The original version of this article was published in Italian by the same author on 5 April 2025.
“Create five Instagram posts to promote the master’s degree programme in Communication and Digital Cultures at the University of Macerata. Address a young audience using a direct and engaging tone, and highlight that the programme includes lectures and hands-on labs focused on artificial intelligence and generative AI. Add hashtags and emojis. The five posts should be customised based on different educational backgrounds: classical high school, scientific high school, human sciences high school, technical institutes, and working professionals who wish to complete a master’s degree.”
This is a prompt to be used with Claude, Gemini, ChatGPT, or any other modern large language model – LLM.
It marks the beginning of a journey towards increasingly personalised content, attraction strategies, and marketing policies through large-scale customisation.
Even more could be done by continuing to personalise, for example, based on gender, geographic origin, and personal interests.
Image: Canva.
Large-scale customisation
Generative AI is radically transforming the way companies interact with their customers.
For the first time in history, mass personalisation is no longer just a theoretical concept – it’s a tangible, accessible reality.
What once required creative teams, weeks of work, and substantial budgets can now be achieved in minutes with a well-crafted prompt.
Companies can now create tailored content for increasingly specific audience segments, moving beyond the traditional demographic approach to embrace personalisation based on interests, behaviours, values, and even emotional states.
This revolution meets a fundamental need of today’s consumers: to be treated as unique individuals, not just as numbers.
AI at work
Generative AI isn’t just about creating content — it excels at analysing vast amounts of data to uncover hidden patterns and predict future behaviour.
Platforms like Persado use AI to analyse emotional reactions to marketing messages, while tools such as Obviously AI allow even non-data experts to build sophisticated predictive models.
In the fashion industry, some companies are using AI algorithms to analyse customer preferences and predict which styles they might enjoy.
Stitch Fix is a prime example: their system considers not only past purchases, but also explicit and implicit feedback, creating a constantly evolving style profile for each customer.
Perhaps the most groundbreaking application of generative AI in marketing is its ability to generate tailor-made content.
In tourism, companies like Expedia are testing AI-generated personalised itineraries that take into account not just the traveller’s stated preferences, but also factors like forecasted weather, local events, and even moods expressed on social media.
Retail is another rapidly evolving sector.
Sephora uses generative AI to craft personalised product descriptions based on skin type, beauty concerns, and even the customer’s language in previous reviews.
In the B2B space, platforms like Drift and Intercom have implemented generative AI chatbots that not only answer questions, but also adapt tone and content based on the user’s industry, company size, and even job role.
In multimedia advertising, tools like Midjourney and DALL·E are transforming the production of custom visuals, while GPT-4 and Claude 3 enable the creation of personalised ad copy for different audience segments — in just seconds.
The Berlaymont building in Brussels hosts the headquarters of the European Commission. Photo by Wikimedia Commons.
Transparency in the age of the AI Act
With the European Union AI Act coming into force, transparency is no longer just a best practice — it’s a legal requirement. Companies must now:
- Inform users when they are interacting with AI-generated content.
- Document the development and implementation processes of AI models.
- Ensure traceability of decisions made by automated systems.
- Implement human oversight mechanisms for high-risk applications.
This new regulatory framework presents both a challenge and an opportunity.
Companies that adopt an “ethics by design” approach can set themselves apart from the competition by building lasting relationships of trust with their customers.
Tools like Explainable AI – XAI – are emerging to help organisations understand and communicate how their AI systems arrive at certain decisions or recommendations, making processes more transparent — both internally and to consumers.
Image: Canva.
Mass personalisation, anything but easy
Despite its revolutionary potential, personalisation powered by generative AI faces several key challenges.
Personalisation requires data — a lot of it.
At the same time, however, consumers are becoming increasingly aware of – and protective over – their digital privacy.
Companies must find a balance between personalisation and privacy, adopting approaches like “privacy by design” and building systems that allow users to control which data is used and how.
Over-personalisation can lead to what’s known as a “filter bubble,” where users are only exposed to content that reinforces their existing beliefs.
This can limit the discovery of new products and services and, ultimately, stifle innovation.
Forward-thinking companies are experimenting with systems that deliberately introduce elements of “controlled serendipity” into their recommendation algorithms.
While consumers appreciate the convenience of automated personalisation, they still value the empathy and understanding that only a human can provide.
The most promising future lies in a hybrid approach — where generative AI handles large-scale personalisation, and human beings step in at key moments of the customer journey.
Interdisciplinary skills
Marketing driven by generative AI requires a range of skills that few organisations possess today.
- Technical Skills: Understanding AI models, prompt engineering, and data analysis.
- Creative Skills: Storytelling, design thinking, and understanding human emotions.
- Ethical and Regulatory Skills: Awareness of the ethical implications of AI and knowledge of privacy and AI regulations.
- Strategic Skills: The ability to integrate generative AI into the overall business strategy.
Universities and business schools are beginning to develop interdisciplinary programs to train this new generation of professionals, but there is still a significant gap between the demand and supply of these skills in the market.
Photo: Canva.
Generative AI in conversational and contextual marketing
The next frontier of personalisation seems to be an increasingly conversational marketing – where brands do not just talk to consumers, but actively engage with them in an ongoing dialogue mediated by AI.
Imagine a future where a customer’s favorite brand knows them so well that it anticipates their needs, adjusting not only the message but the entire customer journey to their specific context.
A shopping experience that adapts to their mood in real time, a travel assistant that alters recommendations based on live weather conditions, a virtual financial advisor that tailors its advice to their evolving economic situation.
This future is already under construction.
The companies that succeed in balancing the power of generative AI with a genuine respect for the dignity and autonomy of their customers will be the ones to thrive in this new era of mass personalisation.
Efficiency and ethics
Generative AI is redefining the boundaries of what’s possible in marketing and communication.
Mass personalisation is no longer a luxury reserved for large companies with enormous budgets, but a strategy accessible to organisations of all sizes.
With this great power comes great responsibility: long-term success will depend not only on technological sophistication but also on the ability to use these tools ethically, transparently, and with a true focus on the customer.
Much will depend on the capacity for intelligent and creative collaboration between humans and algorithms.
The companies that manage to find the right balance between automation and authenticity, data and humanity, efficiency and ethics will be the ones that define the future of communication and marketing in the age of generative AI.
