Journal of Economic Policy

VECTOR AI. ALGORITHMS, ENTERPRISE, SOCIETY

Introduction

by Stefano Manzocchi, Paolo Spagnoletti

Artificial intelligence: developments, opportunities and challenges

by Giuseppe F. Italian

How do machines learn?

by Luigi Laura

Geopolitics of artificial intelligence

by Alessandro Aresu

Adjusting artificial intelligence

by Giusella Finocchiaro

Artificial intelligence and productivity: conceptual framework, early evidence and future trajectories

by Francesco Filippucci, Cecilia Jona-Lasinio, Giuseppe Nicoletti

Generative artificial intelligence in small and medium-sized enterprises: empirical evidence in the Italian context

by Paolo Spagnoletti, Tiziano Volpentesta

The role of artificial intelligence as an organisational and strategic tool in smart cities

by Filippo Marchesani, Federica Ceci

Artificial intelligence and criminal compliance. Current scenarios and evolutionary perspectives

by Antonio Gullo, Rossella Sabia

AI for cybersecurity

by Simone Saverio Fildi, Maria Teresa Gonnella, Simone Guarino, Roberto Setola

Share on

Introduction

by Stefano Manzocchi, Paolo Spagnoletti

For Italy, the impact of artificial intelligence (AI) on industrial strategies and policies is crucial for the country's future competitiveness. To understand why, it is useful to refer to the benefits of AI for entrepreneurship. Indeed, it offers tools that amplify the ability to identify and exploit business opportunities.

Firstly, AI can detect hidden trends and patterns by analysing vast volumes of data and help discover new market opportunities more quickly and accurately. Secondly, AI facilitates collaboration between businesses and organisations, enabling a more efficient use of resources. Finally, advanced pattern recognition by AI in fields ranging from security to energy efficiency opens up new possibilities for entrepreneurs to anticipate emerging trends and proactively respond to potential threats or market changes. For instance, AI algorithms can help to accelerate the decarbonisation process by increasing the yield of plants using renewable energy sources.

This volume of the Journal of Economic Policy aims to offer an overview of the forces driving the 'artificial intelligence vector', providing entrepreneurs, analysts and policy makers with a lexicon of key vocabularies and some critical tools to understand and manage the challenges and opportunities related to this technological revolution. Through a multidisciplinary approach combining advanced theories and practical experience, the first part examines the technological evolutions of AI and its global implications, focusing on geopolitical tensions and current and future regulations. This section provides a broad theoretical framework, highlighting how AI influences economic and social contexts on an international scale.

The second part of the book focuses on the practical implementation of AI in businesses, with a particular focus on Italian small and medium-sized enterprises. This section investigates how AI is transforming internal processes and organisational dynamics, promising to significantly increase productivity and transform traditional business models. From applications in smart cities, to criminal compliance systems, to cybersecurity strategies, this technology is helping companies address risks and capitalise on the opportunities offered by digital.

magazine-vector-algorithms-enterprise-s-1_Manzocchi_Spagnoletti_RPE_2_2024.pdf

Artificial intelligence: developments, opportunities and challenges

by Giuseppe F. Italian

  • Recent prestigious awards in the field of science, such as the Nobel Prizes in Physics and Chemistry 2024, have further highlighted the disruptive role of artificial intelligence (AI) in science and society. AI is a sophisticated technology that offers enormous potential for solving complex problems, improving productivity and creating new services, with a profound and cross-cutting impact in various sectors, ranging from economics to finance, industry to healthcare, commerce to entertainment.
  • In this contribution, we will analyse recent developments in artificial intelligence, focusing in particular on generative AI. The introduction of artificial intelligence technologies is such a vast and complex topic that it touches on multiple aspects of our lives and our society, making knowledge of artificial intelligence a fundamental prerequisite for understanding it, using it to best effect, and helping to govern it.
  • Besides generating new opportunities in the economy, changing business models, creating new markets and influencing the work of the future, recent developments in AI raise sensitive ethical and legal issues, such as data protection, discrimination, liability, human control over machines, or intellectual property. AI also has significant social and political implications, from digital governance to social justice and democracies. Given the increasing complexity of artificial intelligence, staying abreast of technological advances by investing in innovation, research and skill enhancement seems of great strategic importance to address these challenges.

JEL Classification: D83, D81, C88.
Keywords: artificial intelligence, machine learning, deep learning, generative AI.

magazine-vector-algorithms-enterprise-s-2_Italian_RPE_2_2024.pdf

How do machines learn?

by Luigi Laura

  • In recent years, we have witnessed a number of successes by artificial intelligence (AI), including the very recent Nobel Prize in Chemistry awarded for developing an AI that can predict the structure of proteins. Most of these successes are actually attributable to so-called machine learning systems, i.e. systems that learn from data.
  • In this contribution we present, privileging basic ideas at the expense of implementation details, how these systems work and, in particular, how 'deep' neural networks (deep learning), which are the ingredient behind the most successful systems, work.
  • We will see that there are three fundamental factors behind these deep learning systems: data from which to learn, a great deal of computing power to enable the training process and, finally, the existence of fast algorithms to guide the training.
JEL Classification: C45, C61, C63.
Keywords: algorithms, artificial intelligence, machine learning, neural networks, deep learning.
magazine-vector-algorithms-enterprise-s-3_Laura_RPE_2_2024.pdf

Geopolitics of artificial intelligence

by Alessandro Aresu

  • Artificial intelligence has generated, especially since the end of 2022, a very significant investment cycle, led by large US technology companies, within an ecosystem where NVIDIA's centrality emerges.
  • On an economic and political level, what we now call 'artificial intelligence' is an evolution of the digitisation processes of the world, based on the increasing precision and specialisation of the semiconductor industry. As the central location of the artificial intelligence ecosystem is the data centre, this is accompanied by an increasing emphasis on infrastructure and energy capacity, on which the various companies and political players compete.
  • The political aspect of artificial intelligence is intertwined with the competition between the United States and China, which has defined the global arrangements of the last decade and the changing relationship between states and markets on the basis of national security, according to the logic of political capitalism.
JEL Classification: F01, F02.
Keywords: artificial intelligence, semiconductors, political capitalism, data centre, manufacturing, USA, China.
magazine-vector-algorithms-enterprise-s-4_Aresu_RPE_2_2024.pdf

Adjusting artificial intelligence

by Giusella Finocchiaro

  • The three regions of the world that currently play a predominant role in the artificial intelligence scenario, Europe, the United States and China, have adopted different regulatory approaches.
  • In the geopolitical context, the European approach is characterised by the intention to assert European regulatory competence beyond the territory of the Union: as the President of the European Commission, von der Leyen, declared in his State of the Union address in 2020, Europe's digital sovereignty is to be asserted.
  • It is certainly appreciable that the European Union has wondered about the problems posed by artificial intelligence and has tried to intervene. However, some criticism of the regulatory choices made in the AI Act is unavoidable.

JEL Classification: O33, O38, K24.
Keywords: AI regulation, geopolitical context, AI Act, risk-based regulatory models.

magazine-vector-algorithms-enterprise-s-5_Finocchiaro_RPE_2_2024.pdf

Artificial intelligence and productivity: conceptual framework, early evidence and future trajectories

by Francesco Filippucci, Cecilia Jona-Lasinio, Giuseppe Nicoletti

  • This paper explores the economic implications of artificial intelligence (AI), focusing on its potential as a new general purpose technology (TUG) capable of significantly influencing the labour market, productivity and growth. It emphasises its role in the production system and its peculiarities compared to previous TUGs, most notably its ability to learn and self-improve, which could accelerate innovation in various sectors.
  • The analysis is based on an extensive review of theoretical and empirical research and points to a positive effect of AI on growth through its impact on labour productivity. However, its quantification is uncertain and depends on a set of critical factors that may increase or decrease its magnitude.
  • The main critical issues include the speed and extent of the spread of AI in the economy, the extent to which AI will serve as a substitute or complement to human tasks, and the intensity and speed of the resource reallocation mechanisms triggered by the new technology.
  • By addressing some of these critical issues, public policies can help determine the long-term impact of AI on growth.

JEL Classification: O4, D4, L8, O15.
Keywords: artificial intelligence, growth, productivity, labour.

magazine-vector-ia-algorithms-enterprise-s-6_Filippucci_Jona-Lasinio_Nicoletti_RPE_2_2024.pdf

Generative artificial intelligence in small and medium-sized enterprises: empirical evidence in the Italian context

by Paolo Spagnoletti, Tiziano Volpentesta

  • The use of generative artificial intelligence (AI) solutions in enterprises promises significant productivity gains and can bring about significant changes in work processes and practices.
  • The ease of access to generative AI solutions can also benefit small and medium-sized enterprises (SMEs) by overcoming the difficulties associated with the scarcity of resources and data.
  • However, as this is a recent and evolving phenomenon, it is not yet clear what the possible ways of use, areas of application and consequent organisational impacts on SMEs are.
  • In this study we introduce a framework that identifies three adoption strategies, each characterised by infrastructural and governance choices aimed at mitigating emerging risks and generating value for firms. The framework, based on empirical evidence gathered in the Italian context, allows entrepreneurs, managers and institutional decision-makers to orient themselves in the implementation of generative AI solutions.
JEL Classification: O33, M15.
Keywords: generative artificial intelligence, small and medium-sized enterprises (SMEs), strategic framework, generative AI in SMEs, digital innovation in SMEs, digital transformation in SMEs.
magazine-vector-ia-algorithms-enterprise-s-7_Spagnoletti_Volpentesta_RPE_2_2024.pdf

The role of artificial intelligence as an organisational and strategic tool in smart cities

by Filippo Marchesani, Federica Ceci

  • This study examines the potential of artificial intelligence (AI) technologies in supporting data-driven decision-making processes for efficient urban management and in integrating citizens into digital transformation through tools such as municipal AI-BOTs. Starting from a qualitative analysis based on interviews with public managers, the research highlights how local governments perceive AI as a key resource for service optimisation, while acknowledging current structural limitations. The results show that collaboration between public authorities and local businesses, facilitated by distributed data governance, could bridge the existing technology gap and increase the effect of digitisation processes on the urban fabric. This article makes a contribution to the academic debate on smart cities, proposing a strategic vision for the implementation of AI in current urban dynamics.

JEL Classification: H50, O18, D73.
Keywords: smart cities, artificial intelligence, public administration.

magazine-vector-algorithms-enterprise-s-8_Marchesani_Federica_RPE_2_2024.pdf

Artificial intelligence and criminal compliance. Current scenarios and evolutionary perspectives

by Antonio Gullo, Rossella Sabia

  • New technologies represent a particularly promising horizon for corporate compliance, including that peculiar sector aimed at crime prevention within organisations. The aim of the contribution is to conduct a reflection on the state of the art of digital criminal compliance, firstly by examining some applications of interest - such as AI for data analytics and blockchain technology - and then proceeding to an assessment of the impact of such innovations on the delicate terrain of the criminal liability of entities under Legislative Decree no. 231/2001, most recently also in the light of the European Artificial Intelligence Regulation. In the concluding part, a comparative look is taken at the recent innovations related to the inclusion of technological risks in the US Department of Justice's guidelines on the assessment of compliance programmes.

JEL Classification: K14, K24, K42.
Keywords: digital criminal compliance, corporate criminal liability, organisational models, Legislative Decree No. 231/2001, artificial intelligence, AI Act.

magazine-vector-ia-algorithms-enterprise-s-9_Gullo_Sabia_RPE_2_2024.pdf

AI for cybersecurity

by Simone Saverio Fildi, Maria Teresa Gonnella, Simone Guarino, Roberto Setola

  • As also highlighted by Legislative Decree 138/2024, which transposes European Directive 2022/2555 (known as NIS2) into Italian law, the cyber threat is constantly increasing and requires specific initiatives to be taken by all those economic entities that can be classified as medium-sized or large companies operating in one of the 17 sectors listed in the regulation.
  • These threats are linked both to the inescapable presence of vulnerabilities in software, but above all to the inadequate cultural preparation of human subjects, be they operators or end users, whose erroneous behaviour is at the root of the vast majority of cyber incidents. These aspects are exploited by cyber criminals, who have organisational models and action tools that are largely based on the use of artificial intelligence tools.
  • In this context, the protection of operational technologies (OTs), i.e. those digital systems used to monitor and control production processes, plays a primary role, given the possibility that a cyber event perpetrated against them can turn into a kinetic event with significant consequences on the physical integrity of machinery, the production capacity of companies, the environment, and even the health of workers and citizens.
  • In order to limit risks, it is necessary to develop solutions capable of identifying possible anomalous situations at an early stage. This should be framed within the framework of emerging risk management, exploiting the potential of AI and the availability of an increasing amount of information from the field that can be properly analysed by exploiting the Digital Twin paradigm.
  • The pervasiveness of the threat requires the development of adequate incident management capabilities as a tool to mitigate damage and promote a rapid return to normality. In this vein is the PACY project, which aims to develop a platform that, by exploiting the features of generative AI, is able to help SMEs in managing cybersecurity incidents.
JEL Classification: D81, K24.
Keywords: Digital Twin, critical infrastructure, Bayesian network, dynamic risk assesment, emerging risks.
magazine-vector-algorithms-enterprise-s-10_Fildi_Gonnella_Guarino_Setola_RPE_2_2024.pdf

Other Contents

All CSC analyses

Join the largest business community in Italy.

Join Confindustria

Highlighted topics

All Themes

Environment and Ecological Transition

Explore

International

Explore

Europe

Explore

Digital transition

Explore

Energy

Explore

Fisco

Explore
Our Platform