This dissertation examines the role of Artificial Intelligence in innovative startups, with particular attention to its contribution to growth processes, economic and financial monitoring, and corporate turnaround strategies. After analysing the Italian regulatory framework for innovative startups, introduced by Legislative Decree No. 179/2012, the study explores the main characteristics of these companies, the incentives provided by the legislator, and the financing instruments available to them. The dissertation then investigates the use of Artificial Intelligence during the startup creation and development stages, highlighting its usefulness in product validation, predictive market analysis, and management control. AI can improve the quality of available information, support managerial decision-making, and monitor economic and financial indicators more efficiently. Particular attention is devoted to the phenomenon of so-called “zombie startups”, namely companies that continue operating despite showing signs of stagnation and difficulties in achieving a sustainable business model. Through the analysis of financial statements and indicators such as profitability, financial structure, liquidity, cash burn rate, and financial runway, the study identifies the main warning signs that may precede a crisis situation. Finally, the dissertation highlights how Artificial Intelligence can facilitate the early diagnosis of corporate imbalances and support turnaround strategies based on business model revision, cost control, and the use of predictive tools. The study concludes that the conscious integration of AI into business processes can help prevent or overcome the condition of zombie startups, improving decision-making capabilities and supporting more sustainable growth paths over time.
Il presente elaborato analizza il ruolo dell’Intelligenza Artificiale nelle startup innovative, con particolare attenzione al suo contributo nei processi di crescita, monitoraggio economico-finanziario e risanamento aziendale. Dopo aver esaminato il quadro normativo italiano delle startup innovative, introdotto dal D.L. 179/2012, la ricerca approfondisce le principali caratteristiche di tali imprese, le agevolazioni previste dal legislatore e gli strumenti di finanziamento a loro disposizione. Successivamente viene analizzato l’impiego dell’Intelligenza Artificiale nelle fasi di avvio e sviluppo della startup, evidenziandone l’utilità nella validazione del prodotto, nell’analisi predittiva del mercato e nel controllo di gestione. L’AI consente infatti di migliorare la qualità delle informazioni disponibili, supportare le decisioni manageriali e monitorare in modo più efficiente gli indicatori economico-finanziari. Particolare attenzione è dedicata al fenomeno delle cosiddette “zombie startup”, ossia imprese che, pur continuando a operare, presentano condizioni di stagnazione e difficoltà nel raggiungere un modello di business sostenibile. Attraverso l’analisi del bilancio e di indicatori quali redditività, struttura finanziaria, liquidità, cash burn rate e runway finanziaria, vengono individuati i principali segnali di deterioramento che possono precedere una situazione di crisi. Infine, il lavoro evidenzia come l’Intelligenza Artificiale possa favorire la diagnosi precoce degli squilibri aziendali e supportare strategie di turnaround basate sulla revisione del modello di business, sul controllo dei costi e sull’utilizzo di strumenti predittivi. La tesi conclude che l’integrazione consapevole dell’AI nei processi aziendali può contribuire a prevenire o superare la condizione di zombie startup, migliorando la capacità decisionale e sostenendo percorsi di crescita più sostenibili nel tempo.
START-UP INNOVATIVE E INTELLIGENZA ARTIFICIALE: CRESCITA E STRATEGIE DI TURNAROUND PER START-UP ZOMBIE
ASIF, AMNA
2025/2026
Abstract
This dissertation examines the role of Artificial Intelligence in innovative startups, with particular attention to its contribution to growth processes, economic and financial monitoring, and corporate turnaround strategies. After analysing the Italian regulatory framework for innovative startups, introduced by Legislative Decree No. 179/2012, the study explores the main characteristics of these companies, the incentives provided by the legislator, and the financing instruments available to them. The dissertation then investigates the use of Artificial Intelligence during the startup creation and development stages, highlighting its usefulness in product validation, predictive market analysis, and management control. AI can improve the quality of available information, support managerial decision-making, and monitor economic and financial indicators more efficiently. Particular attention is devoted to the phenomenon of so-called “zombie startups”, namely companies that continue operating despite showing signs of stagnation and difficulties in achieving a sustainable business model. Through the analysis of financial statements and indicators such as profitability, financial structure, liquidity, cash burn rate, and financial runway, the study identifies the main warning signs that may precede a crisis situation. Finally, the dissertation highlights how Artificial Intelligence can facilitate the early diagnosis of corporate imbalances and support turnaround strategies based on business model revision, cost control, and the use of predictive tools. The study concludes that the conscious integration of AI into business processes can help prevent or overcome the condition of zombie startups, improving decision-making capabilities and supporting more sustainable growth paths over time.| File | Dimensione | Formato | |
|---|---|---|---|
|
amna 2 PDFA upload.pdf
accesso aperto
Dimensione
777.87 kB
Formato
Adobe PDF
|
777.87 kB | Adobe PDF | Visualizza/Apri |
I documenti in UNITESI sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/20.500.12075/28730