Evaluating the Economic Feasibility of Labor Replacement Through Robotics and Automation in Qatar

Background: Qatar’s economy relies heavily on low-skilled expatriate labor, especially in construction, logistics, and manufacturing. With the nation aiming for diversification under Vision 2030, the feasibility of substituting this labor with robotics and automation becomes an important policy question. This study assesses whether robotics can economically replace human labor in Qatar's context by accounting for sector readiness, displacement risks, and socio-economic implications. Cultural preferences, such as 68% resistance to robotic domestic workers, further complicate adoption dynamics. Materials and Methods: A capital-augmenting Cobb-Douglas production model was calibrated using Qatarspecific data including labor composition, wage structures, and robotics import data. Elasticity of substitution, robotics productivity coefficients, and TFP growth rates were derived from international benchmarks and adjusted to Qatar's regulatory environment. Three adoption scenarios (optimistic, status quo, and pessimistic) were simulated through 2030. Results: A 5% increase in robotics capital yields an annual 1.5% GDP gain under baseline conditions, with labor displacement of 3-5% in low-skilled sectors. Construction faces the highest displacement risk (4.8%), while cultural factors limit last-mile delivery automation to 32% adoption. Job creation in maintenance and AI oversight could offset 40% of losses by 2030. Conclusion: Robotics adoption in Qatar is economically viable but requires phased, sector-specific implementation. Policy safeguards must address cultural resistance, workforce reskilling (850+ technicians needed by 2027), and wage stabilization to ensure inclusive growth