When it comes to artificial intelligence in marketing, it is easy to fall into the temptation to see 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 5 a number that shows how present this technology is already in the industry.
But every technological revolution carries its dilemmas & AI is no different. On one hand, we have an impressive arsenal of possibilities: large-scale customization, optimized campaigns in real time, accurate predictions of behavior. Just think of chatbots that do not sleep, systems that “sentem” the mood of social networks or platforms that generate content in seconds. Everything fast, efficient, and apparently under control. But is it really?The promise to deliver the right message, at the exact moment and to the ideal person sounds almost utopian 'til we remember that for this, there is a huge volume of data being collected, processed and interpreted only.
This question echoes strongly at a time when marketing becomes increasingly data-driven. And here's the point: data is cold, but decisions shouldn't be. AI can, rather, improve strategic decision-making. McKinsey points out, for example, that companies that adopt AI in marketing increase their profits by up to 20% faster than competitors that don't adopt. However, we can't ignore the risk of replacing the sensitive, intuitive, empathetic human gaze 'by a purely algorithmic logic.
Brand communication is not only about efficiency; it is also about connection, emotion and authenticity. There is another critical layer in this debate: inequality of access to technology. Big brands, with robust budgets and dedicated teams, are surfing the AI wave more easily. And small ones? Will they be able to compete in this new scenario, where who has the best AI also has the best opportunities? Marketing may be becoming an increasingly asymmetric game & this should worry us.
And we can't ignore the risks of bias. Algorithms learn from historical data, and historical data carry biases. We've 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 & not always this data reflects 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% from personalized consumers and personalized experiences are crucial.
It seems fascinating, and indeed it is. But fascination without responsibility can be dangerous. The way is not to abandon technology, but to understand it in depth and critical spirit. 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 part of the strategy. Because, in the end, the consumer does not just want to be understood by an algorithm. He wants to be understood as a person. And this, as far as I know, is still an irreplaceable human capacity.
