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The Pathogenesis of Digital Marketing as Highlighted by Extensive AI Use. Nobody has dared to talk about these five problems until today. Theodoros Moulos, the CEO of GrowthRocks, uses AI 3-4 hours a day and comments on emerging issues.

Lack of horizontal technical skills 

AI is not just a platform. It’s an extensive process that requires a broader technical background and knowledge. Initially, those who worked with AI were content creators (copywriters) who, on the one hand, only specialized in that subject and on the other hand, didn’t have the foundation to benefit from content available in different forms. For example, let’s look at the following five areas that are considered advanced AI use:

a) Transforming my favorite podcast or TedTalk into a series of articles.

b) Analyzing my competitors and their service descriptions and using this as the basis for my own content.

c) Analyzing photos of my products or services and personalizing them in relation to my audience personas. For example, having a tailored hotel room description for couples on their honeymoon.

d) Creating photos with no typographical errors that don’t appear to be made with AI tools like Canvas.

e) Creating content by analyzing the performance of my paid ads and drawing conclusions that are useful and practical for my internal users or readers.
f) Creating a complete, detailed syllabus for a digital course (courses, lessons, benefits, scripts, educational material).

The examples above share a common characteristic: They require knowledge in 10 different subjects, from voice synthesis to podcast integration and subtitle analysis. With this knowledge, one can use AI effectively and constructively to create content that generates conversions. However, everyone still needs help with this problem: Their AI-made material does not convert into customers.

If you are good, AI will make you better; if you are bad, AI will make you worse! @tmoulos Click To Tweet

Failing To Create Added Value

AI highlights the pathogenesis of a system that consumes and recycles value instead of producing it. Historically, in digital marketing, a few (about 2%) create value (concepts, playbooks, methodologies, systems), and everyone else either absorbs or reuses it. This was more challenging in the pre-AI era than in the post-AI era. Hence, we now see the quality of marketing content significantly reduced in terms of value and messaging. We are reading more and more texts created by AI that are simply substance-less. They are written to cover the keywords needed to rank in Google, providing no added value to the readers. As a result, this practice won’t shortly have any value, even for SEO reasons. Sooner or later, this change will happen and be applied retroactively, as with every upgrade of Google’s SEO algorithm.

We shouldn’t accuse just the ease and hastiness with which we treat digital marketing but also the fear of marketers becoming replaceable by sharing knowledge with competitors or readers. This mentality is more common in Small Countries than in England or America. I attribute this to the small size of the market and the lack of education on the use of AI.

Upskill or Die

AI has highlighted another problem: we don’t know everything and need to continue learning new things. Learning means investing. Investing means buying resources that others have created so I can familiarize myself with a subject and its use. However, investing also means knowing that I need to allocate money to learning and that quality knowledge isn’t free. Even if that means investing my time, the most expensive thing at my disposal due to lost income.

All the above are investments. And without investment, there is no return. In that sense, AI is not a marathon but a sprint. The faster someone grasps its use, the faster they will get more projects and have greater profit margins & satisfied employees. It’s that simple. 🙂

For example, to create our educational program on AI and efficiently integrate it into our processes, we attended almost all academic programs on the market and bought about 50 AI tools to examine their usefulness in our daily lives.

Short Supply Of Marketing Experts

AI has exposed another problem. Even when professionals finally learn to use AI prompting correctly, they still don’t have the theoretical basis to understand what they should be asking because they lack creative thinking or training on theoretical topics, such as knowledge of frameworks, etc.

Let’s start by (re)defining the term “Marketer”. A marketer is not just someone who graduated from a marketing school, attended a seminar, or has been involved in marketing for several years. A marketer is an individual who continuously tries to recognize or create opportunities to promote their product, business, or services. It’s the individual we see constantly traveling, taking photos of clever advertising messages wherever they are, or consuming hours on TikTok to discover new market trends and promotion methods. I imagine that they have a large audience on LinkedIn. As a kid, they probably were trying to monetize their early activities, such as painting and selling childish designs, exchanging subscription cards, or running dropshipping sites.

[That is how we would describe the persona of a marketer in the real world]

Speaking out Loud about AI

For now, the use of AI remains an agency’s well-kept secret. It’s about time it becomes a competitive advantage. Customers don’t come from another planet. They listen, read, and see what AI means for marketing and want specialized partners so they can benefit from its advantages. Customers increasingly tell us, “We found you while using AI.” So, how far is the question, “To what extent and in what way will you use AI if we collaborate?” The winner, in the end, is the person that will answer that question correctly. What the correct answer is, I leave to you 🙂

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