Industria avanzata e intelligenza artificiale: un nuovo paradigma per competitività, sostenibilità e valore

Autori

  • Andrea Santoni Ente Nazionale per l'Intelligenza Artificiale Autore

DOI:

https://doi.org/10.82015/NNR.2025.100103

Parole chiave:

Intelligenza Artificiale; Industria; Innovazione; Competitività; Digitalizzazione.

Abstract

L’intelligenza artificiale (IA) sta ridefinendo i paradigmi dell’industria avanzata, imponendosi come fattore chiave per la competitività in un contesto globale segnato da incertezza e trasformazioni rapide. Realizzato nel contesto del 1°Congresso Nazionale dell’Ente Nazionale per l’Intelligenza Artificiale (ENIA) “L’Economia dell’IA: Ricchezza, Regole e Rigenerazione”, l’articolo approfondisce alcuni degli impatti specifici dell’IA sull’industria avanzata per la quale E.N.I.A. ha istituito un’apposita Commissione.

L’Italia, pur vantando una solida tradizione industriale manifatturiera, è chiamata a colmare significativi ritardi nell’adozione di tecnologie digitali e nella valorizzazione del dato. In questo articolo, si analizzano le applicazioni concrete dell’IA e i potenziali benefici in termini di efficienza, resilienza e adattabilità delle filiere. Si discutono inoltre le sfide associate a questo cambiamento, a partire dalla necessità di nuovi modelli organizzativi e di partnership tra pubblico, privato e ricerca, proponendo le direttrici strategiche per una trasformazione sistemica e inclusiva.

Biografia autore

  • Andrea Santoni, Ente Nazionale per l'Intelligenza Artificiale

    Executive manager nel settore ICT. In qualità di COO, si occupa di organizzazione e pianificazione strategica in Sealence SB Spa, PMI innovativa nel settore delle propulsioni navali elettriche. Membro del board tecnico-scientifico di E.N.I.A. e Coordinatore della Commissione per la promozione dell’industria avanzata, guida l’adozione etica dell’IA.

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Pubblicato

18.11.2025

Come citare

Industria avanzata e intelligenza artificiale: un nuovo paradigma per competitività, sostenibilità e valore. (2025). Neural Nexus Review, 1(1), 78-124. https://doi.org/10.82015/NNR.2025.100103