Assessing impact of strategic investments on development of sustainable artificial intelligence dynamics

• Novel Application of SIR Model: This study uniquely applies a modified Susceptible-Infected-Recovered (SIR) model to analyze the strategic investment impacts on AI technological breakthroughs, providing a fresh perspective on technology development dynamics. • Distinct Investment Dimensions: The research differentiates between investments in technology development. • Dynamic Investment Strategy for Sustainable AI Development: The study proposes a dynamic, responsive investment approach that adapts to the evolving AI market landscape, emphasizing its critical role in balancing technological progress with environmental sustainability and social equity. This research employs a modified Susceptible-Infected-Recovered (SIR) model to explore the strategic investment impacts on the frequency of significant AI technological breakthroughs and their implications for sustainable development. The study quantitatively assesses the differential effects of investments in technology development (v1) versus technology spreading (v2). Our results show that v1 investments, which concentrate on the creation and improvement of new AI technologies, lead to a more frequent occurrence of breakthroughs, suggesting that early, substantial investments accelerate technological advancements. However, these investments must be balanced with considerations of environmental impact and social equity to ensure long-term sustainability. Conversely, v2 investments, which promote the widespread adoption and diffusion of AI technologies, demonstrate a more gradual impact on breakthrough frequency, with no apparent saturation point, suggesting a vast untapped market potential for technology spreading. Such investments aid in closing the digital divide and fostering inclusive growth, thereby supporting the achievement of the UN's Sustainable Development Goals (SDGs). The balanced investment scenario reveals synergistic potential, although it does not reach the efficiency of concentrated investments in development. The study highlights the need for strategic balancing of investments and suggests that a dynamic, responsive investment approach is critical as the AI market evolves. This approach offers a novel framework for understanding the complex dynamics of AI technology development and market adoption, with implications for policymakers and industry leaders in strategizing future AI development and diffusion to promote economic and social sustainability.