Automation in Rural Economy of Pakistan: Risks & Rewards

Automation, driven by artificial intelligence (AI), robotics, and machine learning, is transforming industries worldwide, redefining labor markets and economic productivity (Cugurullo, 2020). While urban economies have experienced the most visible impacts, through the rise of smart manufacturing, fintech, and service automation, the ripple effects of automation on rural economies remain less studied. In Pakistan, where approximately 62.7% of the population lives in rural areas and agriculture contributes 23% to the national GDP (PBS, 2023; World Bank, 2023), the implications of automation are profound and multifaceted.

Rural Pakistan’s economy is primarily dependent on low-skilled labor in agriculture, textile manufacturing, and informal services. As automation technologies begin to enter these sectors, through mechanized harvesting, AI-based crop monitoring, and automated logistics, there is a dual potential for disruption and progress. On the one hand, the adoption of advanced technologies can boost agricultural productivity, reduce waste, and improve supply chain efficiency. For example, precision agriculture using drones and sensors can help smallholder farmers monitor soil health and crop performance in real time, leading to yield increases of up to 20% (PARC, 2022). On the other hand, automation also threatens to displace unskilled laborers who rely on seasonal farm work or factory-based employment, exacerbating rural unemployment and income inequality.

This article examines how automation is expected to alter employment patterns, productivity levels, and structural dynamics in Pakistan’s rural economy. Through a review of global and local literature, and case studies from agri-tech startups the potential and the pitfalls of automation for rural communities are identified. The role of policy in mitigating risks, such as through reskilling programs, rural internet expansion, and inclusive digital literacy initiatives is also discussed. Ultimately, understanding and managing automation’s impact is crucial for shaping a resilient and equitable rural economy in Pakistan.

Automation in Agriculture and Rural Industry in Pakistan

Automation is reshaping the landscape of agriculture and rural industry in Pakistan, offering both transformative opportunities and serious challenges. With 37.4% of the workforce employed in agriculture (Labour Force Survey, 2023), the sector is witnessing rapid technological advancement. AI-powered irrigation systems are boosting crop yields by 20–30% (IFPRI, 2022), drones are enabling precise crop monitoring and reducing pesticide usage by 15% (FAO, 2023), and autonomous tractors are cutting labor costs by up to 40% (Punjab Agriculture Department, 2023). While these innovations enhance productivity, they also threaten to displace the over 50% of rural workers who rely on low-skilled farm labor. PIDE (2023) estimates that, without targeted reskilling initiatives, rural unemployment could rise by 12% by 2030 due to automation.

In rural manufacturing, particularly in textile, leather, and small-scale industries, automation is also a disruptive force. Although urban factories are adopting robotics and increasing productivity by 25% (SBP, 2023), rural small and medium enterprises (SMEs) face major barriers. Only 5% can afford AI tools (SMEDA, 2023), and digital literacy among rural workers stands at a low 18% (PITB, 2023). However, with the right support, automation could enhance competitiveness. The use of 3D printing in traditional crafts and automated stitching machines could significantly reduce production time and boost exports (Trade Development Authority, 2023; LCCI, 2023).

While an OECD (2023) study warns that 45% of rural jobs in Pakistan are at high risk of automation, it also notes the potential for new employment in areas like AI maintenance, data analytics, and agri-tech services (World Economic Forum, 2023). Yet, the urban-rural divide may widen as urban tech hubs receive the bulk of investment, leaving rural communities behind (Planning Commission, 2023). Women, who constitute 70% of the rural agricultural workforce, are especially vulnerable to job loss (UN Women, 2023). Still, IFAD (2023) highlights that, if made accessible, digital farming tools could raise rural incomes by 15%, signaling the potential for inclusive growth through carefully managed automation.

Job Market Shifts and Policy Gaps in Rural Automation

The rise of automation is set to redefine Pakistan’s rural job market, creating both high-risk vulnerabilities and new opportunities. Traditional roles such as farm laborers and manual factory workers are among the most threatened by automation. These occupations, which currently form the backbone of rural employment, are increasingly being replaced by machines, sensors, and AI-powered systems. However, automation also introduces emerging job categories such as drone operators, AI technicians, and precision agriculture specialists. These roles demand new skill sets, often unavailable in rural settings without structured training programs. According to the Pakistan Institute of Development Economics (PIDE, 2023), automation has the potential to contribute an additional $3.5 billion to the national GDP by 2030. Yet, the International Labour Organization (ILO, 2023) warns that without comprehensive reskilling programs, over 5 million low-skilled jobs could be lost in the same timeframe.

A key challenge lies in the absence of a coordinated national automation strategy tailored to rural contexts. Current policies lack a focused framework to guide technological transition in agriculture and cottage industries. Furthermore, weak digital infrastructure continues to hamper innovation, only 22% of rural Pakistan has access to 4G internet (PTA, 2023), limiting adoption of digital tools essential for automation. To address these gaps, several policy interventions are necessary. Collaborative reskilling initiatives between the government and NAVTTC should equip rural workers with competencies in AI, robotics, and digital literacy. Tax incentives for rural SMEs adopting automation can ease financial barriers and encourage innovation. Establishing rural tech hubs at district levels would provide hands-on training and knowledge exchange platforms. Moreover, gender-inclusive policies must be prioritized, offering targeted programs to equip rural women, who form a majority of the agricultural workforce, with skills in agri-tech and digital systems. Strategic implementation of these recommendations can ensure a just and inclusive automation transition in rural Pakistan.

Conclusion

The integration of automation into Pakistan’s rural economy presents both unprecedented opportunities and serious risks. While AI, robotics, and precision farming technologies promise to boost agricultural yields, reduce costs, and modernize rural industries, the potential for widespread job displacement, particularly among low-skilled workers and women, raises critical socioeconomic concerns. With 45% of rural jobs at high risk of automation and only 22% of rural areas having reliable 4G access, a clear digital divide threatens to exacerbate inequality and marginalization.

Nonetheless, automation does not have to be a threat. If strategically managed, it can act as a catalyst for inclusive growth. Reskilling programs, digital infrastructure development, and targeted support for women and SMEs can help ensure that rural community’s benefit from technological change rather than suffer from it. The creation of new job roles in AI maintenance, drone operations, and data analytics offers a viable path forward, provided rural workers are equipped with the necessary skills. Above all, a coordinated national policy tailored to rural realities is urgently needed to balance innovation with equity. With timely investment and inclusive planning, automation can become a driver of rural empowerment and long-term economic resilience in Pakistan.

References: Cugurullo; PBS; World Bank; IFPRI; OECD; PIDE; FAO; Labour Force Survey; Punjab Agriculture Department; PITB; SMEDA; Trade Development Authority; LCCI; World Economic Forum; Planning Commission; IFAD; SBP; PTA

Please note that the views expressed in this article are of the author and do not necessarily reflect the views or policies of any organization.

The writer is affiliated with the Institute of Agricultural and Resource Economics, University of Agriculture, Faisalabad, Pakistan.

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