Historic Trademarks, AI, and Heritage Marketing

In 1822, Jean-François Champollion succeeded in deciphering the Rosetta Stone, the administrative document translated into three languages, Greek, Demotic and hieroglyphic, which had been discovered more than twenty years earlier. With this discovery, the French scholar did not uncover a new civilization, but made comprehensible what already existed.

This episode is also useful for interpreting the role that artificial intelligence can play in companies that are custodians of historic Italian trademarks. AI is often associated with automation technology, but this view helps explain why many companies, especially smaller ones, struggle to adopt a technology that, understood in this way, would seem poorly suited to innovating the processes of organizations whose DNA lies, by definition, in quality, craftsmanship and the narration of values.

Precisely for this reason, before even thinking about automating activities, AI should be interpreted as a function capable of connecting emails, catalogues, offers and contacts, making the company’s history accessible so that its memory can be consulted and reworked.

Historic trademarks are not simply long-established companies. They are complex systems of trust, built over time through consistency and continuity. Their value does not lie only in their products, but in the credibility accumulated among customers, distributors and local communities. This trust is nourished by a memory that is not always digitized: past decisions, consolidated relationships, progressive adaptations to markets, mistakes and corrections.

This memory is often not formalized, but distributed among people, documents, archives and individual practices. In companies with a long history, information is not lacking: it is simply difficult to read and, therefore, to share. It exists in paper archives, in personal emails, in the accounts of those who experienced specific phases of the company’s development. Without a process of recomposition, this heritage risks remaining inaccessible or, worse, being dispersed through generational change.

It is in this space that artificial intelligence finds one of its most relevant applications. Not as a tool for the automatic production of content, but as an infrastructure for translating corporate memory. By securely connecting systems such as document archives, CRM platforms, and commercial and technical correspondence, AI can make the company’s history searchable: reconstructing the logic behind a strategic choice, identifying recurring patterns in customer relationships in order to understand how the positioning of a product has evolved over time, and enabling the reuse of information that has already been produced.

This step is particularly delicate for historic trademarks because it directly concerns the subject of heritage. Heritage is not a static narrative to be used in communication, but a dynamic system of styles, materials and price positioning that must be continuously reinterpreted. If it is not understood and shared within the organization, it risks becoming a decorative element, useful for marketing but disconnected from operational decisions.

Artificial intelligence can help avoid this disconnect because, thanks to the ease of use of language models, it can help connect past and present, turning heritage into a concrete lever for guiding choices. For example, by analysing how the company has responded over time to market changes, it is possible to identify recurring principles that can guide future decisions. Similarly, by observing relationships with long-standing customers, it becomes possible to better understand the dynamics of trust that have supported the company’s growth and apply them to new customers, markets and channels.

Another central aspect concerns trust itself. In historic trademarks, the relationship with the customer is not only transactional, but relational. It is built on continuity, recognizability and reliability. Today, however, this relationship is under pressure from faster and more fragmented markets.

AI can support the preservation of this trust not by replacing the relationship, but by strengthening its quality. For example, it makes it possible to reconstruct the history of interactions with a customer, understand preferences and critical issues, and anticipate needs based on past experience.

ANDREA BOSCARO

Partner The Vortex