When it comes to artificial intelligence in marketing, it is easy to fall into the temptation of seeing only one path of innovations and results. And yes, it is undeniable that AI has profoundly changed the way brands communicate, position themselves, and, especially, relate to their consumers. According to Salesforce (2023), 84% of marketers already use some form of AI in their strategies — a number that highlights how present this technology already is in the sector.
But every technological revolution carries its dilemmas — and with AI, it is no different. On one hand, we have an impressive arsenal of possibilities: large-scale personalization, real-time optimized campaigns, precise predictions of behavior. Just think of the chatbots that never sleep, the systems that ‘feel’ the mood of social networks, or the platforms that generate content in seconds. Everything fast, efficient, and seemingly under control. But is it really? The promise to deliver the right message, at the right moment, and to the ideal person sounds almost utopian — until we remember that, for this, there is an enormous volume of data being collected, processed, and interpreted. The boundary between personalization and invasion of privacy has never been so thin. When we let the machine decide what the consumer wants, are we really offering value or just guiding choices that serve the interests of brands better?
This question resonates strongly at a time when marketing becomes increasingly data-driven. And here is the point: data is cold, but decisions should not be. AI can indeed improve the making of strategic decisions. McKinsey points out, for example, that companies adopting AI in marketing increase their profits up to 20% faster than competitors who do not adopt it. However, we cannot ignore the risk of replacing the human perspective — sensitive, intuitive, empathic — with purely algorithmic logic.
Brand communication is not just about efficiency; it is also about connection, emotion, and authenticity. There is yet another critical layer in this debate: the inequality of access to technology. Large brands, with substantial budgets and dedicated teams, are riding the AI wave more easily. And the small ones? Will they be able to compete in this new scenario, where those with the best AI also have the best opportunities? Marketing may be becoming an increasingly asymmetric game — and that should concern us.
And we cannot ignore the risks of bias. Algorithms learn from historical data, and historical data carries prejudices. We have seen cases where recommendation systems or automated campaigns have reinforced stereotypes or excluded certain audience profiles. AI is only as fair as the data that feeds it — and these data do not always reflect the diversity and complexity of society. The future scenario points to even more immersive experiences, with augmented reality, increasingly natural conversational interfaces, and predictive marketing that anticipates desires before they are even expressed. And to meet these expectations, personalization becomes a key piece. Adobe estimates that more than 60% of consumers expect personalized experiences — and AI is crucial for this.
It seems fascinating, and indeed it is. But fascination without responsibility can be dangerous. The path is not to abandon technology, but to understand it deeply and critically. Brands need to take an ethical, transparent, and responsible stance in the use of AI. This means questioning their own systems, constantly reviewing the data used, ensuring consumer privacy, and above all, keeping the human factor as a central piece of the strategy. Because, in the end, the consumer doesn’t just want to be understood by an algorithm. They want to be understood as a person. And that, as far as I know, is still an irreplaceable human ability.
