This thesis explores the integration of Artificial Intelligence (AI) into the processes of Small and Medium-Sized Enterprises (SMEs), with a specific focus on the features and foundational elements of an entrepreneurial project for contract automation. It proposes a Contract Lifecycle Management (CLM) model enhanced by AI modules and integrated into companies’ existing management systems (CRM/ERP). This solution is not merely a technological upgrade but a strategic organizational choice that turns the contract into an informational-productive asset, with positive, measurable benefits in terms of time, costs, and errors. The proposed AI software generally falls outside the “high-risk” category under the AI Act (2024), while remaining subject to obligations of transparency and informational fairness. The analysis extends to a comparative review of the current political, economic, and regulatory landscape on Artificial Intelligence (international, European, and Italian), including specific considerations regarding the new European Artificial Intelligence Regulation (AI Act, 2024), the new Product Liability Directive (PLD, 2024), and the GDPR (2016), outlining an integrated allocation of responsibilities along the supplier–SME–third-party chain. From a private-law perspective, it clarifies that AI systems operate as assistive-operational tools whose outputs remain attributable to the parties through mechanisms of identification and electronic signature, framing the current legal-interpretative issues and emphasizing the paradigm of risk assumption. From a business-economic standpoint, the thesis examines management systems and, specifically, how CRMs constitute the most suitable infrastructure for channeling AI into SMEs, taking into account the typical barriers these organizations must overcome, such as data availability and quality and skills shortages. It also provides a framework for the accounting treatment of AI systems like the one proposed, in accordance with Italian civil-law principles and the OIC standards. The paper concludes with an analysis of the results of a qualitative survey conducted on a sample of Italian SMEs (specifically, those based in Veneto), which reveals a positive perception of AI as a lever for efficiency, especially in organizational and commercial processes. The willingness to invest is high, particularly in solutions that automate bureaucratic-administrative tasks. Nonetheless, there remains a strong demand for clearer and stronger public rules on safety and data protection, with particular attention to risks related to output quality and the erosion of human values.
Tale tesi esplora l’integrazione dell’Intelligenza Artificiale (IA) nei processi delle Piccole e Medie Imprese (PMI), con un focus specifico sulle caratteristiche e sugli elementi fondativi di un progetto imprenditoriale di automazione contrattuale. L’elaborato propone un modello di “Contract Lifecycle Management” (CLM) potenziato da moduli di IA, e integrato nei sistemi gestionali (CRM/ERP) esistenti in azienda. Tale soluzione non rappresenta un mero aggiornamento tecnologico, ma una scelta organizzativa strategica che trasforma il contratto in un asset informativo-produttivo, con benefici positivi e misurabili in termini di tempi, costi ed errori. Il software IA proposto viene a qualificarsi, di regola, al di fuori della categoria dei sistemi ad “alto rischio” secondo l’AI Act (2024), pur rimanendo soggetto a obblighi di trasparenza e correttezza informativa. L’analisi si estende a considerazioni comparate del quadro politico, economico, e normativo, ad oggi esistente in tema di Intelligenza Artificiale (sia internazionale, che europeo e italiano), includendo specifiche considerazioni in ottica del nuovo Regolamento europeo sull’Intelligenza Artificiale (AI Act, 2024), nonché della nuova Direttiva sulla responsabilità da prodotto difettoso (PLD, 2024) e del GDPR (2016), delineando una mappa integrata delle responsabilità lungo la filiera fornitore-PMI-terzi. Sul piano civilistico, si chiarisce che i sistemi IA operano come strumenti assistenziali-esecutivi, il cui operato rimane imputabile alle parti tramite meccanismi di identificazione e di firma elettronica, inquadrando le problematiche giuridico-interpretative in essere, e ponendo l’accento sul paradigma dell’assunzione del rischio. Sotto il profilo economico-aziendale, la tesi esplora i sistemi gestionali, e nello specifico, come i CRM costituiscano l’infrastruttura più ideale per veicolare l’IA nelle PMI, prendendo in considerazione le barriere tipiche che queste realtà sono chiamate a superare, come la reperibilità e l’alta qualità dei dati o la carenza di competenze. Viene inoltre fornito un framework per il trattamento contabile di sistemi IA come quello proposto, secondo i principi civilistici e OIC. L’elaborato si conclude con l’analisi dei risultati di un’indagine qualitativa condotta su un campione di PMI italiane (venete, nello specifico), dalla quale emerge una percezione positiva dell’IA come leva di efficienza, soprattutto nei processi organizzativi e commerciali. La propensione a investire risulta alta, in particolare per quelle soluzioni che automatizzano compiti burocratici-amministrativi. Tuttavia, permane una forte richiesta di regole pubbliche più forti e chiare in materia di sicurezza e tutela dei dati, ponendo una particolare attenzione ai rischi legati alla qualità degli output e alla perdita di valori umani.
L'integrazione dell’IA nelle PMI: profili giuridici ed economici di un progetto di automazione contrattuale all’interno di software gestionali personalizzati
D'AGOSTINI, PIERNICOLA
2024/2025
Abstract
This thesis explores the integration of Artificial Intelligence (AI) into the processes of Small and Medium-Sized Enterprises (SMEs), with a specific focus on the features and foundational elements of an entrepreneurial project for contract automation. It proposes a Contract Lifecycle Management (CLM) model enhanced by AI modules and integrated into companies’ existing management systems (CRM/ERP). This solution is not merely a technological upgrade but a strategic organizational choice that turns the contract into an informational-productive asset, with positive, measurable benefits in terms of time, costs, and errors. The proposed AI software generally falls outside the “high-risk” category under the AI Act (2024), while remaining subject to obligations of transparency and informational fairness. The analysis extends to a comparative review of the current political, economic, and regulatory landscape on Artificial Intelligence (international, European, and Italian), including specific considerations regarding the new European Artificial Intelligence Regulation (AI Act, 2024), the new Product Liability Directive (PLD, 2024), and the GDPR (2016), outlining an integrated allocation of responsibilities along the supplier–SME–third-party chain. From a private-law perspective, it clarifies that AI systems operate as assistive-operational tools whose outputs remain attributable to the parties through mechanisms of identification and electronic signature, framing the current legal-interpretative issues and emphasizing the paradigm of risk assumption. From a business-economic standpoint, the thesis examines management systems and, specifically, how CRMs constitute the most suitable infrastructure for channeling AI into SMEs, taking into account the typical barriers these organizations must overcome, such as data availability and quality and skills shortages. It also provides a framework for the accounting treatment of AI systems like the one proposed, in accordance with Italian civil-law principles and the OIC standards. The paper concludes with an analysis of the results of a qualitative survey conducted on a sample of Italian SMEs (specifically, those based in Veneto), which reveals a positive perception of AI as a lever for efficiency, especially in organizational and commercial processes. The willingness to invest is high, particularly in solutions that automate bureaucratic-administrative tasks. Nonetheless, there remains a strong demand for clearer and stronger public rules on safety and data protection, with particular attention to risks related to output quality and the erosion of human values.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/94449