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Don’t let automation undermine what makes advertising effective: the human element.
There can be no doubt that in the rapidly and constantly evolving landscape of digital marketing, artificial intelligence is dominating the conversation. Vendors are rushing to deploy AI-based solutions for campaign optimization, machine learning, consumer targeting based on behavioral data, data analysis, etc. In my experience as a media director, this is reminiscent of the early days of the programmatic revolution, when digital media turned into the Wild West and dozens of vendors overwhelmed marketers with promises of never-seen before efficiencies and benefits.
AI tools have evolved beyond expectation, and they offer remarkable capabilities to help build and implement marketing campaigns. But overreliance on these technologies can lead marketers down a path that prioritizes whatever the algorithms decide is best versus a genuine and effective human connection.
AI, at its core, is a fast and efficient series of algorithms to connect and analyze data from many sources and find complex patterns which it can then condense into what feels like human analysis. When used properly, it can identify trends from overlooked small factors, segment audiences with remarkable granularity, and help optimize campaigns in real time. However, the data-driven approach carries limitations that, despite its seemingly precise response, can ultimately diminish the main purpose of advertising: creating a meaningful connection with consumers.
“As marketing AIs optimize for engagement based on past performance, we run the risk of excluding large portions of the population from our messaging and reach.”
Diego Lastra
We must remember the basic principle of Garbage In, Garbage Out (GIGO). The AI is only as good as its data. AIs are powered by language learning models (LLMs), the majority of which train on publicly available online data—and probably 70 percent of that is written in English. Of this digital content, large amounts are generated by a small but extremely active percentage of online users while most consumers do not generate as much data.
This presents a dangerous potential for algorithmic bias. The AI can reflect the limitations and tendencies of the data it was fed. It takes time and massive amounts of data to train a model. Most models will assign higher probability values to data that reflect common patterns—but they may not be accurate.
Grok, X’s AI model, was trained on X comments and replies, many of which are bot-generated, agenda-driven, or misleading. The results provided by these models can inadvertently perpetuate stereotypes, exclude less represented communities, enforce specific biases, or propagate false information. As marketing AIs optimize for engagement based on past performance, we run the risk of excluding large portions of the population from our messaging and reach.
The use of AI tools for creative testing and optimization can lead to a homogenization of messaging based on metrics such as click-through rates (problematic in an environment where bot fraud is rampant—I can imagine a world in which AI generates campaigns driven by bot actions in a vicious circle). It can also reduce the effectiveness of ads by sacrificing creativity and emotional connection in favor of formulaic content that drives short-term engagement and on paper shows statistical improvements but is ultimately forgettable and ineffective at driving brand connection.
I’m a firm believer that in a diverse world, the most effective ads feature authentic storytelling that resonates with human audiences. This requires a level of nuance, empathy, and contextual understanding that AIs still lack. An AI might recognize that a certain demographic responds well to specific visual cues or messaging styles, but it lacks the emotional intelligence to understand the motivations of our intended audiences or cultural context.
Authentic advertising requires an understanding of human emotions, aspirations, social dynamics, and differences to craft a compelling narrative. Would you trust an AI to understand the cultural nuances and differences between Latin American cultures, or between African Americans in the Deep South versus Los Angeles?
Another thing to keep in mind when considering AI for campaign development is its potential to create echo chambers. By continuously optimizing for engagement and conversion based on existing user behaviors, these systems can trap consumers in narrow, predictable information corridors. This not only limits consumer exposure to diverse perspectives but also reinforces existing biases and potentially manipulative marketing techniques.
The danger is a progressive narrowing of individual worldviews, as exemplified by social media algorithms. Fine if you’re Facebook and want to drive user engagement by outrage, but detrimental to advertisers and brands aiming to grow their share of voice and market.
“Relying too much on automation carries the risk of losing the innovative thinking that drives breakthrough marketing strategies.”
Diego Lastra
We also need to consider the economic implications. As companies increasingly rely on AI tools to develop their marketing strategies, there’s risk of diminishing the strategic and creative insights of experienced professionals who understand the delicate interplay between data-driven insights and creative intuitions. Relying too much on automation carries the risk of losing the innovative thinking that drives breakthrough marketing strategies.
I am not suggesting at all that AI has no place in advertising. Rather, the most promising approach lies in using AI as a collaborative tool rather than as a replacement for human creativity and experience.
Use machine learning to identify emerging trends, do deep analysis on data, optimize campaign delivery, and leverage its capabilities to complement. It should not supersede human strategic thinking, creativity, emotional depth, and capacity for nuanced analysis and experience-driven intuition.
Organizations must also implement robust ethical frameworks to govern AI’s role in advertising. This involves regular audits of algorithmic systems to detect and mitigate potential biases, maintaining transparency about how AI influences marketing strategies, and ensuring that human oversight remains central to the decision-making process.
As we move forward, the most sophisticated advertising will emerge not from complete automation, but from a harmonious collaboration between human creativity and artificial intelligence. By recognizing AI’s strengths while remaining vigilant about its limitations, marketers can develop more authentic, ethical, and genuinely engaging advertising experiences that respect both consumer intelligence and human complexity.
The future of advertising lies in leveraging technology as a tool to amplify human creativity, empathy, and strategic thinking.
Born in Mexico City to a creative director and a psychologist, Diego Lastra has been working in advertising since 2004, focusing mostly on multicultural and tribe-based marketing. Diego has always been fascinated by the power of media to persuade and shape culture, and the evolution of digital media as it becomes an extremely entrenched part of our personal and social lives. He is currently the associate media director at Dieste.
