Impact Investing and AI: Advancing Developmental Goals through Data-Driven Investment Strategies - Benjamin Monday Ojonugwa; Oluwasanmi Segun Adanigbo; Bisi Ogunwale; Akoche Ochefu (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024)
The convergence of Impact Investing and Artificial Intelligence (AI) represents a promising frontier in advancing developmental goals through data-driven investment strategies. Impact investing, characterized by its intention to generate positive social and environmental impact alongside financial returns, has gained momentum as a powerful tool for addressing global challenges. By integrating AI technologies into investment decision-making processes, stakeholders can harness the potential of vast datasets to drive informed, targeted investments that maximize both impact and financial returns. This review explores the symbiotic relationship between impact investing and AI, emphasizing their collective potential to tackle pressing developmental issues such as poverty alleviation, environmental sustainability, and healthcare accessibility. Leveraging AI enables enhanced impact measurement and evaluation, enabling investors to quantify and optimize the social and environmental outcomes of their investments with greater precision. However, ethical considerations regarding algorithmic bias, data privacy, and transparency must be carefully navigated to ensure that AI-driven investment strategies remain aligned with ethical standards and societal values. Despite these challenges, the integration of AI into impact investing holds immense promise for catalyzing positive change on a global scale, driving innovation, and unlocking new opportunities for sustainable development. As stakeholders across the investment landscape increasingly recognize the potential of this synergy, collaborative efforts and cross-sector partnerships are poised to drive meaningful progress towards achieving developmental goals in a rapidly evolving world.