How digital innovations are driving future economic growth. Exploring the role of technology in our society’s transformation in an interview with Carlo Alberto Carnevale-Maffè.
Our economy has transformed into a digital economy, and moreover, our democratic freedoms are now entrenched within servers.
Digitalization is a complex process that must be integrated in every part of our society to ensure consistency and real change.
To truly grasp the trends steering economic growth, a deep understanding of digital technology’s evolution is imperative, and the converse holds true as well.
Today we’re surfing with Carlo Alberto Carnevale-Maffè, Professor of Strategy at Bocconi University School of Management.
Which technological developments do you envision exerting the greatest influence on global economic patterns in the forthcoming decade?
I foresee four principal dynamics at play. The first is the Life Sciences domain, where I anticipate bioinformatics and proteomics will be at the forefront — the convergence of software and biology that came to prominence with mRNA technology’s crucial role in the COVID vaccine. This breakthrough foretells a transformation in the interplay among software, mathematical models, human physiology, and molecular structures. At the heart of the Life Sciences revolution lies an unprecedented capacity for model simulation enabled by today’s advanced computational power, representing a compelling dynamic. Particularly because, with an aging worldwide population, the Western economic landscape must innovate beyond traditional healthcare paradigms. The substantial portion of healthcare expenditures susceptible to this shift measures in the trillions of dollars.
The next significant vector is found in Automation and Robotics—industries that exert a profound influence on manufacturing processes in conjunction with materials science. As we reach the limits of current material capabilities, innovations in this domain become critical. Anticipated advancements in chemical engineering, energized by intelligent design and software-driven molecular construction, promise to chart new territories. Equivalent progress in the inorganic chemistry domain is poised to mirror the breakthroughs we’ve seen in biological fields.
The third pivotal trend revolutionizes the concept of work as we know it, introducing a new era for white-collar professionals. Four decades ago, having a computer on every desk epitomized Microsoft’s vision for the future. Today, that vision has evolved dramatically towards a more symbiotic relationship between humans and technology, where the goal is for every individual in the service industry to work alongside an artificial intelligence (AI) agent. However, this isn’t just any AI—it’s an AI driven by objectives. This represents a significant departure from the stochastic nature of current generative models, which, despite their ability to generate data, lack a clear direction or objective. Conversely, objective-driven AI is precisely that—focused on achieving specific outcomes. This means beginning with a defined goal and subsequently crafting a path to achieve it, fundamentally inverting the traditional AI process that starts with learning before generating.
The fourth emerging trend underscores the critical domain of energy in all its facets—generation, distribution, and storage. In this arena, digital technology has the potential to catalyze a seismic shift. Our current utilization of energy operates on an analog basis, a method ripe for transformation. By weaving AI into the fabric of energy’s lifecycle, from production and distribution to storage, we stand on the brink of drastically enhancing the system’s efficiency. This application of AI not only promises to innovate how we harness and utilize energy but signals a broader move towards integrating intelligent solutions across sectors, heralding unprecedented levels of efficiency and sustainability in our economy.
What do you consider the most significant macroeconomic challenges arising from the digitalization and automation of advanced economies?
In the ever-evolving landscape of advanced economies, digitalization and automation wave bring forth many macroeconomic challenges, chief among them being the intricate dance of managing currency in a digital age. The advent of cryptocurrencies has cast a stark light on the inefficiencies — and, if we’re to speak candidly, the outright mismanagement — of currency by the titans of central banking. For over a decade, these entities have manipulated the levers of monetary policy, distorted the marketplace and fueled an unprecedented inflationary surge, the likes of which we’ve not seen in four decades, wreaking havoc across global economies.
The most pressing macroeconomic imperative now is to forge a harmonious relationship between the traditional use of currency and the principles of central banking, adopting a framework that eschews the unpredictable and often arbitrary nature of past policies. The rise of Central Bank Digital Currencies (CBDCs) — such as digital iterations of the dollar or euro — signals a progressive move towards institutionalizing responses to the challenges posed by digital currencies, effectively bridging the divide between traditional and cyber economies.
This evolution offers a glimpse into a future where the economic foundation is significantly more stable and governable than what we contend with today. It envisages a world economy with a rich mosaic of currencies, operating with a level of transparency far beyond our current capabilities, especially in the context of financial outcomes. Despite advancements, the financial sector remains plagued by massive arbitrage opportunities and inefficiencies that are indefensible in an era ripe with information symmetry. However, the introduction of Robotic Advisory services and sophisticated investment algorithms promises a pathway to surmounting these challenges, revolutionizing inefficiencies that currently stymie our financial systems.
Moreover, as we navigate this discourse on currency evolution and inflationary pressures, another significant challenge demands our attention: a fundamental shift in how we conceptualize productivity. The traditional measure of productivity, disproportionately tied to hours worked, is becoming obsolete. Instead, a task-oriented approach offers a more fitting metric for our digital and automated future, aligning productivity with a broader set of inputs rather than time spent, and heralding a more efficient and equitable economic model for the 21st century.
What do you anticipate will be the macroeconomic implications of the emergence of artificial intelligence (AI) and automation on the employment landscape?
The conversation around Artificial Intelligence in the workplace transcends merely its incorporation; it signifies a transformative shift in our whole organizational structure. AI causes a paradigm shift, dismantling the rigid, traditional workflows.
Employment of conventional enterprise software mandated adherence to predefined and structured procedures. In stark contrast, the advent of dialogic AI ushers in an era where we transition from a procedural to a conversational and interactive paradigm. This evolution means we move away from the follow the manual approach towards an ask me anything mentality. Rather than strictly following set procedures, we engage in a dynamic dialogue where humans inquire about the Next Best Action from AI, which doesn’t strictly conform to any preset workflow guidelines.
This technological revolution is redefining work organization rather than eliminating existing jobs. The notion that AI will usurp employment opportunities is fundamentally flawed. Contrarily, the challenge we face is not surplus labor but a shortage; there’s an abundance of work necessitating human intellect to harness AI’s full potential. The apprehension regarding technological displacement betrays a misunderstanding of AI’s augmentation role rather than its substitution of human intelligence.
In the context of business strategy, how can enterprises adapt to stay at the forefront in the rapidly evolving landscape of technological innovation?
The future belongs to enterprises capable of deconstructing and reconstructing themselves – I refer to these as highly reconfigurable or Lego companies. Such companies thrive on the agility of their ‘knowledge tokens,’ which are inherently adaptable and fluid. This adaptability is crucial, for a significant shortcoming within many organizations is their inertia: a deep-seated resistance to change characterized by the creation of comfort zones and, subsequently, inefficient monopolies. True competitiveness diverges from the static rent-seeking behaviors outlined by Michael Porter and goes beyond the perpetual innovation highlighted by Joseph Schumpeter. Instead, it manifests as a relentless recalibration of strategies and practices, a process where the past is not obliterated but is ingeniously reimagined and repurposed.
Enterprises, in this sense, start to mirror the essence of a language model. Like how systems like Gemini produce text that simulates meaning without embodying true intelligence, businesses must learn to navigate within the realm of “good enough” models. These models, though inherently imperfect, embrace the fluid imperfections of language models and must pivot swiftly to stay relevant.
How are the current waves of protectionism reshaping technological innovation and the international competitiveness of companies?
In today’s era, technological innovation — especially within the digital sphere — stands as the modern bastion of liberal democracies. The perimeters of our digital servers have become synonymous with the boundaries of our sovereignty. As the world gradually shifts away from the ideals of free trade and earnest cooperation amongst diverse global regions, largely due to a resurgence in authoritarian, autocratic, and sometimes even illicit governance, the implications of trade protectionism have emerged as a significant obstacle, resulting in the fragmentation, or balkanization, of technology. A prime example can be observed in the United States, where there’s an uptick in the impediments to technological trade. The internet, previously celebrated as a beacon of globalization and inherently based on its principles, is now experiencing a phase of pronounced fragmentation across various dimensions. This encompasses not only American protectionism, influenced by political and geopolitical considerations but also a form of regulatory protectionism prevalent in Europe. European nations are establishing technological barriers legislatively, considering the stringent regulations on Artificial Intelligence, data sovereignty, and the General Data Protection Regulation (GDPR) — the latter being a sanctioned form of personal data protectionism.
Protectionism unequivocally erodes value by escalating transaction costs, promoting opportunistic tendencies, and safeguarding domestic market monopolies.
The sphere of technology is markedly affected by these global dynamics, showing a decline in interoperability and a diminution in the benefits derived from economies of scale, which are crucial for the sustenance of the digital domain. Moreover, countries such as China and Russia enforce restrictions on major digital platforms – a restriction similarly observed in several Middle Eastern nations – leading to a stark segmentation of technology services and platforms, which stands as a significant constraint to global technological progress and integration.
Can technological innovation be a solution to the growing economic inequalities?
One must acknowledge that there are two vectors at play, one positive and the other negative. The negative aspect, as per the simulations conducted at Bocconi University, is that Artificial Intelligence (AI), for example, leads to a productivity acceleration that is proportional to the quantity of data available and the computing power accessible; these two components are predominantly found in the more developed and digitized countries. Furthermore, as the productivity boost induced by AI is exponential, it creates a diverging vector in relation to the issue of equality: AI in fact increases disparities and does so at an increasing speed because it more rapidly improves the wealthy, service-based economies where artificial intelligence is most effective.
However, AI also introduces a factor of convergence; we witness a spillover of productivity. Poorer countries, even without any investment, can reap the benefits of Artificial Intelligence at very low costs without having to develop any special infrastructure, simply because they can access technologies created by others. This phenomenon has marginal effects on productivity increases. To illustrate, even in Africa, people can use technologies such as Gemini, hence productivity grows in those nations as well.
How can we evaluate technology’s pivotal role in steering us toward a more sustainable economy and effectively responding to climate change?
It’s imperative to acknowledge that the challenge of sustainability is fundamentally a technological one, not merely a matter of cultural shift. At present, we are confined by inadequate technologies, remaining in a state of ignorance reminiscent of our ancestors who relied on burning coal and oil. Yet, the next decade holds promise for substantial advancements in our quest for sustainability, spanning the realms of energy, innovative materials, and notably, agriculture.
Though often overlooked, it’s agriculture that stands as one of the largest contributors to global pollution, even more so than the industrial sector. Globally, agricultural activities and food production contribute approximately 26% of total greenhouse gas emissions, mainly due to the use of chemical fertilizers, pesticides, and animal wastes. In the EU, agricultural greenhouse gas emissions are higher than those from industrial processes and product use.
The shift towards electric vehicles represents an irreversible transition away from combustion engines — a domain where the USA and Europe are trailing China by about a decade.
In contrast, the West maintains a competitive edge in agricultural innovations essential for feeding the world in novel ways. Yet, this progress risks stagnation due to self-inflicted obstacles, especially in Europe and Italy, where resistance to genetic research prevails.
Looking forward, the key to feeding the global population lies in adopting minimal impact technologies such as aquaculture, vertical farming, precision agriculture, and regenerative farming. The current dependency on animal proteins is untenable; the inefficiency of rearing and slaughtering billions of animals for human consumption, apart from being ethically questionable, is simply unsustainable. The scarcity of land and essential nutrients highlights the impracticality of this system in the long run.
What we need is an agriculture paradigm designed for zero emissions. Moreover, echoing Elon Musk’s foresight, space farming presents an upcoming frontier. As humanity progresses towards becoming an interplanetary species, mastering crop cultivation on planets like Mars or the Moon becomes not just visionary, but essential.
What are your thoughts on the regulation of tech behemoths, and what could be the ramifications of such regulations on the global economic landscape?
In Europe, an intriguing paradigm shift is underway: we implement regulations before the innovation takes root, favoring preemptive regulation (ex-ante) over reactive measures (ex-post), a strategy divergent from the American approach. This method has led to Europe missing nearly a quarter-century of innovation trends. Regulatory oversight is essential but should pivot on factual data for intervention rather than speculative hypotheses. Currently, Europe enforces a form of speculative regulation, presuming risks and consequently imposing restrictions on both companies and research endeavors. The AI Act exemplifies this approach.
Europe’s legislative environment operates on a principle where actions are prohibited unless explicitly permitted by regulations. This restrictive framework undeniably repels both human and financial capital from the region.
How do you perceive the macroeconomic risks posed by escalating cyber threats, and what strategies should governments and institutions employ to mitigate these risks?
The era of technological naivety must come to an end. The realm of technology is a battleground—not theoretically, but in a tangible and current sense. We continuously face systematic disruptions, encroachments on democracy, and privacy infringements via digital arenas.
Today, hackers compromise critical infrastructure in healthcare, transportation, and the banking sector, posing significant threats to public order.
This constitutes warfare—a low-intensity conflict, perhaps, but warfare, nonetheless. Consequently, adopting a wartime stance is imperative. Ignoring the reality of conflict is not feasible. I advocate for the declaration of a digital security conflict status, urging a collective, conscious response to the ongoing assaults. Without robust defense mechanisms, our democratic and economic liberties are at risk of dissolution.
The responsibilities of warfare cannot be exclusively relegated to engineers, just as cybersecurity cannot be solely managed by IT professionals. Such measures are insufficient.
In such a challenging landscape, the mantle of security must be shared by all—citizens, corporations, organizations, and governmental bodies alike.
Carlo Alberto Carnevale-Maffè, Professor of Strategy and Entrepreneurship at SDA Bocconi School of Management, has taught in international programs at GSB Columbia University, Stern School NYU, and Wharton School. He is an independent director of industrial and technology companies in Italy, the USA, and India, as well as venture capital funds and start-up studios for artificial intelligence. He is also a member of the editorial board of Harvard Business Review Italia, and an economic commentator for the Mediaset group and a journalist, contributing to various national and international newspapers and television stations such as Il Sole 24 Ore, The Economist, Time, Wall Street Journal, New York Times, Financial Times, Les Echos and CNBC International/Class CNBC.
