AI in Agriculture: From the Lab to the Land.
Artificial intelligence is no longer an experiment at the edge of the field — it is becoming the infrastructure of how we grow, inspect, and govern food. This is where I track that shift, and what it means for the people doing the work.
What "AI in Agriculture" Actually Means
AI in agriculture is the application of machine learning, computer vision, and data systems to farming and the wider agrifood chain — from a seedling in a nursery to produce on a shelf. It spans precision agriculture, autonomous machinery, post-harvest quality control, yield forecasting, and the policy that decides who benefits from all of it.
Dr. Maryna Kuzmenko is an AI in agriculture speaker, advisor, and educator who works at exactly that intersection — technical innovation, public policy, and commercial viability. The throughline of this work is human-first: technology should widen access for smallholders and specialists alike, not just optimise the largest operations.
Precision Agriculture
Sensors, drones, and satellite imagery turn a field into data — letting growers target water, nutrients, and crop protection with far less waste. The frontier now is making these tools usable on small and mid-sized farms, not only industrial ones.
Computer Vision & Post-Harvest
Non-destructive AI sensing grades produce, predicts shelf-life, and standardises quality for global trade. This is the core of my own technical work — automating quality control across agrifood and forestry nurseries.
Agrifood Policy & Governance
Adoption is decided in policy rooms as much as on farms. Data ownership, algorithmic accountability, and equitable access are the questions that determine whether AI in agriculture is a public good or a new divide.
Responsible & Human-First AI
Bias, data privacy, and the changing role of the farmer are not footnotes. Responsible deployment means software that augments human judgement and keeps the people who feed us at the centre of the design.
Women in AgTech
Diversity is a prerequisite for good agricultural innovation, not a nice-to-have. I write and speak on navigating the male-dominated intersection of agriculture and technology — and why it matters for what gets built.
Education & Adoption
The gap between what AI can do and what farms actually use is mostly a learning gap. Making complex tools accessible — through courses, talks, and plain language — is how adoption really happens.
Where This Work Lives
I publish across formats so the conversation reaches policymakers, founders, and students alike. If a brief on the page below is useful, the long-form version is usually one of these:
- AI in Agriculture newsletter: analysis for 15K+ readers on LinkedIn.
- YouTube: talks and explainers for 3K+ subscribers.
- Udemy course: 3K+ students in the AI in Agriculture programme.
- On stage: see my AI in agriculture keynotes and book a session.
- With your team: bespoke strategic advisory on responsible AI adoption.
AI in Agriculture FAQ
What is AI in agriculture?
AI in agriculture is the use of machine learning, computer vision, and data systems across farming and the agrifood chain — including precision agriculture, autonomous machinery, post-harvest quality control, yield forecasting, and supply-chain optimisation.
Who is Dr. Maryna Kuzmenko?
Dr. Maryna Kuzmenko is an AI in agriculture speaker, advisor, and educator, and a LinkedIn Top Voice on the subject. She works at the intersection of computer vision, agrifood policy, and commercial deployment, and teaches a course on AI in agriculture reaching students in 119 countries.
What are the main applications of AI in agriculture?
The most established applications are precision agriculture, computer-vision quality control for produce and nursery stock, predictive analytics for yield and risk, autonomous machinery, and decision support that helps growers reduce waste while improving output.
Where can I learn about AI in agriculture?
You can follow the AI in Agriculture newsletter on LinkedIn, watch explainers on YouTube, or take the structured Udemy course. For organisations, advisory engagements offer a tailored route to responsible adoption.
How can I book Maryna to speak on AI in agriculture?
Visit the speaking page to see signature topics and formats, then use the contact page to check availability for your event.