This article was not made with (artificial) intelligence — but the header was

Like any professional activity that has somehow been impacted by some kind of new technology, advertising is an activity that -thanks to this- has constantly evolved in recent decades. From the first print ads to the ads in digital environments, the process of thinking and creating original ideas has been fundamental for the growth and maturity of the advertising industry. However, with the growing popularity and use of AI, in each meeting, after-lunch talk, and coffee chat, the question of how it can affect this creative process has been steadily popping up.

But before we focus on what is happening today, it is worth reviewing and remembering some technologies that broke into our lives both personally and professionally, and which all have one factor in common. In the first instance, we can name that moment when agencies bought their first Macs, bringing with them a new way of approaching tasks, doing, solving problems, and making stuff happen. In the second part of the 90s, with the start of mass access to the Web, new platforms surfaced, new ways of relating, new needs, and new solutions for those needs. We could name other milestones, such as the emergence of social networks, or the adoption of smartphones, both being key moments in terms of how they impacted our industry, giving it the shape it has today.

We mentioned a common factor earlier. That common factor is that they have all taken us, in their own way and at their own pace or speed, through three different phases of adopting new technologies.

Phase 1: the arrival of “the new”. The new technology appears, first adopted by a few, then its scope and use increase. At this point, hyperbolic rhetoric develops: this technology will solve all the problems… or else a whole new bunch of issues will be created by its use. There is a tendency towards radicalization: this new technology is either good or bad, with no middle ground. Exaggerations are heard, written, and predicted in all directions. We have experienced this many times, from social networks to NFTs to search engines to video games to the metaverse.

Then comes Phase 2: the “unmasking”. It turns out that with time, adoption, and use of the technology in question, all the good and utopian things that were predicted to happen generally did not happen, but neither did the bad. One lives in a constant situation of ambivalence, with conflicting and confusing feelings and thoughts. Boredom also appears as a factor to be taken into account: we are no longer as surprised or excited as before, being victims of the so-called “roller coaster syndrome” (there comes a time when if we ride the same roller coaster enough times, it will no longer generate the same effects). Perhaps a good example of technology in this stage is -even today- smartphones.

Finally, Phase 3: “invisibility”. In this last phase, technology is not perceived as such, or at least is no longer externalized, as it is perceived as part of everyday life, integrated into our routines, habits, and processes. What is obtained by its use and application is what is expected, and no more than that. Expectations, in this instance, are replaced by concrete facts. In this instance, we could say that smart TVs or computers are invisible to our eyes, for example.

Having identified and established these 3 phases, we can now clearly see that everything concerning the use and application of AI in at least our activity is clearly in its first phase. In recent months we have seen, read, and heard everything. Apocalyptic predictions, confronted with pro-AI positions advocating the rapid massification of platforms that use AI for whatever. Also, fortunately, we have access, usually immediately and at least initially for free, to be able to try these platforms firsthand, understand how they work, what exactly they do, and see how we can take steps to integrate them into our routines, habits, processes, and experiences today.

And therein lies a large part of what it takes to understand any new technology: you have to use it, live it, and experience it. Trial and error, a thousand times, if it is necessary. That is why it is at least curious that with many of these platforms within our reach just a few months ago (we are now in April 2023), gurus and ‘experts’ appear everywhere (btw, I now remember Malcolm Gladwell and his theory that to be an expert in something, you have to invest at least 10,000 hours in it) wanting to teach and explain with certain dubious authority topics and things that have to be experienced in the first person to be able to really dimension, internalize, digest and apply them in practice.

Like riding a bike or making a barbecue, we are facing many actions that are only learned and understood in depth in practice, not in theory. We could perhaps delve deeper into the difference between information and knowledge, but that is the subject of another article.

As far as its application in advertising is concerned, it seems to be quite efficient (it remains to be seen if it is effective) when it comes to research, being used to examine vast amounts of information (profiles, behaviors, etc.) about audiences and customers. It is also taken into account when automating repetitive tasks where human intervention obviously does not add up to much, or where sometimes it is not possible to find a human willing to do such tasks. We’ve seen it also have an impact on programmatic campaign planning and optimization, to mention another area where AI has started to be adopted (85% of programmatic ads are bought by automated algorithms, demonstrating the growing use of AI, according to Business Insider).

But none of these areas are my area of expertise. Since I started working in that hybrid area between advertising communication and new technologies quite a few years ago, my focus has always been on creating solutions and/or messages that help brands achieve their goals. And it is from that perspective that I propose to think and reflect on the impact of AI in this industry. But of course, this article has already become long, and I don’t intend to identify opportunities and solutions without first asking the necessary questions. And for that, I look forward to seeing you in the next article.