The growing interest in Human Activity Recognition (HAR) systems in logistics reflects broader trends in automation and intelligent process management. While HAR technologies have proven effective in domains such as healthcare and physical activity monitoring, their application in logistics remains limited and raises substantial implementation challenges. This paper explores whether HAR represents a breakthrough opportunity or an overestimated technological promise in logistics management. A review of literature reveals limited empirical research and a significant lack of reliable, annotated datasets tailored to logistic operations. Moreover, economic and organizational barriers—especially for SMEs—include high implementation costs, uncertain return on investment, concerns over data privacy, and limited system reliability in complex, real-world environments. The study presents the results of a quantitative survey conducted among 397 logistics-related companies across Poland. The analysis, based on Spearman correlation and Mann-Whitney U tests, indicates that the perception of HAR technology improves with company size and employee experience. Larger companies are more likely to use and invest in HAR, though they also acknowledge the cost-benefit imbalance. Simulations confirmed that awareness of HAR increases with enterprise size and respondent seniority. These findings highlight a key contradiction: while HAR offers significant theoretical benefits in logistics, its practical implementation is hindered by economic, ethical, and technical concerns. The paper concludes with recommendations for further research and policy-making, including the need for pilot programs, targeted funding, and development of logistics-specific HAR datasets.