AI Adoption in Italian Retail Stalls Despite Strong Experimentation

The survey on artificial intelligence in large-scale retail trade, conducted in collaboration between the tech companies Aton and GTN, ENIA (Italian Foundation for Artificial Intelligence) and Fòrema, a training body within the Confindustria Veneto Est system, revealed that companies are experimenting with innovative solutions, but only one in seventy has reached the industrial scaling stage, while governance and compliance with the AI ​​Act are now essential priorities.

Italian large-scale retail trade (GDO) no longer views artificial intelligence as a futuristic idea, but as an imminent operational necessity. However, the transition from theory to industrial practice is still a long way off. This is what emerges from the AI ​​in GDO survey, conducted by Fòrema and ENIA and commissioned by the tech companies Aton and GTN on a sample of 70 leading companies in the sector (just over 100 in Italy, 46% of which exceed €1 billion in turnover). The survey paints a picture where enthusiasm for the technology’s potential coexists with marked organizational caution.

Aton and GTN, specializing in digital solutions for the retail industry and distribution, both work in the digitalization of commercial activities and traceability

Their synergy has created a technology district with 385 direct employees and a turnover of €33 million. Partners supporting the survey include ENIA , the National Foundation for Artificial Intelligence, Zebra Technologies , Datalogic , Soti as a tech partner, and Largo Consumo as a media partner.

“The strong push toward logistics and back-office efficiency documented by the survey demonstrates that large-scale retail trade believes in the concrete and reliable value of AI,” said Giorgio De Nardi, CEO of Aton. “To move beyond the pilot project phase and achieve a real leap in industrial scale, a systemic vision is needed, capable of translating data into immediate operational decisions that improve speed and precision.”

The results

The most interesting data concerns the digital maturity curve. While 68% of respondents, representing 48 companies, declared themselves immersed in the exploration or active experimentation phase , only one company, equivalent to 1.4% of the sample, declared it had begun “scaling,” or adopting it on an industrial scale. Conversely, 19% of companies in retail, representing 13 entities, have not yet launched any operations, representing the true “bottleneck” of modern retail. It’s not just a matter of making a new technology work, but of making it replicable and sustainable within complex logistics networks and hundreds of physical stores.

“The data showing that just 1% of large-scale retail companies have reached an industrial scaling stage, compared to 68% still at the exploration stage, demonstrates that we are facing a delicate cultural and regulatory shock, even before a technological one,” commented Valeria Lazzaroli , president of the Enia Foundation. “Artificial intelligence cannot be introduced in silos or seen as a mere test of operational efficiency to reduce costs. Without a solid regulatory framework, a widespread data culture, and, above all, massive investments in internal skills to bridge the organizational gap, AI risks generating mistrust rather than value.”

Where artificial intelligence comes into play, it does so by favoring pragmatism over spectacularity, aiming straight for internal efficiency. The most widespread use cases are corporate knowledge bases, adopted by 38 reatil companies, followed by out-of- stock monitoring with 28 applications. Automatic document reconciliation (DDT) and chatbots for customer service account for 23 preferences, while price and promotion management involves 28 companies. Finally, energy consumption optimization reaches 21 applications, demonstrating a focus primarily on reducing operating costs.

Paradoxically, the main obstacle to mass adoption is not technological or financial limitations, but rather organizational ones, where there is a lack of comprehensive governance that allows for the seamless and safe implementation of AI. A lack of specialized internal skills is cited by 41 respondents, closely followed by cultural resistance to change and mistrust of AI (35 responses).

Regulatory challenges are also challenging: only 11 retail companies have formalized an internal AI governance policy, 17 are in the process of defining one, while 42 companies have yet to address compliance with the European AI Act. Uncertainty about the economic return also weighs heavily: for 29 companies, the real benefits of innovation remain “unquantifiable.”

“The survey clearly highlights that the real challenge for large-scale retail trade is no longer technological, but regulatory and governance,” said Paola Geretti, CEO of GTN. “Adopting AI without a formal policy exposes companies to damaging legal and ethical vulnerabilities. To unlock investment and scale projects safely, large-scale retail trade must urgently develop clear governance models that combine the drive towards automation with full data accountability.”

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(Featured image by Abstracts photo via Unsplash)

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