Recent technological advances in big data, machine learning, and robotics, have begun to have a negative influence on existing employment opportunities for human beings. Numerous studies have demonstrated a worrisome decline in low- and medium-income employment resulting from the replacement of human workforce with machines. A seminal study by Frey and Osborne in 2013 predicted that 47% of the 702 examined occupations in the United States faced a high risk of decreased employment rate within the next 10–25 years as a result of computerization. Despite the seemingly dystopian future foreshadowed by these numbers, the wholesale replacement of labor by machines will most likely not become a reality in the foreseeable future for an array of reasons, including the creativity required by many occupations and interventions by governments.
However, despite the barriers, computerization is likely to have a significant effect on the current market. In this paper, we aim to track the relative quantities of jobs that are either susceptible or non-susceptible to computerization in the future, by developing and utilizing an analytical model using Markov chains. Various simulations performed using this model demonstrate the importance of intervention policies, such as improved technical education of the public, in controlling the rate of computerization. Moreover, the simulations identify the probable creation of new jobs that would facilitate new human employment. Although radical changes in technology and economy await humanity, adequate preparation will help to facilitate a smoother transition into the age of computers.