40 Experts weigh-in on how AI will change Farming, Food Systems & Agribusiness
What does AI really mean for agriculture and food? Where should leaders focus first? And what are the hidden risks?
To answer these questions, the two of us, Aidan Connolly (AgriTech Capital) and John Power (LSC International), brought together 40 of the top experts from AI or from the global agri-food ecosystem. CEOs, researchers, entrepreneurs, investors, and advisors and asked them six essential questions to gain their collective wisdom. Their views are illuminating, occasionally provocative, and consistently practical. Here’s how they answered.
Q. 1. How Will AI Transform the Agri-Food Sector?
AI is not just a better calculator—it’s a new nervous system for the food system. Key insights:
From instinct to prediction: AI will help producers, processors, and retailers make decisions proactively rather than reactively, forecasting demand, optimizing logistics, managing input use, and even shaping product innovation.
Sylvain Charlebois and Jack Bobo emphasize the transition from forecasting yields and consumer behavior to managing input timing and optimizing logistics.
From silos to systems: AI can integrate farming, processing, retail, and R&D in ways that create new business models—not just better margins.
As Shail Khiyara notes that AI will allow companies to “reimagine how food is grown, moved, and consumed.”
Winners and laggards: Early adopters will build data moats and reconfigure the competitive landscape, while others may struggle with inertia or lack of infrastructure.
Damien McLoughlin warns that transformation may be uneven, with benefits accruing first to those in row crops or with data-rich operations.
Bottom line: AI is a strategic reset for the Agri-Food sector—not a tech upgrade.
Q. 2. Which Jobs Will Be Most Affected?
Some roles will shrink. Others will evolve. New ones will emerge. Key insights:
At risk: Routine manual and digital jobs—like data entry, produce grading, basic logistics coordination—will likely be automated.
However, Ash Sweeting notes this is more complex in agriculture than in other industries.
In demand: AI-savvy agronomists, supply chain strategists, digital farm managers, and AI ethics officers.
Charlebois cites “farmers who can code” (Charlebois), and Rogge-Fidler cites, “trusted advisors” who evolve into AI-enhanced consultants (Rogge-Fidler)
Not eliminated—but enhanced: Trusted advisors, extension specialists, and decision-makers will be augmented by AI co-pilots.
Mary Shelman and Julia Somerdin also note that AI will allow mid-level managers to oversee broader spans of control, expanding their role and potentially reducing layers of management.
Bottom line: The best people will become better, but teams must upskill now to stay relevant.
Q.3. What Should CEOs Be Doing?
Leading the AI transition is a job for the CEO—not just the CTO. Advice from the panel:
Own the strategy: Don’t treat AI as an IT project. Integrate it into corporate strategy and value creation.
Shail Khiyara warns “Don’t treat it like an IT project…It’s a strategy shift.”
Start small, aim big: Focus on strategic use cases with clear ROI—like demand forecasting, inventory optimization, or customer insights.
Rob Dongoski and AJ Shelman argue that the focus should be on solving meaningful business problems
Build internal AI fluency: Leadership teams must understand what AI can and cannot do. Invest in training and reverse mentoring.
Claudia Roessler, Jack Bobo and others recommend scenario planning, reverse mentoring, and cross-functional teams.
Embed ethics early: Governance, transparency, and social equity must be part of the roadmap—not an afterthought.
Bottom line: AI is a leadership challenge, not just a technology one.
Q.4 What Are the Concerns or Risks?
AI brings disruption—and not just the good kind. Key concerns raised:
Hype vs. reality: Many tools labeled “AI” are rebranded statistics. Don’t get distracted by buzzwords.
Shouman Datta and Jayson Lusk warn that “misaligned expectations” are a real risk
Data inequality: The biggest players may capture the most value, leaving smaller producers and rural communities behind.
Jonah Kolb, Joseph Byrum and Rory McInerney all noted the potential for widening inequality and concentration of resources.
Ethical and social impacts: Job displacement, biased algorithms, loss of local knowledge, and data sovereignty are real risks.
Charlebois, Sweeting, and Shelman emphasized the need for “inclusive AI” that empowers people rather than replacing them.
Overdependence: What happens when the systems break—or get hacked?
Shelman notes cybersecurity as a concern, while Roessler notes the risk of lack of interoperability between data sources.
Bottom line: Responsible adoption is essential. Build trust, protect equity, and proceed with clear direction.
Q.5. What Should Executives Do in the Next 6 Months?
Speed matters—but clarity matters more. Immediate actions recommended:
Use AI early and often: Experiment with tools like ChatGPT, image classifiers, or precision Ag dashboards. Learning comes from doing.
McLoughlin recommends dedicating 10% of one’s time to hands-on practice, while Julia Somerdin recommends working with AI daily.
Audit your data: Clean, structured data is the engine of AI. Know what you have—and what you need to collect.
John Herlihy, Shelman and Kolb recommend starting with a data audit and digitizing everything you can.
Pick a use case: Focus on 1–2 high-impact pilots. Measure ROI. Share learnings across teams.
Bobo and Byrum suggest starting with high-value, low barrier to entry areas such as yield prediction, inventory optimization, and market intelligence.
Invest in talent: Bring in outside expertise as needed, using AI-native talent to blends Ag expertise with digital fluency- but retain strategic control.
Aaron Beydoun dictum is “Don’t try to do it all in-house.”
Establish ethical frameworks: Transparency, data privacy, and governance need to be embedded from the start.
Hadar Sutovsky, Jose Tomas and Pia Brantgarde all note the ethical challenges of AI tools and processes.
Bottom line: The race is on. Don’t over-plan. Start acting—and learning.
Q. 6. Final Reflections from the Experts
We are at the beginning of a long-term transformation
1) “AI will not replace humans. But humans using AI will replace those who don’t.”
2) “If you wait for a perfect roadmap, it will be too late.”
3) “Transformation starts with culture, not code.”
4) “Treat AI like electricity or the internet: foundational, ubiquitous, and non-optional.”
Extra question = Any Closing Thoughts?
The future of Agri-Food is not about who has the most land or the biggest factory—it’s about who can learn and adapt the fastest. AI offers a generational opportunity to build a food system that is smarter, more resilient, and more equitable. But that future depends on choices leaders make today. It is interesting to see that our experts didn't mention sustainability, ESG. Is this a reflection of that they were mainly North American based or that not enough see the overlap between AI strategies and sustainability. More to ponder.
Will you be the one to lead that change—or be forced to follow it?
And yes – before you ask AI LLMs (eg. ChatGPT) were used to create this blog, the analysis and chose the quotations!
Many thanks for all the contributions from our AI expert opinions on applications food and farming and from our food and agribusiness experts on how AI will transform the food chain, (alphabetically) Aaron Baydoun, Adrian Percy, AJ Shelman Anthony Howcroft, Ashley Sweeting, Bonnie Brayton, Claudia Roessler, Damien McLoughlin, David Hunt, Dean Cavey, Ed Eggers, Ejnar Knudsen, Hadar Sutovsky, Haven Baker, Jack Bobo, Jayson Lusk, Jean-Martin Bauer, Joe Jennings, João Ribeiro da Costa, John Foltz, John Herlihy, Jonah Kolb, Jose Fernando Tomás, Joseph Byrum, Julia Somerdin, Kevin Gohil, Marcos Fava Neves, Mary Shelman, Naira Hovakimyan, Pia Brantgärde, Rahul Mehendale, Rob Dongoski, Robert C. Wolcott, Rory McInerney, Shail Khiyara, Shari Rogge-Fidler, Dr. Shoumen Datta, Dr. Sylvain Charlebois, Tim Hassinger, Wolfram Schlenker
If you’re working on AI strategy in agriculture or food systems and would like to connect or exchange ideas, drop a message or comment below.
POST-NOTE
The final post from our AI survey is now live. It offers thoughts & conclusions on what you should do to prepare for the AI Bullet train
