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03.31.22

AI and cannabis farming—A joint effort

By Paulina M. Starostka

We previously covered the expansion of artificial intelligence (AI) into the agriculture field, so it is fitting that the cannabis industry—another agribusiness—is taking advantage of how AI can scale cannabis cultivation, increase profits, and improve the user experience. The cannabis industry is incorporating AI in more than one way, showing a multifaceted approach to combatting several hurdles.

AI has been assisting with crop production. Algorithms are used to compute optimal growing conditions, including temperature, nutrients, light exposure, and watering levels. AI is also helping uncover and combat crop diseases, which helps reduce the spread of diseases and loss of crops, resulting in healthier crops, increased yields, reduced waste, and greater profits.

On the medical cannabis side, AI is also being used to pinpoint the particular indications that certain crops can be used for. For example, MedicascyAI, an AI solutions network, has been considered as a means to make predictions about the safety and efficacy of the molecule’s use for targeted indications through the analysis of the chemical structure of small molecules, including those found in cannabis. Not only could this help predict which crops to grow but it could also improve the efficacy for those relying on cannabis for medical purposes.

AI is also being used to improve packaging, labeling, and the consumer experience. Algorithms knowledgeable about the various cannabis strains can be used to monitor the products being distributed into the market, which helps consumers get the product they expect and ensure compliance with any applicable laws. Analysis of the users can also help improve experience—by analyzing various factors, such as food consumption, previous cannabis use, environment, etc., users can have a more tailored experience.

While the benefits of utilizing AI throughout industries seems like a no-brainer, there are a number of hurdles still facing AI, including: costs and access for smaller companies, monopolization of datasets impacting industry-wide machine learning, access to user health records, and ability to protect valuable AI through intellectual property laws.

Nixon Peabody’s Cannabis team helps companies stay ahead of legal and regulatory changes so that they can thrive in this emerging market, despite its complex regulatory challenges. As always, we will continue to monitor developments in industries expanding on AI and accompanying changes to the US IP legal system.

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Paulina M. Starostka

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