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