Generative Artificial Intelligence is radically changing the way digital advertising is done. In daily life, I realize that this technology has transformed every stage of the creative process, from the first insight to the final validation of campaigns.
In the ideation phase, text generation tools offer instant brainstorming, providing quick and creative suggestions for slogans, scripts, or visual concepts. This greatly expands and accelerates the creative process, allowing the exploration of thousands of ideas in a few minutes, without relying solely on personal inspiration.
During content creation, the change becomes even more evident. There are advanced tools that generate complete ads, from well-crafted texts to customized images for different types of audiences. AI finally delivered something the market had been seeking for a long time: hyper-personalization at scale. This allows delivering the right message, at the right time, to the right person with an efficiency that would be impossible manually.
These advances mean not only efficiency gains but also a quantitative leap in campaigns. Ads that used to take weeks to launch are now ready in days or even hours. Major advertisers have already realized this, highlighting that generative AI has significantly reduced the time required for creative production, freeing up more time for the team to focus on strategic decisions.
Furthermore, the quality of the ads has increased because intelligent algorithms analyze previous behaviors and optimize every detail, from titles to images and calls to action, enhancing overall engagement. In practice, many high-performance companies are already adopting these technologies.
Another interesting point is that this revolution is not limited to just creating ads. In the distribution and broadcasting stage, platforms like Meta's AI Sandbox already use AI to dynamically adjust content based on real-time audience reactions, generating multiple automatically adapted versions for each channel. But to make the most of all this, it is essential to have a solid knowledge base. Companies should carefully structure their internal information – from style guides, records of previous campaigns, and product catalogs to customer interactions on social media, reviews, and market research. All of this works as fuel for the AI, allowing it to create more accurate content aligned with the brand's identity.
Today, there are platforms and technologies like Retrieval Augmented Generation (RAG) that can quickly access this database and generate coherent and personalized content. Leading companies, such as Coca-Cola, have already demonstrated the potential of this approach by combining models like GPT-4 and DALL-E with their own collections, ensuring that AI captures and reproduces the true spirit of the brand. Connected to a good database, generative AI also becomes a powerful insights machine. She analyzes huge volumes of information to identify trends and opportunities that often go unnoticed. An example is how big brands can predict consumption trends by analyzing millions of online interactions, generating useful insights for much more effective campaigns.
Next, AI comes into play producing highly personalized content. The results are impressive: texts and images generated instantly and tailored to different audience profiles, drastically increasing the effectiveness of campaigns. A clear example is Michaels Stores, which achieved nearly complete levels of personalization in their communications, significantly improving their results.
Creativity also gains new horizons with AI, enabling even co-creations between brands and consumers. Coca-Cola's "Create Real Magic" campaign is a great example, with consumers using AI to generate unique artwork, reaching very high levels of engagement.
It is worth emphasizing that, even with all this automation, the human factor remains essential. The role of professionals becomes one of curation and refinement, selecting and enhancing the ideas generated by AI, ensuring strategic and emotional alignment of the campaigns. Another important benefit is the prior validation of ideas. Today, AI models simulate campaign performance before they go live, helping to quickly identify what works best and significantly reducing risk. Companies like Kantar already do this in minutes, predicting the actual impact of ads even before they are launched.
These simulations go beyond the numbers, also providing qualitative insights that help understand how different audiences might react to a campaign, functioning as true virtual focus groups.
The key to making all of this work well is the correct data. Proprietary data, social media, market reports, customer service conversations, and previously produced content are essential for AI to deliver truly personalized and effective results.
This transformation is here to stay. Today it is possible to do much more with less, launching more targeted, faster campaigns with high return potential. Sure, challenges exist, such as ensuring ethics and quality, but the path is already clear: digital advertising will increasingly be guided by Artificial Intelligence, and the marketing professional will play a key strategic role in steering and refining these results.
