AI in the Green Industry
When ChatGPT was released in November 2022, AI exploded into public consciousness. We watched it transform, seemingly overnight, from a technology that was once only available to researchers in labs into one that’s now widely accessible to the general public. Over the past three years, every industry, including our own, has clamored to learn how we can implement it in our own businesses as we look for ways to increase efficiency, automate repetitive tasks, and, ultimately, revolutionize the way we analyze data. I, for one, have eagerly read every article about the use of AI in the green industry that’s landed in my inbox. I’ll admit that, early on, I was often disappointed by the lack of specifics in those articles; it felt like everyone wanted to talk about AI’s potential but couldn’t point to practical ways it could be put to use. But, behind the scenes, many companies have been busy developing AI-powered solutions for the greenhouse and nursery industry over the past few years.
Some of the lowest hanging fruit when it comes to opportunities for implementing AI in any type of business often revolves around customer service and content creation. (We’ve heard it’s popular for blog-writing as well.) Chatbots can certainly be a valuable tool when it comes to answering common questions and offering 24/7 support, just as automated assistants like Copilot can help with drafting routine emails, refining the tone of a message, or simply looking for grammatical mistakes. As for content creation, we can use AI to whatever degree we feel comfortable with. It could be as simple as using it in a brainstorming session to come up with ideas, or something more complex, like generating images for a marketing campaign. But, at least for now, AI isn’t a replacement for human-driven ideas or service. And, for what it’s worth, I will personally never use AI to write.
When it comes to the green industry, some major greenhouse growers are already beginning to implement cutting edge AI technology. Leading AI companies like Source.ag, IUNU, Adaviv, and Blue Radix, just to name a few, have made great strides in developing autonomous irrigation and climate control systems, tracking crop health issues to facilitate more efficient IPM strategies, and using predictive analytics to effectively scale businesses. Due to their nature, greenhouse operations lend themselves more easily to automation than nurseries do in many ways, and so it makes sense that they’re leading the charge in this way.
The ways we’re seeing AI integrated into nursery operations are just as exciting, but different, and they’re often associated with drones and robot technology. Burro is currently one of the most recognized names in the industry when it comes to autonomous robots, and the company was recently named Greenhouse Grower’s 2025 Technology of the Year. Burro robots use computer vision, GPS, and AI to independently move plants around the nursery, and the technology is being adopted on a large scale by fruit, vegetable, and nursery growers. Drones don’t only save time and labor when it comes to counting inventory, but they provide a number of benefits when it comes to chemical application. The precision they offer can reduce the volume of chemicals needed and limit employees’ direct exposure to pesticides.
Naturally, we’ve had many conversations regarding our next steps when it comes to implementing AI here at Mariani Plants. While it’s tempting to jump in with both feet, there are benefits to waiting for lower-cost and more advanced solutions as AI continues to mature and evolve. For some companies, adopting the newest technology early on is the right choice, and for others, it’s more practical to wait until the time is right. Taking a patient approach can also mean less risk, and we can learn from the challenges that early adopters face. We each need to prioritize and identify the areas that would benefit most from AI technology in our business. One function of AI that we’re especially excited about is the use of predictive analytics. But the cost of implementing this type of technology can be high and requires the integration of predictive AI into existing sales and inventory software. So, we’re taking a methodical approach when it comes to AI. We think the key is to experiment with AI tools that make sense right now while exploring other opportunities so that we can be prepared to integrate more fully in the future.
