Over the last couple of months I have been looking at vertical software companies from other industries, like healthcare, services, restaurant management and construction and their approach, offering and vision surrounding artificial intelligence integration into their offerings.

The aim was to get a baseline for what agribusiness software companies might do, and look at some of the products they might offer to ag retails and crop input manufacturers and positon themselves moving forward.

This week I am publishing a White Paper exclusively for Upstream Ag Professional members that shares some of the learnings from other industries, what that means for agribusiness software strategy and where we are headed. At the end I look at some of the capabilities and considerations ag retailers need to be aware of today.

Index of the White Paper

1.  Why Vertical AI Matters Now

• Why Vertical Beats Horizontal

• The Agribusiness-Specific Context

2. Lessons from Other Industries

• Procore and the Connected Platform

• Toast and Multi-Product Expansion

• Service Titan and Atlas

3. The Current Agribusiness Software Landscape

• Core Systems of Record (ERPs)

• Engagement and Action Platforms

• Data and Intelligence Providers

• Agronomy and Supply Chain Platforms

4. The Evolution: Systems of Record to Systems of Action

• Phase 1: Systems of Record

•  Phase 2: Systems of Engagement

• Phase 3: Systems of Action

• The Context Graph

5. What This Means for Agribusiness

• For Ag Retailers

6. Interface Concepts for AI in Ag Software

• Design Principles for Ag AI Interfaces

•  Interface Concept

7. Strategic Recommendations

8. Conclusion 

Executive Summary

The agricultural industry is evolving for a number of reasons. Some of these reasons include software evolution.

While ag retailers have invested in enterprise software for decades, the emergence of vertical artificial intelligence presents a new opportunity to change how agribusinesses operate, compete, and create value on top of the software they use.

This white paper examines the strategic implications of vertical AI for agribusiness professionals, drawing lessons from other industries that have already undergone this change. Construction, restaurants, and services offer parallels for how systems of record evolve into systems of action – changing how individuals and businesses operate on a day to day basis.

The thesis is that software companies that embed AI deeply into industry-specific workflows will capture disproportionate value moving forward and empower businesses like crop input retailers to win.

For ag retailers, this means accessing tools that deliver more than digitizing existing processes toward reimagining how recommendations are made, how fleets are dispatched, how farmer programs are managed, and how workflows throughout the value chain are orchestrated and coordinated.

Key findings from this analysis include:

• Systems of record (ERPs like Agvance, Merchant Ag) remain foundational but are insufficient alone. The next competitive advantage comes from systems of action, towards systems of intelligence with embedded AI that execute workflows autonomously.

• AI agents represent a new tool that can handle repetitive cognitive tasks: processing orders, dispersing recommendations, coordinating logistics, and managing customer communications and advertising initiatives.

• The agribusiness software landscape is fragmented across ERPs, agronomic software, CRMs, and various specialized tools. AI can create an coordination layer that connects these systems.

•  Interface design matters enormously. The winning platforms will meet users where they work: in truck cabs, warehouses, field offices, and manufacturing facilities, not necessarily a chat-based interface.

• First-mover advantage is significant but not insurmountable. The key is moving deliberately: mapping workflows, piloting solutions, and building institutional capability.

The organizations that act decisively from control points have the right to win and influence the value chain. Those that wait risk operating with legacy systems while competitors achieve fundamentally different levels of efficiency and insight, enabling them to manage costs and improve outcomes for their teams and customers.

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