Rudy Lai

AI @ Deere & Co.

Agricultural and construction equipment
Industry
Last updated
July 3, 2025 at 10:44 AM

Summary

  • John Deere has progressively expanded the use of AI and machine learning since at least 2018, evolving from initial 'see and spray' real-time weed detection technology to fully autonomous tractors and integrated farm ecosystems by 2025.
  • Key leadership figures such as CTO Jahmy Hindman have driven Deere's AI strategy, which now includes partnerships with technology leaders like NVIDIA for advanced edge computing, and investments up to $300 million in AI and machine learning capabilities.
  • The AI implementations have focused on precision agriculture (e.g., analyzing grain quality, optimizing chemical use), addressing labor shortages with autonomous equipment, and improving farm productivity and sustainability, culminating in leadership in autonomous farming technology and digital operational tools like 5G connectivity and digital twins by late 2025.

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5 AI Use Cases at Deere & Co.

Precision Spraying
2025
Customer Facing
Traditional
Generative
Agentic
Outcome
Costs
John Deere uses AI-driven computer vision and machine learning to identify weeds in real-time and apply herbicides precisely only where needed, reducing chemical waste and environmental impact. [1][2][3]
Autonomous Operations
2024
Customer Facing
Traditional
Generative
Agentic
Outcome
Costs
John Deere integrates AI technologies such as computer vision and machine learning to enable fully autonomous tractors and machinery to perform field operations without human intervention, addressing labor shortages and increasing efficiency. [1][2][3]
Labor Shortage Mitigation
2024
Customer Facing
Traditional
Generative
Agentic
Outcome
Costs
AI-powered robotics and autonomous equipment help overcome agricultural labor shortages by automating farm tasks, enabling farmers to operate more efficiently despite workforce constraints. [1][2][3]
Data-Driven Insights
2023
Customer Facing
Traditional
Generative
Agentic
Outcome
AI algorithms and machine learning techniques analyze large datasets collected from farm machines to provide actionable insights to farmers, helping optimize planting, fertilization, and harvesting strategies. [1][2]
Crop Quality Optimization
2021
Traditional
Generative
Agentic
Outcome
Revenue
Machine learning analyzes grain quality during harvest, allowing automatic adjustment of operating parameters to minimize damage and maximize crop yield. [1]

Timeline

2025 Q4

2 updates

Enhanced autonomous field operations with computer vision powered driverless tractors; implemented productivity tools including 5G, data analytics, and digital twin technology in manufacturing.

2025 Q3

3 updates

John Deere leverages 36 cameras with advanced ML to refine 'See and Spray' precision, reducing chemical use and enhancing crop yields; CTO Jahmy Hindman highlights AI's divergent approach from Silicon Valley norms.

2025 Q2

4 updates

Scaled AI innovation to facilitate labor shortage solutions, broaden adoption of 'See & Spray' technology, enhancing precision weed targeting and improving operational productivity.

2025 Q1: no updates

2024 Q4

1 updates

Implemented generative AI solutions for enhanced database access to support operational efficiency and data-driven decision making.

2024 Q3

2 updates

Advanced integration of AI data, edge computing with NVIDIA partnership, and $300 million investment in AI/ML; strengthened position as leader in precision agriculture.

2024 Q2: no updates

2024 Q1

2 updates

Developed robotics and AI solutions primarily targeting agricultural labor shortages, delivering productivity enhancements and modernized farm management.

2023 Q4

1 updates

Announced preparations for a fully autonomous farm by 2030, emphasizing AI technologies such as computer vision and machine learning to meet global food demands.

2023 Q3

2 updates

Focused on end-to-end AI adoption from factory automation to autonomous field operations; deployed AI-driven seeding machine targeting weeds with lasers.

2023 Q2

3 updates

Expanded AI integration in farm machines delivering data insights and automation; launched AI-powered features like ExactShot for optimized inputs.

2023 Q1: no updates

2022 Q4: no updates

2022 Q3: no updates

2022 Q2

3 updates

Debuted a fully autonomous tractor at CES 2022; advanced AI and automation positioned John Deere as a major AI innovator in agriculture.

2022 Q1: no updates

2021 Q4: no updates

2021 Q3

1 updates

Applied machine learning to analyze grain quality and adjust harvesting parameters automatically to reduce damage and improve yield.

2021 Q2

1 updates

Committed hundreds of millions of dollars shifting corporate culture to deeply integrate AI as a core operational transformation.

2021 Q1: no updates

2020 Q4: no updates

2020 Q3: no updates

2020 Q2

1 updates

Reinforced position on AI, ML, and computer vision as cutting-edge technologies in agriculture to harvest efficiencies and productivity gains.

2020 Q1: no updates

2019 Q4

1 updates

John Deere launched its 'Farm Forward' campaign focusing on deploying AI across machines towards an autonomous farm vision.

2019 Q3: no updates

2019 Q2: no updates

2019 Q1: no updates

2018 Q4: no updates

2018 Q3: no updates

2018 Q2: no updates

2018 Q1

1 updates

John Deere introduced 'see and spray' technology utilizing machine learning to process real-time images for weed identification and targeted spraying.