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Secondary review demonstrates uneven productivity and cost benefits of narrow AI in small and medium enterprises, highlighting the need for digital readiness and security support.
This paper examines the conditional effects of narrow artificial intelligence on the economic performance of small and medium sized enterprises (SMEs) in the United States using secondary research and policy evidence. It argues that narrow AI tends to improve productivity, reduce operating costs, and support profitability by automating routine tasks, improving customer communication, and strengthening decision making. However, these benefits are not automatic. They depend on a firm’s financial capacity, workforce skills, digital readiness, and ability to manage privacy and cybersecurity risks. For many SMEs, adoption remains limited by implementation costs, knowledge, and concerns about data protection and regulational uncertainty. This paper concludes that narrow AI is most beneficial when it is carefully integrated into business operations with adequate training and security support, but without these conditions, effects are often uneven.
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Sameeksha Nair (2026) studied this question.
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