The New Gatekeepers: Nation Branding in the Age of AI Bias

Nation branding studies suggest that, like consumer products, nations elicit certain cognitive associations. Just as the “Apple” brand evokes the associations of innovation and sleek design, the “France” brand elicits deep seated associations with culture, romance, and artistic movements. Much like consumer products, nations may also elicit negative associations. France may just as easily elicit the associations of colonial legacies, social unrest, and arrogance. In this context, nation branding may be viewed as a form of “strategic association management” or a deliberate attempt by states to amplify positive associations while weakening negative ones.

Traditionally, states have pursued “strategic association management “through dedicated branding campaigns replete with logos and taglines, such as “Malaysia, Truly Asia,” “Incredible India,” or “Essential Costa Rica.” For states, nation branding campaigns are not an exercise in vanity but, rather, a strategic tool for competing successfully in a global marketplace. Through nation branding, states hope to dedifferentiate themselves from one another and to cultivate a positive image that can help attract investments, tourists and skilled or talented laborers.

While scholars have long noted that diasporas and media narratives can contest a nation’s brand, few have explored how AI biases now complicate this practice. This shift is driven by three distinct biases inherent to the AI era.

The Automation Bias

The “Automation Bias” leads users to assume that the information they access via AI is accurate. Indeed, studies have found that individuals tend to trust AI output given the assumption that AI systems are incredibly sophisticated, incredibly complex and thus incredibly reliable. The “Automation Bias” is magnified through media hypes that often depict AI tools such as ChatGPT and Claude as being so accurate that they can be used to diagnose patients, author legislation and optimize state services.  

As individuals increasingly turn to AI to learn about the world, these tools become powerful narrators of state attributes. When an AI labels a nation as “racist” or “declining,” the Automation Bias cements this association in the user’s mind more firmly than a traditional news report might. For example, when prompted about the negative attributes of France, ChatGPT frequently cites strikes, colonial legacy, and cultural elitism. These responses resonate with existing stereotypes of France, but because they come from an AI, they may become cemented in the minds of users and more difficult to counter in branding campaigns.

The Algorithmic Bias

While Automation Bias concerns how we perceive AI outputs, “Algorithmic Bias” concerns how that output is built. AI systems consume vast amounts of data, but if that core data is skewed or biased, the responses will also be biased. A recent study revealed a troubling geographic bias as nations from the Global North are often depicted by AIs as beacons of democracy and affluence, while the AI glosses over challenges such as crime, pollution, corruption or political polarization.

In contrast, Global South nations are frequently reduced to “scenic but unstable” states as they are consistently depicted by AIs as crowded, corrupt, dirty or inept. The study found a systematic bias in which Global North countries were labeled as attractive places for tourism and investments as opposed to the corrupt and dangerous Global South. This “Algorithmic Bias” means that Global South nations have an uphill battle when it comes to strategic association management as they are more likely to be negatively judged by AIs, while these negative judgments may linger in users’ minds because of the “Automation Bias”.

The Template Bias: America as the “Standard”

The aforementioned “Algorithmic Bias” is further complicated by the fact that many leading AI applications use American norms as a universal template. This is because many AI applications are created in the US.  States that adhere to different social, legal, or cultural values are often negatively judged by Ais against this “Standard.” This suggests that nation branding is becoming a matter of digital sovereignty. If a nation’s global image is now dictated by AI models trained on US Silicon Valley data, that nation loses the agency to define its own identity and to manage its own image.

A New Era of Strategic Management

Coupled together, the “Algorithmic Bias” and “Automation Bias” suggest that nation branding has entered a new era. State images are not only shaped by branding campaigns and stakeholder engagement but by AI systems which can shape the associations that states elicit. Increasingly, states will need to evaluate how they are depicted by AIs and then plan campaigns that either strengthen positive AI depictions or counter negative ones. This will prove a difficult task given the amount of AI tools now available online and potential differences across these AI tools.