Agribusiness is on the cusp of digital transformation

Increasing consumer demand for greater food quality, nutritional content and sustainability has sparked a transformation across agriculture as growers and food companies strive to meet these heightened expectations while improving output.

While various solutions for using field and crop data to improve business profitability and yield larger harvests have been proposed, certain barriers have led growers to resist digital transformation and instead stick with traditional techniques. For example, many of these approaches place too much dependence on the grower taking manual steps for data inputs to make the solution function easily or rely on remote internet accessibility to view or access the necessary information. Consequently, tremendous amounts of agricultural data are generated, but never used.

screenshot showing the IBM Weather Operations Center dashboard
Worker in indoor farm monitoring plants with a tablet

Make faster, smarter decisions for agriculture

IBM Agriculture helps overcome obstacles to digital transformation by combining the power of Artificial Intelligence (AI), data analytics and predictive insights with unique agricultural Internet of Things (IoT) data, the expertise of veteran food and agribusiness industry leaders and decades of IBM research.

The result is a platform of customized low-cost solutions that help stakeholders across the ecosystem to make faster, more informed agricultural decisions.


Increased profitability

Execute analytics on satellite imagery, weather, supported agricultural equipment data and more, to gain insights that help yield more bushels or tons per hectare across targeted crops.

Improved sustainability

Gain deeper insights into factors such as crop input optimization, energy consumption, land and water use, soil conservation, soil carbon content and greenhouse gas emissions.

Higher quality crop output

Apply unique agricultural data insights to generate higher quality crops such as increased protein content in barley or sugar content in beets.

Improve decisions across the entire agriculture ecosystem

IBM Agriculture also automates data handoffs between stakeholders across functions, creating a more transparent, connected ecosystem and driving value for non-growers in roles such as:

  • Food producers: Adopt integrated supply chains with greater harvest timing and volume predictability.
  • Commodities traders: Encourage price stability for growers by using custom predictive queries on multi-layer geospatial analysis.
  • Agriculture lenders: Provide lower-friction loans for growers by validating yield performance versus potential.
  • Insurance agents: Generate smarter rates for growers by using validated EFR data to improve risk insight and claims processing.
  • Governments: Improve food independence strategies by giving growers and agencies a common set of tools.

Cranberry bog operation

Next steps