Human-Artificial Intelligence Collaboration in Knowledge Work

A Systematic Literature Review of Productivity, Creativity, and Decision

Bibliographic Data

ID19490805
AuthorsPritam Kumar (0000-0003-2871-8623, Assumption University), Amarjeet Singh Mastana (0000-0002-1777-6492, Stamford International University), Sandeep Khanijou (Assumption University), Rattiporn Luanrattana (Assumption University)
Year2026
Volume7
Issue10s
Publication date2026-05-19
Open AccessYes
TypeARTICLE
VenueShodhKosh: Journal of Visual and Performing Arts (JOURNAL)
Journal identifiersISSN: 2582-7472 • E-ISSN: 2582-7472
PublisherGranthaalayah Publications and Printers (PUBLISHER • IN)
DOI10.29121/shodhkosh.v7.i10s.2026.7927
OpenAlexW7161639550
LanguageEN
References cited39

Human–Artificial intelligence (AI) is becoming increasingly prevalent in a variety of knowledge work fields, such as accounting, finance, logistics, marketing, manufacturing, and management. While AI is commonly utilized to enhance productivity, creativity, and decision-making in these fields, the impact of collaboration between humans and AI agents on these fields remains fragmented and incomplete. This systematic literature review synthesizes the available research on the effects of human-AI collaboration on productivity, creativity, and decision quality. The search strategy identified all the peer-reviewed journal articles, conference papers, and book chapters published in the English language between 2017 and 2025 that discuss the topic of human involvement in AI-assisted knowledge work. Studies that did not involve human participation in the AI system’s functions were excluded from the review. The systematic literature review was performed through searching databases like Google Scholar, Scopus, and Web of Science for terms related to the topic of AI and human collaboration. Articles were searched using Boolean operators and specific criteria to include or exclude certain types of articles in the search. Articles were screened according to their titles, abstracts, and full texts to determine which would be included in the literature review. Data from those articles was extracted and analyzed to determine the main findings of the research in the field. The database search identified 86 records, of which 10 were duplicates. Screening of the titles and abstracts of the remaining 76 studies led to the inclusion of 42 full-text articles. Of these articles, 38 met the inclusion criteria and were incorporated into the literature review. The studies found that collaboration between humans and AI generally increases creativity and productivity if the AI is augmenting human effort rather than replacing it. Furthermore, decisions made with AI are found to have higher quality when the AI system can provide humans with explanations of its decisions and decisions are made that align with human judgement. However, outcomes vary depending upon the type of task that is to be performed, the setting in which the work is to be done, and the level of expertise of those who perform the tasks. Studies discuss themes including explainability and trust, task and technology fit, human autonomy, ethics and accountability, workforce adaptation, and the need for appropriate evaluation frameworks. Human–AI has the potential to aid humans in knowledge work processes. However, to reach this potential, AIs must be carefully designed to work alongside humans and to allow for human oversight of their actions. Furthermore, more research needs to be conducted in this area to establish appropriate standards for human-AI collaboration

Decision aids · English language · Systematic review · Web of science · AI in Service Interactions · Ethics and Social Impacts of AI · Personal Information Management and User Behavior

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