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THE IMPACT OF AUTOMATION ON AGRIBUSINESS JOBS
1. Introduction to Automation in Agribusiness
1.1 Definition and Overview
Agro-robotics also known as automation inn agribusiness is the application of robotics, artificial
intelligence, and other precision agriculture technologies to increase farming productivity, and
efficiency together with sustainable practices. These technologies are focused on the automation
of several activities within the agricultural sector inclusive of planting and the harvesting
process, assessment of crop health, and the use of the available resources (Gao & Lin, 2020). In
this case, by adopting these innovations, farmers would be in a position to approach the farming
activities in a more efficient way which would result to the use of appropriate resources and
minimal effects on the environment. For example, machine learning-based system can
recommend the best time and rate of water and nutrient application to crops (Johnson et al. ,
2021). Increased use of automation in sales and marketing, operations and human capital
management in agribusiness is a result of the increasing shortage of labor force, the need to
improve productivity and cut costs. In many different areas around the world, the issue of labor
and more specifically labor scarcity has become a major problem; this is in view of the relative
inefficiency of most farms when they rely solely on manual labor. This can however be handled
by automation because activities like planting, weeding, and even the act of harvesting may be
done by robots in a better an efficient way than employing many people (Smith & Jones, 2020).
Also, the organization of automated systems can work on a shift or simultaneously without
getting tired thus increasing efficiency and productivity. This paper supports the use of
technology in that when repetitive tasks are automated, the farmer is able to tend to matters of
key importance since most of their time is not wasted on physical work which is tiresome and
time-consuming (Smith & Jones, 2020). Technology helps farmers to gather data, also large
volumes and they can easily make decisions, for instance, on which crop should be planted next
time, whether pests are attacking plants, or the state of the soil. It is an effective strategy of
increasing the yields and quality of produce hence increasing food production to meet food
demands in the increasing world population. However, it opens up the issues like future jobless
for the old traditions of farmworkers and to manage those systems new skills are required (Chen
& Zhang, 2020). Inability to acquire such skills the new technology and Artificial Intelligence
demands a work force that is skilled in technology and data analysis which is scarce in rural
regions. This implies that a measure has to be taken in supporting education and training so that
employees are well-prepared for the changes so that they can embrace the new technologies to
their advantage as against being displaced.
1.2 Historical Context
The history of automation in agribusiness goes hand in hand with the mechanization of
agriculture in the early part of the 20th century that resulted in the use of tractors and other piece
of machinery which greatly eliminated the use of personnel (Ibid). This period was perhaps one
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of the most interesting in that it saw a change from labor intensive farming to that which
involved use of mechanized farming. For example, the tractor changed the profile of plowing,
planting and even the process of harvesting, because with it, farmers can work much faster,
without undue exhaustion. In the subsequent decades, the manifestation of the innovation process
remained relentless with technologies such as GPS tutorial equipment, automatic systems of
irrigation, and drone technology (Jenkins & Cooper, 2021). Technological advancement in the
last last two decades of the twentieth century however was the introduction of Global Positioning
System (GPS) that paved way for precision farming which has led to enhanced efficiency and
production. With the help of GPS, farmers could it was possible to plant crops with high
precision thus minimizing wastage especially on the seeds and space between crops. Such
systems as auto irrigation that was based on information pertaining to water availability in the
soil and the prevailing weather conditions aided in the optimization of the use of water and the
feeding of the crops with this important input. Incorporation of drone technology thus improved
the field of agricultural practices by offering direct aerial shots and also relevant data on the
crops’ well-being, the conditions of the soil, and the presence of pests. They were able to
monitor problems quickly through this high resolution imagery and therefore resulted to
improved yield among the farmers. These actions therefore enabled farmers to tend larger sums
of lands with fewer implements, which only goes to show the effect of automation in its
unification of agribusiness. But the tempo of automation has increased in the recent decade
following the application of the AI and Machine learning to increase precision in farming
(Rodriguez Martha Martinez, 2022). Autonomous tools can also survey lots of data from the
climate, meter readings, and even market tests, and give advice based on the results. It can
predict crop yield, to schedule the time for planting and even ability to diagnose diseases at early
stages so that interventions can be responded to on time.
1.3 Current Trends
The trends currently witnessed in the agribusiness automation involve the aspect of Artificial
Intelligence and Robotics to conduct the farming operations (Feng & Chen, 2020). Informational
technologies such as precision agriculture is gradually adopted by the farmers in order to make
decisions regarding planting, feeding and harvesting (Li & Zhao, 2021). There is precision
agriculture, which is based on such tools as the status of the soil, aerial photography, and GPS to
control the field in real-time for crops management. For example, the use of a cellular phone
allows the farmer to apply fertilizers and pesticides in areas of widespread infestation only and
not in other areas this increases efficiency hence conservation. Also, robotics is instrumental in
activities including planting, weeding as well as the aspect of harvesting, all of which consume a
lot of manpower. These tasks can be accomplished by automated tractor and harvesters with
more efficiency and adherence to quality hence improving on the productivity of the agriculture
activity. Self-driving vehicles can detect and control weeds or separate fruits and any vegetables
without affecting the plants; this is usually tiresome and requires a lot of time. This technological
improvement is very advantageous especially in counteracting labor inactivity since it decreases
dependence on seasonal labor and ensures constant productivity once human labor is limited.
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They thus assist in solving the problem of a lack of personnel while hence becoming a valued
financial investment in the protection of employees from excessive physical exertion. A section
of work can be done on its own without constant supervision and some work that would prove
strenuous on the bodies of farm workers can also be repeatedly accomplished. Similarly, instead
of use of workers physically moving around in the large fields to assess crop health, and
condition of the soils, use of drones makes the work quick and accurate. There is thereby a need
to assess the effects of the increasing usage of automation industries on the agricultural
employees and also ensure that farmers and hence employees are skilled and also ready to handle
the changes within the agriculture sector. It therefore involves presenting training opportunities
and also tools that would thus assist employed personnel to shift to other positions that demand
their skills in operating and servicing the equipment that the establishments have acquired. It will
also be necessary to protect the rural population from possible displacement during this transition
period and include the relevant elements in the policies and initiatives aimed at automating
production facilities.
1.4 Future Projections
Analysed in the context of the present study’s predictions, the future of automation in
agribusiness will continuously evolve in the field of AI and machine learning to improve
precision in farming operations. Advanced computing intelligence will be used to assess large
chunks of information through understood algorithms to make a prognosis on the productivity of
farming. These technologies will enable the efficient use of water, fertilizers and pesticides thus
minimizing their use, environmental pollution and at the same time increase yields. Launch of
autonomous cars and drones is predicted to minimize the human labor input and enhance the
prospects of agriculture output (Smith & Jones, 2020). The autonomous tractors, harvesters,
drones are self-operated and will help in the planting process, monitoring as well as the carrying
out of the crop harvesting. These machines can thus work at all times, and also have high
working efficiency which thus greatly enhance the production of farms. The newfound sensing
systems and big data solutions will deliver the proper understanding of crop, soil, and weather
status directly to the farmers to predict and manage problems in advance (Nguyen & Tran,
2020). Some of the functionalities that could be featured include ability to test moisture, nutrients
and general health of the plants while they are in the fields. Together with the help of big data,
this data can produce complex models of when to sow and when to reap, in addition to
discovering complications at their initial stages when they do not threaten to become major
issues. However, it also has adversely affecting the advancement of technological systems,
which imply, inter alia, that the agricultural labor force needs regular investment in training and
education to meet the pace of change (Rodriguez & Martinez, 2022). The nature of work in
agriculture will evolve as technology grows, meaning that while the need for people in this
profession will exist for now, the specific tasks that workers will have to perform will be based
more on technical aspects of operating new and complex tools and applications. Companies,
schools, and training schemes have to change, providing courses which enable the employee to
become adaptive to the conditions wherein high levels of automation are present. This is why as
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new automation technologies emerge in the agricultural environment the means of capturing
their potential while minimizing the social and economic impact them on farmers and rural
communities must be established. It is therefore important for policy planners and market
influencers to come up with mechanisms that would encourage the takeoff of the automation
while at the same time trying to organize for the protection of the conventional farming
occupations. Such measures thus include; funds in education and also training and hence
assistance to rural areas that are affected by changes introduced by automation.
2. Job Displacement and Transformation
2.1 Types of Jobs Affected
A logistic consequence of production going high-tech through the use of automation is that it is
changing the nature of employment in the food chain. The skill demand gap concludes that
traditional manual tasks like planting, weeding, and harvesting are now done by machines and
robots thus decreasing the employment opportunities for low-skilled human labor (Gao & Lin,
2020). Larger farming businesses are mainly affected by these changes owing to the fact that
automation solutions are more likely to be implemented based on the scale of operation (Smith &
Jones, 2020). Therefore, the employment prospects of many farmworkers who used to work
without the help of machinery are now reduced to looking for other jobs or remain in the sector
but in other capacities which do not necessarily entail the use of their muscles as a key tool. For
instance, the current generation is resourceful in the newer unconventional professions such as
electrical technicians and engineers for maintenance and assessments of automated systems
(Chen & Zhang, 2020). These positions demand the possessor adequate knowledge and skills in
mechanical and electronics; one should be able to solve technical incidences. Also, data analysts
and IT specialists are valuable for the effective usage of big data from the precision agriculture
technologies (Nguyen & Tran, 2020). Such specialists thus use data from all sorts of sensors and
also other automated systems to furnish information that hence aids in improving farming. These
shifts are therefore valid, pointing out the growing role of training and hence education
interventions geared towards re-skilling the workers on the changes taking place in the
employment sector in agribusiness. Schools and colleges as well as vocational institutes should
integrate into their curriculums topics on the use of complex and modern machineries,
automation and digitization, data analytics and information technology applicable to the present
day farming. Also, the skills demanded in the workplace are constantly changing and require
regular updating to enhance the current workers’ employability. Another element that needs to be
addressed to enable this change is thereby having the governmental and industrial support. The
measures that will facilitate change by offering funds for re-training, promoting Apprentices, and
rewarding business with incentives to train the worker will play significant roles to
newline:reorient agriculture to a more automated labor-using sector. This way the agribusiness
sector will be able benefit from automation to the maximum and at the same time minimize the
number of people who will be sidelined by the technology.
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2.2 Scale of Job Losses
The extent of job displacement as a result of the application of technology in the agriculture
business is however not universal but has its indicators based on the geographical location, the
kind of farming, and the level of use of technology. There are several areas where technological
advancement majoring automation in the agriculture sector has small impact in certain areas,
especially in large-scale industrialized areas where it has led to a drastic downscaling of the
agriculture related workforce (Rodriguez & Martinez, 2022). For instance, the continuous and
increased usage of automated harvesters and robotic milking plants has been found to cut down
the need for labor by up to fifty percent –a situation that has led to massive unemployment of
manual laborers (Huang & Wang, 2020). But they are not received equally in all the regions or
forms of farming that can be classified. A smallholder and specialty producers, the kind of
agriculture that may focus on a few crops and use labor-intensive methods of production, may
feel the least impact of automation, and may continue to employ large numbers of workers (Feng
& Chen, 2020). Such farms mostly are demanding in human input that automation can barely
imitate, thus creating opportunities for those involved in conventional farming and arts of
craftsmanship. In addition, the total effect on occupational opportunities might be reversed by
the generation of jobs in the areas of technology advancement, technology maintaining and data
processing (Li & Zhao, 2021). Self-utilizing innovation in agriculture tends to make more
demands for professional who are capable to design, set up and dismantle those systems. This
change can thus also present opportunities for displaced workers willing to learn new skills
because it therefore requires specialized knowledge and also skills in data management. Thus,
policymakers and also heads of industry should take into account such variations when designing
strategies to mitigate the impact of automation in the workforce. Housing displaced workers’
means developing programs specific to their needs and geographic area, including retraining and
education to match the requirements of an increasingly automated agriculture business.
Moreover, establishment of relationships between producers and also providers of education can
hence be used to make sure that the training meets requirements of the targeted company.
Policies of the government also have to encourage investments needed for moving from
traditional agriculture to high technology agriculture. Honest encouragement to encourage
enterprise’s to sponsor rural training centers and support for such technologies could start to
close the gap between traditional farming techniques and the new technical skills needed.
2.3 Job Evolution and New Roles
Even though automation in agribusiness is replacing the traditional manual work, it is also
opening up areas of employment which are skilled based. Changes in the jobs in the sector are
necessitated by the need for trained personnel to manage and operate the new technologies
including unmanned tractors, drones and precision farming devices (Smith & Jones, 2020).
Therefore, there is a growing need for technicians, engineers, and IT specialists to manage such a
system (Chen & Zhang, 2020). Also, new roles are emerging because data analytics is being
incorporated progressively in the practice of agriculture, including the data scientists and
analysts who can analyze the huge amount of information produced by the mechanization of the
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undertakings to ensure proper functioning (Nguyen & Tran, 2020). They therefore collect data
from numerous sensors and also auto-mated systems in a farm to assist the farmer in making
better decisions of crop yields, resource utilization, and also organizational efficiency of the
farm. These transitions are also positively impacting equal opportunities at the workplace since
new jobs in the market attract people with divergent abilities and stages in life. Thus, the demand
for demanding qualifications and abilities is leading to a diversified growth of workforce in
terms of the gender, education and work experience, and attracting talents from different regions
of the country and various fields of study from the urban areas. However, for the workers to be
able to move into these new positions adequate capital is needed in education and training
programs to prepare the human capital. Academic establishments and vocation training agencies,
as well as collaboration with the industry, must concentrate on the creation of techniques
correlating to analytical and technical skills required for automated agribusiness. This even
therefore involves; application and also exposure to the current trending tools, training in areas
such as data science, engineering, and hence information technology. Industry and also
government partnership is thus a necessary element to foster this shift. This could be made
possible by governmental polices that would encourage funding for retraining necessary
programs, support for apprenticeship, not to mention encouragement of incentives for investment
on human capital development especially to see the agricultural sector become more
technological.
2.4 Case Studies of Impact
Reflecting on the discussed cases of automation in agribusiness thus enables the discussion to
hence consider the practical effects of automation technologies on people. For instance,
implementation of automation technology such as robotic harvesters in the California fruit and
vegetable farms affordably eliminated California’s seasonal workers, although it offered
promising prospects to innovative technicians (Gao & Lin, 2020). These technicians are now
required to operate and maintain the complex systems of equipment to do away with the
manpower thus requiring these efficient skills in lieu of the human ability to muscle it out. In the
same way, similar commercial dairy farms in Europe that adopted automatic milking system
have found reduction in manpower and the direct number of job opportunities for paid manual
labor but there has been a creation of the new kinds of jobs for people to work on the systems
themselves. Robotic milking saves time of milking than when done manually but this requires a
work force that is skilled in the handling and maintenance of hi-tech equipment. This change of
emphasis can be attributed to the transformation of the basic pattern of work force in agriculture
towards technical competence. One more example is the use of drones and precision agriculture
tools in the grain farms in Australia, which in turn enhances performance and productivity of
grain farms but shifts the nature of work on these farms (Nguyen & Tran, 2020). Drones give
farmers an aerial view of the health of crops, condition of the soil and the level of pest infestation
to name but a few. Due to this, there is a demand for data analysts and IT specialists for
processing of data gathered by drones and other sensors resulting in emerging fields that one has
to study to be equipped with those skills. These case studies therefore demonstrate the diverse
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effects of automation on different categories of farming companies and hence emphasize the
necessity of finding specific approaches to the workforce issues and also opportunities of these
innovations (Rodriguez & Martinez, 2022). Automotive impact not only can have positive but
negative effects as well, therefore, policymakers & leaders must understand that it is not same in
all sectors of agriculture & need to develop programs according to the requirements of the
particular area. Education and also training are thereby vital for displaced workers to be able to
fill new demands in areas made possible by automation. This thus includes; enhancing the
curriculum in the agricultural colleges and also the vocational schools to cover various areas that
are related to use of modern technologies.
3. Technological Innovations in Agribusiness
3.1 Automation Technologies
Automated technologies in the operation of agribusiness are thus changing traditional approaches
to farming through enhancing productivity or efficiency. Another revolutionary technological
innovation is the self-driving tractors and other farming machinery including planting and
weeding machinery and harvesters which reduces human manual input (Arnold, 2020). The
existing farming equipment has incorporated the use of GPS and sensors to maneuver through
the fields and execute various activities in farming with higher accuracy and minimal human
intervention (Chen & Zhang, 2020). Technologically advanced irrigation systems such as the one
that incorporates soil moisture sensor and s weather data input are very effective in delivering
water to the concerned crops in the right proportions at the right time hence increasing
productivity while at the same time maintaining the resource adversity (Nguyen & Tran, 2020).
They not only minimize the labor needed in the irrigation methods but also enhance the usage of
water which is a very important factor especially in areas which experience water hiccups. Farm
labor scarcities are hereby a major issue for many agricultural areas, and hence robotics is an
answer to this problem in that it thus decreases the dependence on seasonal and also manual
labor. As a result, practical solutions from the category of artificial intelligence can lead to a
reduction in the level of labor costs and enhance the profitability of the production processes of
the farming businesses. However, the utilization of such technologies warrants a drastic
investment and technical assistance, which may pose challenges as far as small scale holders are
concerned (Rodriguez & Martinez, 2022). Some of the potential drawbacks of automation
therefore include: The quotation of investing in automated system is usually high hence large
scale farmers have to borrow the money required to purchase the automated systems and install
them hence, it will be expensive for small scale farmers hence they cannot afford to put their
money in advance technology. Moreover, the management as well as the maintenance of these
systems need certain expertise, and thus, additional resources would be called for in terms of
training and educational needs. Nevertheless, the long-run advantages of automating the
agriculture business enterprise are quite profound. Productivity of agricultural produce can be
raised and this has a positive effect on the usage of resources which makes agriculture more
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sustainable in the long-run. Others ways that policy makers and also industries can hence help
the small farms include; financing, education as well as infrastructure sharing.
3.2 Precision Agriculture
Precision agriculture is therefore, an important subsector of the automation revolution that is
sweeping through the agricultural business, which thus focuses on data analysis and also
technological applications to enhance crop productivity and hence resources. This one is an
approach of the utilization of GPS, remote sensing and the internet of things for the purposes of
data gathering on the nature of the soils, crop status, and environments (Gao & Lin, 2020). The
entities then apply this information to advise farmers on the proper time to plant, use fertilizer or
even irrigate crops thus enhancing agricultural practices (Smith & Jones, 2020). An example of
precision agriculture technology is VRT or commonly known as variable rate technology that
enables the farmer to apply fertilizer and pesticides only where and when they are needed hence
minimizing wastage of the product and the effects on the environment (Chen & Zhang, 2020).
VRT thereby employs data gathered from the soil sensors and hence crop monitoring systems to
define that amount of inputs needed for different regions of the field. This makes it economical
since it will help in cutting the input costs as only the affected area is treated; it also helps in
checking on the misuse of chemicals hence helping in checking pollution. Lastly, precision
agriculture increases crop productivity and quality that may lead to improvement of the
agricultural products in the international market (Nguyen & Tran, 2020). Farmers are in a
position to know when plants are under threat from factors such as insects or lack of nutrients
hence benefiting from improved plant health. This would therefore go hand in hand in providing
the growers and also farmers with better yields and hence improved quality produce to meet
market expectation. However, precision agriculture define the precise use of different types of
inputs, including technology inputs which might be a problem for smaller or constrained farm.
There are high start-up costs when it comes to accuracy in agriculture methods and equipment;
some farms will not be able to afford them. However, to use these technologies one requires
some level of technical know-how something that may not be common with traditional
agriculture based societies. To eradicate these barriers, government and industry support is very
relevant. Some of the recommendations include the grants and low-interest loans that can be
offered by governments or bigger firms that can be used by relatively smaller farms to invest in
precision agriculture technologies. In the same respect, training and education measures can
ensure farmers are knowledgeable about the manner in which they can successfully apply these
tools.
3.3 Robotics in Farming
Robotics technology in farming is thereby rapidly changing different aspects of farming, thus
making some of these activities less invasive of the use of labor. Planting, weeding, harvesting,
and sorting crops which were earlier labor-intensive have now been done by robots (Smith &
Jones, 2020). For instance, mechanical pickers such as robotic harvesters can pick fruits and
vegetables perfectly and faster thereby cutting down on cyclical human labor and reducing losses
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(Chen & Zhang, 2020). These machines are fitted with special sensors and AI that enable the
machines to spot maturity or readiness of the fruits, vegetables, and nuts and also the handling of
the produce to prevent bruising and breaking. However, automatic weeders that use computer
vision and machine learning algorithms in the form of Robots are capable of recognizing the
weeds and eliminating them without affecting plants, hence, they seek to eliminate the use of
chemical herbicides which are employed in combating weeds and promote GREEN agriculture
(Nguyen & Tran, 2020). Such robots rely on cameras and other machine learning algorithms to
identify the plants which are require for cultivation from the weeds. Besides, it also helps to
minimize the amounts of chemicals that are damaging to the environment or human health while
appreciably cutting the costs of herbicide application and paid manual weeding. Thus, the
application of robotics in farming caters for the improvements in efficiency and also yields,
workforce deficit, and hence physical stress on workers. Combined with the fact that the
agricultural workforce is gradually aging and the quantity of manual labor continues to shrink,
robots allow one to overcome this problem. They can work at any time of the day without getting
easily tired, which in turn yields better and steady results. For instance, robotic systems in dairy
animal farming include milking, feeding and cleaning processes which are time-consuming and
require many manual inputs hence allowing people to work smarter (Smith & Jones, 2020).
Nevertheless, the high investment costs of robotic systems, as well as the necessity for staff
expertise to program and control the robots are constraints for the small-scale farms (Rodriguez
& Martinez, 2022). The use of robotics means that the initial investment might be high and
robotics sort of needs constant repair and upgrade, skills of technicians are therefore important.
However, these financial and technical requirements might be harder for small farms to meet,
which implies that they will have a lot of difficulty in implementing robotics solutions.
3.4 Artificial Intelligence Applications
AI applications have hence shown significance in the enhancement of automation within
agribusiness as a way of making farming better. In addition to machine learning technique,
computer vision and predictive analysis, technologies are used to screen crop health condition,
predicted yield, and resource utilization (Gao & Lin, 2020). For instance, machines with artificial
intelligence such as drones and sensors could relay information on soil and weather as well as the
progress of crops with which farmers could make rational decisions concerning water and
nutrient supply, and pest control (Smith & Jones, 2020). These AI systems thus process a large
amount of data information in order to produce useful information. For example, this application
of artificial neural networks can help decide when to sow seeds and when to harvest crops based
on weather patterns in the past and the present climate. Such a predictive ability is therefore
useful to farmers so that they can thus earn high revenues and avoid big loses. In the same way,
use of AI can guide diagnosis of plant diseases at early stages and various measures can be taken
to avoid losses which may otherwise have been occasioned by such ailments, thus increasing
yield (Chen & Zhang, 2020). With the help of computer vision, crops can be checked for disease
or pest infection, and then farmers can get to know of these problems before they escalate. In use
of artificial intelligence in agribusiness the productivity and sustainability of farming is improved
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not mentioning the fact that there is lesser reliance on labor and a higher accuracy is achieved. AI
can thereby control and hence elaborate on inputs such as; water, fertilizer, and also pesticide
application, thus minimizing on the areas and frequencies it is used. This precision therefore
helps to cut on; wastage, costs and also the effects on the environment. For example,
organizational solutions such as automated irrigation can thus solve the problem of providing
water for plants depending on the soil moisture and also forecasted weather conditions.
Nevertheless, AI integration is associated with capital and human capital costs in the form of
purchasing equipment for AI technologies’ implementation and training farm employees to use
AI systems (Nguyen & Tran, 2020). Since the acquisition of AI system and its maintenance costs
a lot and requires technical persons to run it the constraints faced by SHFs such as small scale
farmers limit their ability to adopt the IT solutions. The implementation of AI in conventional
farming methods thus requires adequate knowledge of the technology and also the ability to
incorporate it into the farming processes.
4. Economic Implications
4.1 Cost Savings and Efficiency
This study thus focuses on the economic consequences of automation technologies in
agribusiness for instance; cost, expenses and also efficiency. It leads to increased efficiency
when using resources like water, fertilizers, and pesticides; hence, less wastes are produced, and
the costs of production are brought down (Gao & Lin, 2020). For example, the smart farming
technologies that are used in the precision agriculture system allow farmers to use fertilizers
selectively where and when likely to be useful and in the right quantity to avoid polluting the
environment (Smith & Jones, 2020). Further, the use of the automated machinery can work for
more hours and with better efficiency than the human labor meaning the productivity of the
company will increase and the labor cost will decrease (Chen & Zhang, 2020). Machines and
automation are not capable of getting tired; hence no issues of tiredness and thus constant work
and quality output. This reliability can go far in improving the overall productivity per farm
whereby the farmers can work on larger expanses of land. For example, tractors are robotic and
can do planting and or harvesting at any time of the day rather than having limited time like
human farmers. All these efficiency gains are very important in a competitive environment that
demands that companies operate on very thin margins and here a little chance to shave down
costs can make a lot of difference (Nguyen & Tran, 2020). Through mechanization of farming,
farmers can produce more at a cheaper cost because high production is the only known way to
counter high market prices of produce or high costs of inputs. Also, due to the increased
precision and speed of automated systems, the results could be harvest and quality of products,
strengthening competitiveness. The change to automation moreover calls for massive capital
investments in both capital equipment and hence training of the workforce, something that is
therefore characteristic of small scale farming. The initial investment which is required for
purchase of automated machinery, precision instruments for agriculture and AI needs a large
amount of capital. However, these technologies require constant updates and maintenance which
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will require finance which makes it costly. Another challenge is the requirement of specialized
training for the operation and management of these systems which may prompt the challenge of
training farm personnel when the farming tracts are relatively small and the farm proprietor may
not be able to afford to provide specialized training. To overcome these challenges there is need
to attract support from government and industries. Most of the small farm businesses need
financial support in terms of grants, subsidies or sponsored programs for automation
investments. It is therefore possible for training programs and strategic alliances with producers
of the new advanced technologies to enable the farmers to learn how to harness on the new
technologies.
4.2 Impact on Wages
The effect of automation technology on wages in agribusiness was indicated to be dual in nature.
On the one hand, the release of low-skilled manual workers from the production line by
automated systems could result in the causing of unemployment of such workers and a veteran
tendency to compel the remaining employees to accept lower wages for labor-intensive
occupations (Smith & Jones, 2020). As companies continue hiring fewer farms workers, the few
remaining in manual labor will most likely have competition and experience reduction in wages
(17). This means in effect that corporations rather than experience an increase in demand would
face a challenge of having the remaining jobs over supplied hence the bargaining power of the
workers reduces and their wages are low. On the other hand, the implemented automation
technologies lead to substitution for the existing workforce resulting into creation of new job
opportunities within higher skilled technology specialization like operating and maintaining
automated machinery, data analytics, and technology innovation (Nguyen & Tran, 2020). Most
of these new jobs demand more education and training than the traditional blue-collar
occupations and pay better salaries and remunerations than physical work (Rodriguez &
Martinez, 2022). That is, technicians who are capable of fixing breakdowns of sophisticated
farming robots or data analysts who are able to understand the data produced by precision
farming technologies are likely to be paid better because of the skills demanded. Automations
effects on wages-results are the summarized effects of technology on wages and are dependent
on the efficiency at which workers are able to switch to these roles and the spending on
education/training programs. If the workers manage to get the adequate qualifications for these
new post, they stand to gain better wages, safety and job security. This process thus needs heavy
expenditure for retraining and also skill development to train the displaced workforce for more
innovative technical positions. For instance, learning that is offered to train workers on core
vocational training programs and partnerships with firms that embrace technology are very
useful and offer the workers a competitive edge to win job offers.
4.3 Market Competitiveness
In one way or another, automation in agribusiness can greatly increase market competitiveness
since it will boost the operational efficiency, decrease costs, and serve as a mean of tying down
the quality and standardization of agricultural products. In this way with the use of the different
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high technologies farmers are able to produce more even with less capital which leads to their
ability to penetrate the domestic as well as the international markets (Gao & Lin, 2020). For
instance, in precision agriculture, technologies assist the farmers in the correct application of
inputs to obtain the maximum out turn and at the same time helping them produce quality
produce that can be sold at higher prices (Smith & Jones, 2020). Precision agriculture thus
includes; applications of GPS, IoT sensors, and also data analysis to oversee crop growing at the
best possible detail. This approach thereby assists farmers to apply fertilizers, pesticides, and also
water in a more efficient way hence reducing the rate of environmental pollution while at the
same time increasing the health and yields of crops. For example, variable rate technology
(VRT) allows for the focusing of inputs in terms of its requirements in various zones of the field
so that the growth and quality of the yield would be effectively enhanced. Furthermore,
automated machinery in the case of harvesting and processing also helps the farmers to minimize
on time and/or labor for such calls hence giving them the flexibility to respond to market forces
and also help in minimizing on post-harvest losses. This process can go on for many hours
without getting tired; thus, it can harvest the crops at the right time and sort them effectively.
This not only makes it easier to avoid seasonal labor which can be much more sought after and
costly but also effectively decreases the risk that results in spoilage or damage to the fruits;.
Therefore, through such improvements in efficiency and productivity, competitiveness of the
agricultural products can be boosted and market share gained. Automated system can assist the
farmers to manage supply chain effectively so that the fresh produce can be transported to the
market on time since this has great influence on consumer loyalty. Automation therefore helps
the farmer to bring down the operational costs and thus increase the productivity, thus making it
easier to offer lower price and also feed the increasing world population. Still, positive effects do
not affect all participants of the agricultural market, and small farms can hardly compete with
large ones using more sophisticated pieces of equipment (Rodriguez & Martinez, 2022). The
costs of acquiring automations and integrating them into the farms as well as the training
required and often expensive maintenance can be very difficult for the small holder farmers.
4.4 Regional Economic Effects
Regional impacts of automation in agribusiness are influenced by many factors and may be
reported differently across regions. In large scale farming areas the use of automation
technologies acts as a stimulus to economic development as it creates new employment
opportunities in technologically based industries like production, maintenance, and analysis
(Smith & Jones, 2020). These developments also contribute positively to productivity apart from
agricultural competitiveness, thereby leading to possible income improvements, and thus
stability in those regions (Chen, & Zhang. , 2020). For instance; the synchronization of
automated machineries and systems of precision agriculture that allow farmers to use every
available resource carefully and expand production in the right manner. This thus increases the
yield and product quality, which may be sold at better prices locally and also internationally,
hence enhancing operational efficiency. Also, employment opportunities for skilled technicians
as well as engineers in operating and maintaining the advanced technologies assists in creating
13
employment opportunities and the promotion of the economy. On the other hand, areas where
traditional agriculture is practiced and manual work is very common, the shift towards
automation comes with difficulties. Faster agricultural technologies can make farmworkers lose
their roles in planting, harvesting and this can cause unemployment or even a downturn in the
economy (Nguyen & Tran, 2020). It is apparent that this shift does more than encourage or
change the fate of a single worker, or a few; it alters the fortunes of several rural economies that
may stagnant or even reduce the populations in such areas along with the economic dynamism
that comes with full employment. This has led to the decrease in demand for employment
opportunities that require manual labor, which is likely to cause social inequalities and pressure
the togetherness of families and individuals due to their shifty monetary prospect. To the above-
mentioned effects, policymakers need to enforce policies that would help improve the conditions
of the workers and the communities influenced by these changes. This hence entails funding for
retraining of the displaced farmworkers in order to effectively enable them to compete for the
jobs within the growing sectors. Programs to encourage new businesses and increase the variety
of industries of a region also minimize adverse effects of automation. At the same time,
technology firms, education institutions and also local governments can form partnerships in
order to help share the needed information and hence resources for implementing automation
technologies into the sphere of agriculture.
5. Social and Labor Impacts
5.1 Worker Skill Requirements
The shifting nature of workforce demands in agribusiness through the application of technology
is changing the nature of skills required with strong focus on the technical competencies rather
than physically demanding jobs. Jobs that were largely manual are now becoming automated,
hence; employment is now tilted towards proficiency in operating, overseeing and repairing
complex machines and computer based systems (Chen & Zhang, 2020). This change thus
highlights the increasing demand for activities that involve; robotics, big data, and also
technologies used in precision agriculture in the agricultural field (Nguyen & Tran, 2020). As the
cases demonstrate automation is becoming more prevalent and therefore there is need to invest a
lot of money in education and training. The above measures are therefore still crucial in making
sure not just that present agricultural employees get adequate training, but also in the capability
of drawing in new talent towards engaging in the agricultural industry. Through recent academic
model and with the advancement of education programs in robotics, the applications of Artificial
Intelligence in agriculture, and data-driven decision-making system; the modern demand of
farming has shifted and become imperative (Rodriguez & Martinez, 2022). Such programs not
only help to fill the skills gap but also help the workers to use technology to therefore increase
productivity and thus sustainability. Further, one must continue to learn as well as further their
education as technology in the profession advances at a fairly high rate. Employees are required
to change and embrace new technologies in hope of being able to stay relevant in a rapidly
transferring agricultural economy (Smith and Jones, 2020, pg 111). Nevertheless, moving into
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the technologically sophisticated positions create some dilemmas to be solved, especially for the
older employees or those who have the limited chance to enhance their education and training
(Gao & Lin, 2020). To therefore tackle these challenges, it is thus necessary to provide specific
assistance and also funds to guarantee equal opportunities of their participants. Measures to
support transitions are vocational training, apprenticeship training and collaboration between
Academic Institutions and farming businesses where necessary to ensure that the new generation
as well as workers of other ages can take part in the new revolution in the use of the new
technology in agriculture. To sum up it can thus be stated that automation in agribusiness has the
potential to open up possibilities for increasing efficiency and also introducing innovation, but its
implementation thus requires focused efforts on the production of qualified workforce. Through
education, training, and also lifelong learning experiences, various stakeholders can thus equip
agricultural workers with skills for performing complex tasks in technologically endowed
positions leading to development of the agricultural sector.
5.2 Job Satisfaction and Conditions
The analysis of employment intensity and also working conditions in the wake of automation in
the contexts of agribusiness thus reveal the presence of opportunities for improvement and
threats. There are benefits to automation of conserving workers’ energy and taking away tasks
that involve strength and bore some of the effort required as workers can then be allowed to
think and work pursuant to their intellect (Smith & Jones, 2020). Traditionally time-consuming
and labor-intensive activities like planting and harvesting can now be accomplished with higher
accuracy and less effort by the workers after the introduction of automated systems— Aetosoft
survey proves the premise that overall job satisfaction improves with the help of technological
improvements in the course of the performance of daily tasks. In addition, working conditions
enjoy benefits from automation because it thereby reduces the exposure of workers to various
dangerous surroundings. For example, smart machines such as automatons for weeding and
harvesting also protect the workers from working in unfavorable conditions or dealing with
invasive equipment personally (Chen & Zhang, 2020). However, the subject of automation
transition also brings about factors that can thus affect the worker’s satisfaction and hence do
create some uncertainties. The off-farm hiring of agriculture workers and young educated people
to eliminate conventional farmworkers have displaced skilled farm workers making them
insecure and stressed at work due to technology orientation (Rodriguez & Martinez, 2022).
Employees may have issues concerning employment security in the future or may have concern
towards obtaining the appropriate skills to work in these new positions. In turn, these changes
represent a source of stress for workers, to which employers are instrumental in helping them
adapt with a positive work culture and constant education/training (Gao & Lin, 2020). Promoting
skills development initiatives such that prepare workers for the roles that are being defined in
automation can therefore positively influence the security and also mobility of these workers.
Developing a culture that accepts workers and also embraces all of them can furthermore, reduce
the effects of the uncertainties of the job and hence increase the job satisfaction among the
workers.
15
5.3 Rural Community Changes
Automation is a critical factor that impacts the economic structure of the rural regions as well as
their social setting in relation to agribusiness. As the traditional farming methods come under
pressure in the regions where automated farming kicks in, resulting in job losses among farm
workers because such animals are more efficient in planting, harvesting and sorting produce
(Smith & Jones, 2020). These changes may help to cause a reduction in economic activity levels
since a lower amount of agricultural jobs suggests that people in the area may have less money to
spend in general (Chen & Zhang, 2020). Besides, job seekers who have been displaced from
their workplace add unto the populace that looks for other job opportunities which increases the
rate of drop-out hence complicating the community cohesiveness as well as the worsening of
infrastructural and service delivery systems. But there are opportunities available for the rural
populations as well in the aspect of automation. New sectors that are linked to automation may
provide employment for the skilled human capital, for instance; robotic maintenance staff, data
analysts, and workers in precision farming technologies( Nguyen & Tran, 2020). Such jobs
usually demand more education attainment and technical skill, and this will encourage the youth
population to return to the countryside besides expanding the economic streams of a given
county other than farming. In addition, technological advancement in the use of automated
farming systems can increase yield and even the operations of agriculture production making the
local farming industries perform better in the national and even international markets (Gao & Lin
2020). This in turns may result thus in increased income for the farmers and also help in the
enhancement of economic status of these rural regions. In order to fully exploit these
opportunities yet at the same time work round the problems that are posed by the issue of
automation, it is necessary that the policymakers and leaders in the community come up with a
balanced approach to enact legislation that may govern the practice. Most technological
advanced nations direct financial resources on education and training that fit the new
technologies as a way of preparing residents to work in advanced agro-food systems (Rodriguez
& Martinez, 2022). Thus it can also support entrepreneurship and small business development so
as to foster economic diversification and robustness. There should be cooperation on how the
inhabitants of the community are going to therefore benefit from the use of automation, who else
can thus benefit or how the local dilemmas will be considered. Finally, the automation in
agribusiness can in some way negatively affect the rural economy but at the same time they can
enhance the development of the zone.
5.4 Workforce Adaptation Strategies
As demonstrated in the case of automation, if aggressive working methods have to be adopted in
the agribusiness, then successful adaptation skills are vital. Education and training is a central
approach required to ensure that the worker is prepared to take on different tasks in modern
technologically developed agriculture fields. These are vocational training, apprenticeship, and
lifelong learning covering Robotics, Data analytics and Precision Agriculture (Chen & Zhang,
2020). After going through such programs, workers can easily move from the traditional low
skilled direct physical labor category to careers that are more technical thus more marketable in
16
today’s society. The stakeholders and the authorities in the field of policy-making should
promote the partnerships between educational institutions, governmental bodies, and
agribusiness organizations to design the corresponding training programs that would suit the
needs of the sector (Rodriguez & Martinez, 2022). Thus, it is possible to state that by
establishing connections with business, training programs will develop crucial knowledge that a
worker needs to be successfully employed in the present-day context of the agricultural sector.
Also, increasing awareness of STEM (Science, Technology, Engineering, and Mathematics)
education among the future generation in rural farming communities can create adequate human
capital for progressive high-tech agribusiness career opportunities. Another significant approach
is to therefore provide; job search assistance, resources, and/or also monetary support for
displaced workers and hence affordable social services to support them. Such measures may
assist the workers to seek other jobs without much difficulty thus solving some of the social and
economic problems created by the use of automation (Smith & Jones, 2020). Workers are viewed
as vulnerable to be provided with financial assistance programs aimed to offset living costs while
they are trained for positions that meet the demands of the reformed fields of agribusiness, albeit
temporarily. Other prevention methods thereby include; promotion of innovation and also the
development of entrepreneurship within the rural areas. Thus, encouraging young companies and
SMEs that work on the advancement of agricultural industry, rural economies can get new
revenues and working places. Local government and hence industry partners can thus provide
incentives such as; grants, low-interest funding or financial assistance and also business
development support for growing the culture for innovation. Lastly, creating a supportive
organizational climate with the latest policies regarding employees’ discrimination and also
equal opportunities is hence crucial. Employers should enhance the welfare of the workers
through providing numerous avenues of professional practice for the employees and creating
social contexts where the employees would feel appreciated and safe (Gao & Lin, 2020).
6. Policy and Regulatory Considerations
6.1 Government Role and Initiatives
Automated technology, in general, has therefore proven to be useful to agribusiness, however
governments have a say in how it thus affects the whole value chain. Thus, they can put in place
policies that will enable organizations adopt automation technologies as well as ensure that the
positive impact is fairly shared (Smith & Jones, 2020). This involves offering subsidies on
automation, offering grants and tax exemptions to fund technologies in farming (Chen & Zhang,
2020). These bonuses can thereby allow reducing the restrictions to small farms’ access to the
benefits of automations for a diverse range of agricultural businesses. Infrastructure is another
key promising area that governments can address improving significantly, Investing in
infrastructure. Fast and steady connections to the internet and electric power are critical for the
application of innovative technologies in the development of rural areas (Nguyen & Tran, 2020).
In this way, the governments can thus enhance the rural environment so that farmers could hence
use all the possibilities of precision agriculture instruments, automated technologies, and also
17
data-driven strategies. This infrastructure development is equally significant in order to avoid
compromising the capability of other citizens in the rural areas by the advancement of
technology in the agriculture sector. More specifically, policymakers should also unveil
reformed rules or new rules to support motives of developing new technologies and product
innovations, safety and wellbeing of workers, and the development of sustainable agriculture
programs (Rodriguez & Martinez, 2022). Policies should promote the development and use of
the green technology when implementing automation in industries while at the same time
offering employment to those individuals who may be affected by the eventualities of
mechanization. Such integrated strategy may thus reduce negative effects of automation in the
process of creating jobs for people and also preserving the natural environment in the agricultural
field. It will furthermore, be the governments’ responsibility to broker the necessary
partnerships between the different stakeholders, including; schools, businesses, and hence rural
people. Therefore, through supporting the partnership and knowledge-sharing opportunities, the
former can contribute to the creation of the relevant training schemes that would prepare the
workforce for the new environment in the sphere of agriculture (Gao & Lin, 2020). These
programs can separately be dedicated too specialties like robotics, data computing and
technological advancement in agricultural business like precision agriculture technologies to
make sure that the workers are ready and prepared for these innovations in the market.
6.2 Labor Laws and Protections
In as far as automation continues to be the order of the day in the agribusiness sector, it is high
time that labor laws and protections are put up to date regarding how emerging challenges and
opportunities in the field are met head on. Most important of which is how recompense adequate
social protection to the labour displaced by the automation process. This entails enhanced
unemployment packages, retraining that best suits the existing hi-tech agricultural environment,
affordable and quality job search facilities (Smith & Jones, 2020). These steps therefore might
assist lessen the effects of job discounting and also assist the personnel in find new jobs in the
industry. Also, one has to remember that there is a need to modernize laws regarding labor in a
way that protects newly appearing types of workers – those working with owls. This involves
taking measures to ensure that the pay offered meets the required standard for people expected to
operate and maintain complex structures, providing safe working environment, and extending
promotional opportunities to upgrade the skills of employees (Chen & Zhang, 2020). However,
through formulating policies that clearly indicate the standards and provisions in matters
concerning employees and their jobs, then workers shall be protected hence guaranteeing a stable
and productive work force for the agribusiness industry. The other vital area that need to be
addressed in the context of improving the labor laws that address automation thus include;
collective bargaining and representation of workers. Allowing the workers to bargain the
conditions of employment, to raise their concerns, and to have a say on the matters within the
company especially those revolving around the automated systems makes it fairer during the
transitional stage (Nguyen & Tran, 2020). This approach thereby promotes teamwork among
employers and also employees and hence checks if the benefits of automation are thus well
18
distributed and check if the problems that may arise are solved together. Additionally, enhancing
labor relation regulation and employee rights may be useful in creating a fair and robust work
force to adapt to technologically induced changes in the agri-business chain (Rodriguez &
Martinez, 2022). Through addressing such policies in advance, governments therefore create a
positive framework for long-term development, where automation is thus used to increase
output, but also address people’s needs and also develop effective social structures in rural areas.
Lastly, reforming the labor laws and also regulating employees’ rights regarding artificial
farming, governments will hence promote positive development with technological initiatives in
agribusiness and also protect humans being from being distanced from job market opportunities
due to technology. It becomes critical in these situations to take an approach that is all-
encompassing in order to effectively address all the factors involved in automation while at the
same time trying to make the transition as equitable as possible for all those involved in the
agricultural value chain.
6.3 Education and Training Programs
Lectures and training’s, therefore, plays an important role in helping the human resource in
agribusiness to be ready to face and exploit the automation revolution. Due to the advancement
in technology that has now posed its effects on the agricultural sector, there is a need to train the
workers and provide them with knowledge for new tasks in the technologically advanced
workplace. Firstly, one has to introduce curricula with a focus on emerging technologies as the
necessary course of the global development. This include; Robotics, Data analysis and especially
precision agriculture technologies, which are fundamental in the process of advancing farming
techniques in the current society (Chen and Zhang, 15 December, 2020). Training methods
should be developed in cooperation with government authorities and key business industries,
enrollment in educational institutions should create training programs. Such programs should
also accord adequate emphasis to showcasing the practical applicability of such systems
alongside focusing on the provision of hands-on experience so as to guarantee that the workers
possess adequate competency in the utilisation of these systems. In addition, the provision of
training interventions, which may occur in nature of informational and on the job training,
enables the workforce update itself on quickly changing technological fields. Training activities
should be tertiary, so the employees would be up-to-date with new technologies and be capable
to compete in the market, throughout their working experience (Nguyen & Tran, 2020). This
could be short term courses, seminars and certification that targets promotion of automation and
technology in farming. Education and training are not solely a means of acquiring the relevant
technical know-how but also to develop an innovation mindset among the workers in agriculture
business. Through encouraging learning, the requisite skills for the working environments can be
retained by the stakeholders, hence, apply changes as necessary (Rodriguez & Martinez, 2022).
More discussion and also cooperation between researchers, policymakers, and hence businesses
are thus required to meet the demands of agricultural businesses in terms of preparing
educational programs. This thereby makes it possible for these stakeholders to discuss possible
new and hence innovative trends in the economy, recognize set trends in regard to needing
19
skilled personnel and consequently align their educational services providers. This way one is
therefore assured that all educational investments provide the best returns for the worker as well
as the agricultural sector as a whole (Smith & Jones, 2020). Education and also training remain
the critical foundation that should thus support the preparedness of an agribusiness workforce for
automation. Therefore, skill training interventions such as micro-learning can help equip the
workers with all the essential skills, knowledge as well as being adaptable thus ensuring that the
stakeholders prepare for a skilled workforce in the ever-changing agricultural environment for
growth, innovation, and sustainable future.
6.4 International Comparisons and Best Practices
Analysis of comparative experience with the use of automation in the agricultural industry and
also the identification of recommendations and hence practices in this area can be thereby used
to develop effective policies and also strategies that will help to thus increase the positive impact
and hence reduce the negative effects of automation on this constantly growing industry. Policy
makers and industries in various countries have adopted different environments to incorporate
automation technologies in agriculture and such practices offer lessons to nations. To illustrate,
there are countries that have adopted elaborate support measures that seek to encourage the
implementation of automation, for example. These programs usually feature special privileges of
financing, for instance, grants and taxation alleviation to support the purchase of such
innovations (Smith & Jones, 2020). Also, enhancements in some infrastructure in the rural areas
such as high-speed internet and reliable power supply are essential for the independent
application of automation technologies in agricultural operations (Chen Zhang, 2020). It also
thus entails the creation of other structures that would hence encourage the use of the technology
and also at the same time having structures that support the functioning of modern agriculture.
However, there are specific measures tied to giving employees the desired training need to
prepare for automation. Advanced countries that have been able to adopt this kind of technology
in their agriculture sector have given emphasis to the education and training for the skilled
operations for the technological kind of environment required in the agricultural sectors. Such
programs include Robotics, Data Analysis, and Agri-Technology to ensure that the employees
who will be working alongside the automated systems can competently manage them (Nguyen &
Tran, 2020). Studying benchmarks of the advanced agribusiness organizations also offer sensible
examples of additional implementation of the automation useful. As such, analysing how these
types of businesses have dealt with such issues and benefited from other opportunities, policy-
makers as well as industry players can learn the best strategies to embrace technology, manage
the human capital and promote sustainable agriculture (Rodriguez & Martinez, 2022). It is
important therefore for various stakeholders involved in service delivery in the school health
sector to thus exchange information and also practices in order to spread such approaches all
over the sector and encourage innovation among change implementers. This way, through
studying the best and also worst practices worldwide, the policymakers will be able to craft
policies and hence regulations that can thus positively impact the agribusiness industry in the
course of being challenged by automation and also other technological instances. By applying
20
this approach, productivity and hence competitiveness are thus improved while at the same time
guaranteeing distribution of the positive effects of automation, thus promoting a sustainable
economic development of the rural areas.
21
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