AI in Marketing Optimized with the Help of Hybrid AI
Of Monsters and Ants: Why AI-Powered Marketing & CX Needs Both (Part 2 of 3)
In the speech “Of Monsters and Ants: Why AI-Powered Marketing & CX Needs Both (Part 2 of 3)” on March 11, 2025, I will shed light on the role of artificial intelligence (AI) in marketing and customer experience (CX). This is the second part of the series.
Missed part 1? Read all about the risks of AI in marketing here.
Part 3 will be published shortly – stay tuned!
You can listen to the full presentation on the ShiftCX platform. Feel free to drop by!
AI as a Tool, Not a Solution
"Generative AI has the potential to change the way we interact with machines and make them more human-like."
This statement by Sam Altman has long since become reality. At the heart of this is AI personalization: AI is fundamentally changing the interaction between humans and machines and making it more human. Instead of relying on search engines, we now communicate via chat interfaces that provide us with answers as if we were talking to a colleague or friend. This form of communication is not only more intuitive, but also more natural.
Personalization Through Generative AI: A Change in User Expectations
However, this type of interaction is also changing users’ expectations of digital services. Instead of just receiving an answer to a question, people today want an individually tailored, contextualized approach. They want machines to understand and respond to their communication style and experience a personalized user experience.
But what exactly makes generative AI so powerful? It can summarize, express and transform texts. It adapts flexibly to different contexts and needs and delivers results at lightning speed. The use of chat interfaces such as ChatGPT creates a personalized user experience that makes the dialogue more natural and individual.
However, caution is required, as the AI’s answers are not only based on data and facts, but are also influenced by the perspectives and weightings with which it has been trained. This can lead to certain opinions being favored or others being unconsciously ignored. You can find more details on the topic of bias in machine learning in our blog post on bias in AI.
AI Risks: When Innovation Turns Into Uniformity
Despite the many benefits that generative AI brings, it is important not to lose sight of the potential risks. In the first part of this blog series, we already emphasized that generative AI is powerful, but also unpredictable. Without clear rules and strategies, the use of AI can quickly become problematic for companies. It is like a wild beast that unleashes its powers without control.
The idea of a universal chat interface as a panacea for AI is particularly critical. Chat as a universal tool is not a universal solution. Without in-depth knowledge and the ability to correctly assess the AI’s responses, the results can be inaccurate and – depending on the sensitivity of the topic and the specific usage scenario – involve high risks.
An example of this problem can be seen in a study from the USA in which children use AI to write creative stories. According to Professor Oliver Hauser, the use of AI to promote creativity leads to a reduction in social originality. The danger is that instead of promoting originality, AI leads to a “downward spiral” in which creative processes stagnate. This highlights the need to critically scrutinize the output of AI and control its use.
Generative AI can often become a “one-size-fits-all”, with no rough edges, which could weaken the creativity of users in the long term. If companies see AI as a quick fix for creative processes, this could lead to an impoverishment of originality in the long term.
AI in Marketing: Between Innovation and Responsibility
The right approach to AI plays a crucial role in marketing. Marketing means strengthening your own brand, gaining leads and developing a well thought-out strategy. It is not enough to rely solely on the creative ideas of an AI. Without a clear strategy, content can quickly become inconsistent and confusing.
Develop the ideal AI-powered marketing strategy by striking the right balance between creativity and systems engineering.
A harmonious balance between creativity and systematic engineering is crucial. The idea of AI-supported personalization, in which customers are addressed individually and dynamically, is a positive example of the use of AI. However, without a well thought-out concept, even this technology can quickly get out of hand, as the example of a DPD chatbot that was overly accommodating to customers and thus put the company in a negative light shows.
In addition to strategy, compliance must not be neglected. Compliance with communication guidelines and regulatory requirements is particularly important. Generative AI acts according to the rules with which it has been trained and must be monitored accordingly. AI tools for companies must not act in an uncontrolled manner – they must follow clear rules and guidelines.
Big Tech vs. Reality: AI Tools for Companies Need Expertise
Big Tech gives the impression that the use of AI tools is child’s play and requires little preparation – an “out-of-the-box” solution, so to speak, as if anyone could suddenly win Formula 1 races. But the reality is different. Many users and companies use generative AI such as ChatGPT without any in-depth training or guidance.
Without the necessary understanding of how AI works and its limitations, there is a risk of making mistakes or getting inaccurate results. A profound knowledge of how to use AI correctly is crucial in order to exploit the full potential of this technology.
In marketing as well as in the customer journey, the aim is to guide users safely, give them clear directions and still integrate surprising moments – supported by the targeted use of AI in marketing. But these surprises should also be controlled and planned – not randomly created by generative AI. It’s about understanding AI as a tool that supports the user on their journey without losing control.
AI: Hard Workers or Uncontrollable Beasts?
The future of AI in marketing lies in the right combination of analytical and generative AI. In this interplay, analytics is understood as a “hard worker” that works systematically and efficiently – similar to ants in their division of labor. In contrast, without clear guidance, generative AI remains an “unpredictable beast”, potentially delivering inaccurate or undesirable results.
AI as an enabler enables us to create dynamic and user-centered processes. But for long-term success, we need a combination of analytical AI, which prepares data in a meaningful way and makes it usable, and generative AI, which enables natural interaction. This approach is known as hybrid AI.
Only through this combination can we ensure that AI remains precise and flexible and thus secures long-term value for companies and users.
Outlook: The Next Step
In the last part of this blog series, we will look at specific solutions. How can the combination of generative and analytical AI be used in such a way that companies can address their target groups in a way that is individually tailored but still authentic and in line with communication guidelines?
Read the first part of the blog series here.
Stay tuned for the third and final part.
Contact us today to discuss your business case and work together to develop a customized AI solution that will drive your business forward!
CEO of MORESOPHY
Heiko Beier is a professor of media communication and an entrepreneur specializing in data analytics and artificial intelligence. As an expert in cognitive business transformation, he supports companies in various industries in the design and implementation of digital business models based on smart data technologies.
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