The size of the AI in agriculture market was USD 1,254.6 million in 2022, and it will advance at a CAGR of 26.7% in the years to come, to reach USD 8,308.5 million by 2030, as per a market research company P&S Intelligence.
The service category will experience the
faster growth because of the increasing requirement for managed services by
farmers for tracking the processes and activities of sensors and managing large
data sets associated with crop health.
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| AI in Agriculture Industry Revenue Estimation and Demand Forecast to 2030 |
The product category dominates the
industry because of the surging necessity for software to control and guide the
devices fitted in an agronomical environment for performing numerous advanced
cultivation practices.
The machine learning category has the
largest share, of about 60%. This is because of the growing acceptance of this
technology by organizations and farmers for enhancing crop productivity with a
combination of agronomical sciences and data technologies. It will hold the
same position in the years to come, because of its rising usage in agricultural
applications, including crop and field management.
Furthermore, ML has been extensively deployed
in Europe and North America because of its high acceptance in agricultural
robots and precision farming.
Moreover, precision farming had the
largest share, of around 35%, in 2022. This is because of the growing requirement
for an optimal yield with limited resources and reduced cost of crop
production. Similarly, the rapidly increasing use of IoT in the agriculture sector
is driving the precision farming industry.
North America leads the AI in
agriculture market, and it will hold the position in the near future, with
a value of about USD 4 billion. This is attributed to the high acceptance of
innovative technologies in the farming industry for maximum productivity. Moreover,
the players are offering services to regional consumers, in partnerships with
other players.
Advanced technologies, such as IoT
and ML, in combination with computer vision, is being used for numerous agronomic
applications, including precision farming, livestock management, greenhouse
management, and soil management.
APAC will have the fastest growth in
the years to come. This has a lot to do with the increasing acceptance of smart
farming techniques, including agronomic robots, drone analytics, and precision
farming. In APAC, China is the major contributor because of the quick acceptance
of advanced techniques in its enormous agricultural sector.
The increasing usage of robots in
agriculture is a main trend. With the growing implementation of modern technology
in agriculture, farming practices are increasingly becoming sophisticated.
Additionally, with the increasing global population, lack of obtainability of
farm workers, and automation in the agriculture sector, there is an increase in
the usage of agricultural robots all over the world.
It is because of the increasing penetration of
IoT in farming sector that the demand for AI solutions in agriculture will
increase all over the world.
