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Artificial Intelligence (AI) stands poised to reshape economies and societies profoundly over the next two decades, yet the nature and magnitude of its impact remain subjects of intense debate and considerable uncertainty. We review the diverse spectrum of projections concerning AI's consequences for labor markets, productivity, wages, and economic growth, and synthesize contrasting viewpoints, ranging from utopian visions of unprecedented prosperity to dystopian scenarios of widespread disruption and inequality. Central to this review is a critique of existing forecasting methodologies and models, highlighting their inherent limitations, particularly the prevalent lack of realistic, integrated scenarios capable of capturing complex feedback loops between technology, policy, and society. Drawing upon recent economic research, including analyses of automation risk exposure [1] and firm-level AI adoption [2], alongside considerations of accelerating AI capabilities [3], we identify significant gaps in current understanding. We argue that realizing AI's immense potential while mitigating substantial risks requires a more grounded, nuanced, and adaptive approach to analysis and policymaking than is currently common. We propose a path forward, emphasizing the need for improved modeling techniques, enhanced data collection, interdisciplinary collaboration, and a focus on adaptive governance strategies designed to steer AI development towards shared prosperity and enhanced human well-being across a range of plausible futures.