American International Journal of Research and Innovation

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Artificial Intelligence and Its Influence on Professional Productivity

Author(s) Kasper Edwards
Country United States
Abstract Generative artificial intelligence has introduced a new form of workplace assistance capable of producing, reorganizing, summarizing, translating, and evaluating professional content through natural-language interaction. Its influence on productivity differs from that of conventional automation because it can support cognitive and communicative tasks previously regarded as dependent on human expertise. This study develops a conceptual framework for examining how generative artificial intelligence may affect professional productivity across writing, information synthesis, analytical preparation, communication, and decision-support activities. A simulation-based methodology compares three work configurations: unaided professional work, basic generative-AI assistance, and governed human–AI collaboration. Productivity is evaluated through task-completion time, output quality, revision burden, knowledge accessibility, and decision preparedness.
The simulated results indicate that governed human–AI collaboration could reduce average task-completion time from 100 to 61 minutes while increasing the composite output-quality score from 72.4 to 89.1. However, productivity benefits decline when generated outputs are accepted without verification or when professionals lack sufficient domain knowledge to identify inaccuracies, unsupported statements, confidentiality risks, and contextual errors. The study argues that generative AI should be understood as a capability-amplifying technology rather than an autonomous substitute for professional expertise. Its sustainable contribution depends on task suitability, prompt clarity, human validation, information governance, ethical accountability, and organizational learning. The proposed Human–Generative AI Productivity Framework offers a structured basis for future empirical investigation and responsible workplace implementation.
Keywords generative artificial intelligence; professional productivity; human–AI collaboration; knowledge work; workplace automation; language models; responsible AI; digital transformation
Field Engineering
Published In Volume 1, Issue 1, January-February 2019
Published On 2019-01-29
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