<p>This paper investigates how algorithmic management reshapes labour market frictions through the lens of Veetil (2021) pausing theory of unemployment. While digital platforms and automated systems promise greater efficiency by streamlining matching, monitoring, and pay-setting, they also generate new uncertainties that alter worker and firm behaviour. We conceptualize this dynamic as a non-linear relationship between algorithmic intensity and pausing behaviour. At low to moderate levels of algorithmic control, improved information flows and coordination reduce hesitation and enhance efficiency. However, at higher levels, algorithmic opacity, reputational lock-in, and reduced trust reintroduce hesitation, creating new frictions. The resulting U-shaped relationship between algorithmic control and market frictions reconciles the mixed empirical evidence on digital labour markets, where efficiency gains coexist with worker disengagement and instability. By integrating insights from classical search-and-matching theory, institutional economics, and digital labour research, this framework positions algorithmic management as both a friction-reducing and friction-generating institutional force. The analysis provides a theoretical foundation for understanding how technological acceleration and algorithmic uncertainty jointly shape the evolving dynamics of employment in the digital era.</p>