Abstract

The advent of generative artificial intelligence (AI) marks a pivotal moment in the reconfiguration of economic and social structures. As we observe the early stages of this technological revolution, the potential for generative AI to reshape the dynamics of competitive markets is becoming increasingly apparent. This study proposes a comprehensive exploration of how generative AI is influencing social patterns and transforming the competitive business terrain through its dual capabilities: augmentation and automation.

In March 2023, Geoffrey Hinton, one of the godfathers of Generative AI, when asked what careers younger people should be planning for, gave a one-word answer: plumbing. Hinton's remark hints at the underlying tectonic shifts in labor markets that generative AI could precipitate. This paper endeavors to scrutinize the breadth of generative AI's societal repercussions, particularly in the realms of innovation, job market, and market dynamics.

This paper aims to delve into this impact through an analysis of the dual and mix effects of generative A.I. on tasks: automation, and augmentation, on both output and the job market, considering market elasticities and the creation of novel tasks and expertise.

So far augmentation is the most remarkable effect of generative AI. In fact, we can observe a multiplicative effect resulting on 30%-75% increase in productivity in areas such as programming, together with the creation of new jobs and expertise, such as prompt engineer. There are however many trials directed to automation that promise higher multipliers and transformative effects.

The job market's response to generative AI remains a complex phenomenon. In sectors like software development, where AI tools are widely adopted, there are emergent trends that may offer predictive insights for broader occupational categories. Our research aims to extrapolate these trends to forecast future economic contours.

We anticipate a discourse on the competitive landscapes emerging from the integration of generative AI, emphasizing the potential emergence of power-law distributions within markets. This metamorphosis, driven by AI adoption, poses critical questions about market consolidation and the balance of economic power.

By presenting this analytical framework, our work aspires to shed light on what could be the most profound technological disruption in recent history. It is an exploration of how generative AI is not merely a tool for economic advancement but a catalyst for a comprehensive reimagining of our social and competitive fabric. Through this lens, we aim to contribute to a nuanced understanding of generative AI's role in shaping the future of work, competitiveness, and societal evolution.

Abstract

In recent years, advancements in artificial intelligence, particularly in large language models (LLMs), have revolutionised multiple sectors, distinguished by their ability to process and generate text with high coherence and relevance. However, their implementation has predominantly been focused on large corporations due to cost barriers and technological complexity. This article examines the current state and potential of LLMs oriented towards small and medium-sized enterprises (SMEs), offering insights on how these models can be integrated into SMEs to enhance efficiency, innovation, and decision-making.

Focusing on the description of LLMs and recent advancements that reduce their cost and implementation complexity, use cases for SMEs are explored, demonstrating how adopting LLMs can significantly reduce the time and resources these organisations invest.

The article concludes with practical recommendations for SMEs adopting LLM technologies, emphasising the importance of a strategic and conscious approach. This work provides a comprehensive view of the value that LLMs can offer SMEs. It establishes a framework for future research and developments, encouraging SMEs to participate actively in AI-driven digital transformation.