In the rapidly evolving landscape of financial technology, a groundbreaking study has emerged that could reshape how economics students approach investment decisions, with potential ripple effects across the energy sector. Led by Maher Mohammad Sharrab from the Hashemite University in Jordan, the research delves into the influence of artificial intelligence (AI) on financial analysis and its subsequent impact on investment intentions, particularly among economics students.
The study, published in the journal ‘Heritage and Sustainable Development’ (translated to English as ‘التراث والتطور المستدام’), explores the mediating role of analytical self-efficacy in this process. Drawing on established theories like the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), Sharrab and his team developed a conceptual framework to understand how AI tools can enhance students’ confidence in their analytical abilities and, in turn, their willingness to invest.
Using data from 300 economics students collected through a structured questionnaire, the researchers employed structural equation modeling (SEM) and the Bootstrap method to analyze the relationships between AI usage, analytical self-efficacy, and investment intention. The findings were striking: AI usage had a significant and positive influence on both analytical self-efficacy and investment decision intention. Moreover, analytical self-efficacy was found to partially mediate the relationship between AI usage and investment intention.
“This research highlights the transformative potential of AI in financial education,” said Sharrab. “By integrating AI tools into the curriculum, we can empower students with the skills and confidence needed to make informed investment decisions, ultimately benefiting the broader economy.”
The implications for the energy sector are particularly noteworthy. As the industry increasingly relies on data-driven decision-making, the next generation of professionals must be adept at leveraging AI technologies. “The energy sector is undergoing a digital transformation,” noted Sharrab. “Our findings suggest that by incorporating AI into educational programs, we can better prepare students to navigate this evolving landscape and drive innovation in the field.”
The study not only contributes to the academic discourse on AI adoption in higher education but also offers practical solutions for curriculum development and technology-oriented training. By fostering analytical self-efficacy through AI tools, educational institutions can enhance students’ readiness to invest and contribute to the energy sector’s growth and sustainability.
As the energy sector continues to evolve, the integration of AI in financial analysis and investment education will be crucial. This research by Sharrab and his team provides a roadmap for educators and industry professionals to harness the power of AI, ultimately shaping a more informed and confident generation of investors ready to tackle the challenges and opportunities of the future.