The Reliability Risks of AIJay Lee’s U.S. Market Report (177)

Unverified AI-generated information can lead to costly mistakes, particularly in food exports

Overreliance on AI for FDA and regulatory research may contribute to import delays and compliance problems

AI should be treated as a research assistant—not the final decision-maker

Jay Lee, President, J&B Food Consulting

It has only been a few years since ChatGPT entered the mainstream, yet artificial intelligence has already become deeply integrated into the way many of us work.

AI is also highly useful in consulting. It can assist with organizing information, preparing reports, conducting preliminary research, and handling a wide range of routine tasks. Many of our clients are also incorporating AI into their daily operations.

However, we occasionally encounter companies that have faced unexpected problems because they relied on AI-generated information without properly verifying it.

A recent episode of the Korean investigative television program PD Notebook highlighted cases involving individuals who reportedly relied heavily on AI when starting businesses, only to experience serious setbacks. These examples illustrate a broader concern: the risks associated with inappropriate or excessive reliance on AI are no longer merely theoretical.

AI Risk in Food Exports

The same issue can arise in the food export industry.

The consequences can be particularly serious in areas involving food, dietary supplements, pharmaceuticals, regulatory compliance, and U.S. market research, where inaccurate information can create legal, regulatory, financial, and even public-health risks.

At the center of the problem is one of AI’s best-known limitations: hallucination.

An AI system may occasionally generate information that sounds authoritative and convincing even when the underlying facts, citations, regulations, statistics, or conclusions are inaccurate or nonexistent.

Another concern is what might be described as error amplification.

When an initial assumption or piece of information is incorrect, subsequent analysis may continue building upon that error. The result can be a detailed and seemingly logical answer whose foundation is fundamentally flawed.

The Hidden Risk of AI-Based Market Research

Many exporters are beginning to use AI for U.S. market research and consumer trend analysis as a way to reduce costs and accelerate decision-making.

Used appropriately, AI can be extremely helpful for these purposes. But relying on it without independent verification creates significant risk.

If the initial prompt contains an incorrect assumption, or if the underlying information is incomplete, outdated, or inaccurate, an AI-generated analysis may continue in the wrong direction while still presenting its conclusions with considerable confidence.

It may even provide statistics, references, or supporting explanations that appear credible but cannot be verified.

If a company uses such information to make major decisions about product positioning, consumer targeting, pricing, packaging, or marketing strategy, the consequences can be expensive.

This is why AI-generated market intelligence should generally be treated as a starting point for research rather than verified market evidence.

Regulatory Research Requires an Even Higher Level of Caution

The risks become even greater when companies rely on AI to interpret requirements of the U.S. Food and Drug Administration (FDA) or other U.S. regulatory agencies.

Food regulations are complex. Requirements can vary according to the product category, ingredients, manufacturing process, intended use, labeling claims, country of origin, and applicable federal or state regulations.

There have been situations in which companies relied heavily on AI-generated regulatory guidance and later encountered problems during the U.S. import process.

AI may cite an outdated requirement, misinterpret a regulation, overlook an applicable restriction, or—in some cases—generate a legal citation or regulatory requirement that does not actually exist.

An answer can therefore look highly professional while still being wrong.

For an exporter, the consequences may include shipment delays, detention, relabeling, additional documentation requests, product reformulation, or other regulatory complications.

AI Cannot Replace Regulatory Verification

There is an important lesson for companies adopting AI:

If an organization does not have the expertise to independently verify an AI-generated answer, relying on that answer without professional review can create more risk than value.

Whether the subject is U.S. market data, FDA requirements, ingredient compliance, labeling, or import procedures, AI-generated research should be verified against reliable primary sources and, where appropriate, reviewed by an experienced U.S. market or regulatory professional.

For FDA-related matters, this means going back to the actual regulatory framework—including applicable statutes, regulations, FDA guidance documents, databases, and other authoritative sources—rather than relying solely on an AI-generated summary.

AI Is an Assistant, Not the Final Decision-Maker

AI remains an extraordinarily powerful tool.

It can organize enormous amounts of information, summarize complex materials, identify potential issues, accelerate preliminary research, and help professionals work more efficiently.

But its greatest value comes when it is used within a system that includes human verification and professional accountability.

AI can prepare the first draft.

AI can organize the evidence.

AI can suggest where to look.

But the final regulatory or business decision should still be made by a qualified person who understands the underlying facts and accepts responsibility for the conclusion.

Paradoxically, as artificial intelligence becomes more sophisticated, careful human verification and professional judgment may become even more valuable.

In the age of AI, the companies that benefit most from the technology may not be those that trust it the most, but those that know when to use it, how to verify it, and where human expertise must take over.