Mikko Ranta
Generative AI is currently at the forefront of a transformative shift in the way we work. While some perceive these changes as threats, others view them as unprecedented opportunities. However, there is a consensus that significant changes lie ahead.
Historically, technological innovation has consistently reshaped the nature of work. What distinguishes the current revolution is the scope of jobs potentially affected by these advancements, particularly within the white-collar workforce. Traditionally, automation has predominantly impacted blue-collar jobs, and the advent of machinery and robotics has drastically reduced the need for manual labor in factories. Today, however, generative AI brings forth the possibility of automating many tasks traditionally performed in knowledge-based professions.
Despite these concerns, generative AI also presents considerable opportunities to democratize the workplace. Drawing a parallel with the ubiquity of smartphones, which have made sophisticated technology accessible to a global audience regardless of socioeconomic status, generative AI has the potential to provide universal access to advanced cognitive assistance. Imagine a future where every individual can afford a personal AI assistant capable of managing everyday tasks—an assistant that, until now, only the wealthiest could acquire through human hiring.
This democratizing effect extends beyond individuals to small and medium-sized enterprises (SMEs). Traditionally, SMEs have faced limitations in accessing specialized knowledge and resources, often due to financial constraints. However, with the advancements in generative AI, SMEs can harness the power of AI consultants to navigate complex tasks such as regulatory compliance, mergers and acquisitions, and financial management. I anticipate that within the next two years, generative AI will empower SMEs with capabilities that bring them closer to competing with larger corporations. This technological democratization could be particularly transformative for SMEs in smaller economies, such as Finland, potentially catalyzing innovation and economic growth.
As an AI researcher, my work has focused on the integration of machine learning in accounting, as detailed in my article, ”Machine Learning in Management Accounting Research: Literature Review and Pathways for the Future,” published in the European Accounting Review. My research explores the intersection of AI and accounting, offering insights into how these technologies can reshape the field. My recent research has also explored the potential of generative AI-based legal advisors for individuals and companies. Recently, I had the honor of being invited as a panelist at the European Accounting Association Congress to discuss ”AI in Accounting Research,” where we explored the profound implications of AI advancements in this domain.
In conclusion, while generative AI undoubtedly presents challenges, it also offers remarkable opportunities to democratize access to powerful tools and resources, boosting individual empowerment and organizational growth. As we continue to explore the potential of AI, it is crucial to approach these changes with a balanced perspective, recognizing both the potential disruptions and the transformative possibilities that lie ahead.
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Mikko Ranta is an Associate Professor of Accounting at the School of Accounting and Finance at the University of Vaasa and a member of the Digital Economy research platform. His research focuses on the integration of data analytics, FinTech, and machine learning into the accounting profession. Mikko has published extensively in top-tier academic journals and his work has gained international recognition, being featured in The Financial Times, The Wall Street Journal, and Harvard Business Manager. Currently, he is leading innovative projects such as ”Harmonizing Profit and Planet: A Geo-Informed Machine Learning for Environmental Accounting” and ”Spacecasting: Economic and ESG Assessment of Companies Using Satellite Data.” In addition to his research, Mikko teaches advanced courses on data analytics and machine learning methods for accounting and finance students.
