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Technology's constant innovation has forced many industries to start adapting to mechanical and automated processes to take advantage of these brand new economies of scale. In the last decade or so, this technological integration has been driven by machine learning and artificial intelligence (AI), the next step in enhancing the precision, automation, and productivity of industrial processes. The cannabis industry is no exception. In an environment where figures like temperature and THC concentration can make or break an entire batch of product, AI has become an integral part of industrial cannabis cultivation.
But what does AI offer cannabis cultivation compared to other industries? Below is a breakdown of how and why artificial intelligence is being utilized by modern cannabis producers.
While artificial intelligence may have started off as a concept and a small-scale demonstration of high-end computers, its recent developments have made it one of the largest growing industries in tech. Not only that, but the benefits extracted from AI are so vast, it has entered almost every industry imaginable, from waste management to retail. But the industry where AI has seen the most opportunity is, arguably, manufacturing.
In the manufacturing industry, AI can be used to identify, manage, and monitor almost every mechanical task in the production journey. Due to its processing capabilities, AI can be used to evaluate, for example, every packaged product that reaches the final stage of inspection. Artificial intelligence, in this case, can be used to judge the quality of packaging and to identify any mistakes. It can also then record the number of packages that satisfy each tier of quality. Information this valuable can be used to reduce the number of errors and improve the cost efficiency of one's production. Minimizing cost, as any business leader knows, means maximizing revenue.
Where AI is most valuable is when it can automate simple but burdensome tasks on a particularly large scale. The volume of data that AI can process at a single time is what makes it extremely valuable in more industrial operations like cannabis cultivation.
From greenhouse monitoring to seed-to-sale tracking, machine learning can be used as a technological solution in almost every stage of the cannabis retail chain. One of the largest complaints regarding the controlled environment agriculture is that it consumes too much energy. Unfortunately, cannabis cultivation, due to the nature of plants, requires a closely controlled environment in order to ensure a certain quality of harvest. This is because some of the cannabinoids found in hemp will be affected by the plant's growing conditions, i.e., it could negatively influence the concentration of cannabidiol (CBD) or other valuable chemical components. Outdoor cannabis environments, particularly in more northerly regions, are very risky and can limit your production periods to specific months of the year. Therefore, a lot of cannabis farmers have resorted to eating a thinner profit margin due to the costs of maintaining a controlled agricultural environment. Fortunately, AI can act as a solution.
Companies like Grownetics, MotorLeaf, and others have created machine learning platforms to help cannabis cultivators optimize their production process and minimize the costs of indoor operation. These AI solutions involve a combination of high-resolution sensors, automated monitoring, and management systems, as well as a variety of plant tracking devices. Together, these platforms can help inform the producers with real-time information on every influencing factor of plant production. For instance, by monitoring the growth rate and nutrient deficiencies of different plant batches, these AI systems could help producers identify and solve problems before they escalate. If one batch has an above-average number of pests, such as insects or bacteria, then it may require additional pesticides and decontamination.
The greatest benefit of machine learning is that one's investment in it improves over time. As artificial intelligence becomes more familiar with a process or procedure, it can become more efficient and more accurate in its decision-making and data analysis. Both are instances that save a company time and money. Two things that any profit-maximizing firm is looking to accomplish on a regular basis. For example, Green CulturED recorded that its clients, on average, noticed a 50 to 70% reduction in harvest forecast errors after they integrated AI into their production process. And that was just after the first year. In the second year of AI adoption, the technology can reduce errors by more than 70%.
The difficult part with integrating artificial intelligence into agricultural production is that every firm is different, along with its operations, machinery, and facilities. But this also helps highlight the importance of AI if a firm has multiple cultivation centers with different environments and produce. Machine learning is now an integral part of cannabis cultivation; which industry will it take over next?
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