Managing Cognitive Overload in Hybrid Teams
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V6I3P108Keywords:
Cognitive Load, Burnout, Artificial Intelligence, Hybrid WorkAbstract
Hybrid work environments have introduced new challenges around communication volume, information overload, and visibility pressure. Traditional responses such as adding more meetings, new collaboration tools, or redundant reporting, often worsen the very problems they aim to solve. This paper introduces two novel frameworks for addressing cognitive strain in distributed teams: Cognitive Load Budgeting, which treats attention as a finite and trackable resource, and AI Social Proxying, which allows team members to delegate low-stakes visibility and alignment tasks to intelligent agents. Together, these frameworks highlight the importance of reframing productivity around sustainable cognitive practices. They suggest a pathway toward reducing burnout and attrition while preserving alignment, accountability, and performance
Downloads
References
[1] Waizenegger, L., McKenna, B., Cai, W., & Bendz, T. (2020). An affordance perspective of team collaboration and enforced working from home during COVID-19. European Journal of Information Systems, 29(4), 429–442. https://doi.org/10.1080/0960085X.2020.1800417
[2] Microsoft WorkLab. (2023). 2023 Work Trend Index: Will AI Fix Work? Retrieved from https://www.microsoft.com/worklab
[3] McKinsey & Company. (2021). Reimagining the post-pandemic workforce. Retrieved from https://www.mckinsey.com
[4] Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4
[5] Bernstein, E., Blunden, H., Brodsky, A., Sohn, W., & Waber, B. (2020). The Implications of Working Without an Office. Harvard Business Review. https://hbr.org/2020/07/the-implications-of-working-without-an-office
