Evaluating the Influence of AI on Market Values in Finance: Distinguishing Between Authentic Growth and Speculative Hype

Abstract

This article ventures into the intricate realm where the distinctions between authentic growth and speculative bubbles from impact of AI (Miller, 2003), celebrated and critiqued as a buzzword, emerges as a transformative element reshaping entire industries, workflows, and fundamentally altering market valuations (Perri, 2023). The promise of efficiency, innovation, and competitive superiority attributed to AI's integration into business models beckons a deeper investigation into its potential to redefine the competitive landscape. However, this promising horizon is not without its perils and scrutiny. A predominant debate as we navigate up to the year 2023 revolves around whether the market's enthusiastic reception of AI capabilities signifies a realistic reassessment of potential based on tangible fundamentals or if it's a manifestation of speculative exuberance, detached from any solid grounding (Baltrusaitis, 2023). This exploration addresses some implications for investment strategies (GuoRong Hu*, Hui Liu , 2020), regulatory frameworks, and potentially influencing the direction of future technological advancements. It endeavors to dissect AI's multifaceted roles in contemporary business ecosystems, scrutinizing its impacts on corporate valuations and attempting to demarcate the fine line separating real growth from speculative froth. Through a detailed examination, this paper illuminates how AI technologies foster operational efficiencies, drive innovation, and unlock unprecedented insights, all the while carefully navigating the surrounding hype to assess overvaluation risks (Svetlova, 2022) and emerging pitfalls. The journey through the AI landscape reveals a spectrum of inspiring successes and cautionary tales, guiding the current nuanced discussion toward clarifying AI's impact on capital markets and corporate valuations understanding for investors, business leaders, and technology aficionados aiming to make informed decisions (Tania Babina , Anastassia Fedyk , Alex He, James Hodson, 2024).

Enhancing Whale Optimization Algorithm with Differential Evolution and Lévy Flight for Robot Path Planning

“…AI, ML, and Neural Networks (NNs) play pivotal roles in revolutionizing robot path planning. AI algorithms enable robots to navigate complex environments autonomously by leveraging advanced decision-making processes [17,18]. ML techniques, particularly reinforcement learning, empower robots to learn from their experiences and optimize path planning strategies over time [19][20][21].…”