commerce.

AI will alter an organization’s fabric, too. Teams will be able to offload and integrate many of their workflows, changing how they spend time. For example, businesses can now utilize supply chains analysis tools to screen their suppliers to ensure compliance with the Customs-Trade Partnership Against Terrorism program, rather than relying on records and staff research. AI might even change the questions a compliance team takes on at all. At the same time, a well-built map of an organization’s global supply chain should be easy to navigate. In many cases those firms integrating AI will see their hiring pool broaden, as the need for candidates with specific data or analytic skills decreases. In fact, the changes AI brings to an organization may run so deep that an organization finds its mission cohering around different questions altogether.

This also means the day-to-day mechanics of the trade compliance official will change too. They will need to be versed in collaboration tools that rely on AI and able to read new kinds of interfaces that distill myriad data sources. They will also need to expand the formats and requirements of compliance documentation, both integrating these new views on the global value chain, while also pushing organizations to go further in understanding their own products and shipments.

AI provides a way to identify products and/or transactions likely to be non-compliant before they cross the border. Governments and trade authorities can deploy AI to bolster their own security measures, such as better predicting the risk in goods and services passing through their ports, or by using AI’s analytics powers to view trade in new, more actionable ways.

Creating competent and insightful AI tools requires talent and financial resources. Using AI to understand value chains is much more complex than training a chatbot. Should a government or organization want to build their own they will need to hire engineers with a background in both the frameworks of AI and the contingencies of global value chains. The intricacies of trade must be woven directly into the code. However, specialized tools now make it possible to see a particular supply chain situated in a map of the world’s supply chains, and as the supply chain network evolves in the real world, so does the view of value chains.

AI also requires enormous amounts of computing power. Cloud computing providers, in fact, have had to scramble to accommodate all the new demands on their data centers with the recent rise of AI applications. As such, to run AI at this scale requires understanding how to manage armies of servers equipped to handle these enormous loads.

That’s why global value chain technologies are increasingly being adopted by governments and private businesses alike – to utilize the best that AI can provide without requiring investment in the technology infrastructure in-house. However, that doesn’t mean that the technology can operate in a silo – nor that every solution applies to your niche in the market. Today’s most innovative organizations are choosing the right platform for their purposes by evaluating a potential AI tool’s data sources, industry application, security, and integrity. And they are then integrating their chosen solution into the organization’s decision-making processes, and training dedicated individuals on how to best utilize the insights gleaned.

Embracing technology like AI creates a promising path toward modernizing customs compliance. It reimagines compliance programs for the modern commercial environment and provides a more complete map of cross-border shipments. Enterprises will finally be able to fully leverage their shipment data and understand each party in a transaction to their nth-tier supplier. Safety measures will become clearer and actionable and the opportunity to use the exceptional computing power behind AI to automate processes will only continue to expand.

Above all, as the trade compliance industry starts to take advantage of an AI-driven world, it will grow more efficient, transparent, and adaptable, and continue to live up to the reason it was created in the first place: to power the future of global trade.

More information
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