In the recent decade, Artificial Intelligence (AI) has achieved unprecedented levels of development, and its expansion has not yet slowed. This rapid rise of AI is enabled by the success of machine learning algorithms which can now be trained with huge dataset and large-scale computing. Overcoming the pre-programmed logic, self- adapting algorithms are being employed in a variety of situations for the first time in human history: industrial operations, data analysis, and a wide range of daily activities. In academic literature, a lot of effort has been made in the study the possible AI applications in the public sector. However, this analysis is almost made from a technical point of view, without providing evidence of how different countries are developing these solutions. Moreover, it is not clear how much states are investing in the development of these projects and in the enabling factors behind them, i.e., the presence of technical infrastructures, the access to high quality datasets, the availability of skilled human resources. Thus, there is a lack of literature concerning an assessment of the investments that governments have planned and the efforts that different European countries are currently doing. Moving from these gaps, the research question and the objective of the study are defined. Therefore, the aim of the thesis is to develop an index to assess the level of AI adoption within European countries. A large set of indicators are collected from existing indexes (such as the AI Watch Index by the European Commission, the Government AI Readiness Index by Oxford Insights, and the Global AI Index by Tortoise Media) to build a new index, with a solid and comprehensive structure. As a result, the AI Maturity Index (AIMI) is developed to measure the readiness of EU Member States in implementing AI solutions, adopting a policy making orientation. Indeed, in each of the four pillars of the index (Public Administration, Enterprises, Human Capital, Infrastructure) indicators are classified into enabling factors and achieved results. This research provides relevant theoretical and managerial implications for the academic literature and for practitioners. Limitations and perspective for future research are then provided.
Negli ultimi dieci anni, lo sviluppo dell'intelligenza artificiale (IA) ha raggiunto livelli senza precedenti e la sua fase di espansione non mostra segni di rallentamento. Questa rapida ascesa è stata favorita dal successo degli algoritmi di apprendimento automatico, che ora possono essere addestrati grazie alle enormi serie di dati a disposizione e all’aumento della capacità computazionale su larga scala. Per la prima volta nella storia gli algoritmi superano la logica pre-programmata e diventano auto- adattativi, quindi applicabili per molteplici scopi: ottimizzazione dei processi industriali, analisi dei dati e in una vasta gamma di attività quotidiane. Nella letteratura accademica vengono ampiamente trattate tutte le possibili applicazioni dell'IA nel settore pubblico. Tuttavia, questa analisi è condotta da un punto di vista tecnico, senza fornire dati concreti di come i diversi paesi stiano sviluppando queste soluzioni. Inoltre, non è chiaro quanto le nazioni stiano investendo nello sviluppo di questi progetti e nei fattori abilitanti che ne sono alla base, come la presenza di infrastrutture, l'accesso a serie di dati di alta qualità e la disponibilità di risorse umane qualificate. Difatti, nella letteratura esistente mancano informazioni relative agli investimenti pianificati dai governi e sugli sforzi profusi dai diversi paesi europei. Tenendo in considerazione queste lacune, vengono definiti la domanda di ricerca e l'obiettivo della tesi, ovvero lo sviluppo di un indice per valutare il livello di adozione dell'IA nei paesi europei. Un ampio numero di metriche è stato raccolto da indici esistenti (come l'AI Watch Index della Commissione Europea, il Government AI Readiness Index di Oxford Insights e il Global AI Index di Tortoise Media) al fine di costruire un nuovo indice, il più completo e preciso possibile, con una struttura solida ed esaustiva: l'AI Maturity Index (AIMI). Lo scopo dell’indice è quello di misurare la prontezza degli Stati membri dell'UE nell'attuare soluzioni di Intelligenza Artificiale con un orientamento al policy-making. Infatti, in ognuna delle quattro dimensioni (Pubblica Amministrazione, Imprese, Capitale Umano, Infrastrutture) le metriche sono classificate in Fattori Abilitanti e Risultati Ottenuti. Infine, vengono descritte le implicazioni teoriche e manageriali della ricerca, sia per la letteratura accademica che per i professionisti, evidenziandone i limiti e fornendo prospettive per studi futuri.
Adopting artificial intelligence in EU member states: an AI maturity index
SCALDAFERRI, ARIANNA;VENTURA, IRENE
2021/2022
Abstract
In the recent decade, Artificial Intelligence (AI) has achieved unprecedented levels of development, and its expansion has not yet slowed. This rapid rise of AI is enabled by the success of machine learning algorithms which can now be trained with huge dataset and large-scale computing. Overcoming the pre-programmed logic, self- adapting algorithms are being employed in a variety of situations for the first time in human history: industrial operations, data analysis, and a wide range of daily activities. In academic literature, a lot of effort has been made in the study the possible AI applications in the public sector. However, this analysis is almost made from a technical point of view, without providing evidence of how different countries are developing these solutions. Moreover, it is not clear how much states are investing in the development of these projects and in the enabling factors behind them, i.e., the presence of technical infrastructures, the access to high quality datasets, the availability of skilled human resources. Thus, there is a lack of literature concerning an assessment of the investments that governments have planned and the efforts that different European countries are currently doing. Moving from these gaps, the research question and the objective of the study are defined. Therefore, the aim of the thesis is to develop an index to assess the level of AI adoption within European countries. A large set of indicators are collected from existing indexes (such as the AI Watch Index by the European Commission, the Government AI Readiness Index by Oxford Insights, and the Global AI Index by Tortoise Media) to build a new index, with a solid and comprehensive structure. As a result, the AI Maturity Index (AIMI) is developed to measure the readiness of EU Member States in implementing AI solutions, adopting a policy making orientation. Indeed, in each of the four pillars of the index (Public Administration, Enterprises, Human Capital, Infrastructure) indicators are classified into enabling factors and achieved results. This research provides relevant theoretical and managerial implications for the academic literature and for practitioners. Limitations and perspective for future research are then provided.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/197108