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Research Paper | Industrial Engineering | Volume 15 Issue 9, September 2026 | Pages: 1313 - 1315 | United States
Evaluating the Effect of AI-Assisted Tools on Engineering Team Productivity and Decision Quality
Abstract: The integration of artificial intelligence (AI) tools into engineering teams has rapidly shifted from an experimental curiosity to a mainstream operational reality. As organizations adopt AI-assisted platforms for coding, scheduling, risk assessment, and project decision-making, a critical question emerges: do these tools genuinely enhance team productivity and the quality of engineering decisions, or do they introduce new forms of dependency and risk? This paper conducts a conceptual evaluation of the effects of AI-assisted tools on engineering team performance, drawing on recent empirical studies and organizational behavior frameworks. It proposes a Human-AI Collaboration (HAC) model that distinguishes between individual-level output gains and team-level decision quality outcomes, argues that the net effect of AI adoption is highly context-dependent, and offers a set of managerial recommendations for engineering leaders seeking to deploy AI tools responsibly and effectively.
Keywords: Human-AI Collaboration, Engineering Management, AI Tools, Team Productivity, Decision Quality, Industry 4.0, Organizational Behavior
How to Cite?: Harsimran Kaur, "Evaluating the Effect of AI-Assisted Tools on Engineering Team Productivity and Decision Quality", Volume 15 Issue 9, September 2026, International Journal of Science and Research (IJSR), Pages: 1313-1315, https://www.ijsr.net/getabstract.php?paperid=SR26901083036, DOI: https://dx.doi.org/10.21275/SR26901083036