How AI Forecasting Can Help Cannabis Companies Navigate the Future

How AI Forecasting Can Help Cannabis Companies Navigate the Future

September 20, 2022

Want to grow more consistent strains of cannabis, find the best product mix or keep up with regulatory changes? Artificial intelligence (AI) can help.

AI has become ubiquitous in our daily lives, and the technology has numerous applications for the cannabis industry in everything from plant nutrition to distribution. No longer an exotic proposition, the use of AI is a common strategic decision in nearly any business scenario. Here’s how all types of cannabis organizations can use AI to make their business more competitive and scalable.

The Beauty of Predictive Modeling

AI enables cultivators, manufacturers, distributors and dispensaries of all sizes to produce a more consistent product, reduce overhead, streamline supply chains and much more. Cannabis businesses typically realize these benefits through varying applications of a single tool – predictive modeling.

Simply put, predictive modeling is the use of past data to figure out what’s going to happen in the future. Your business already generates immense amounts of data and will produce even more as your company matures. The beauty of predictive modeling is that it allows you to strategically leverage the data you already have.

Applications in Different Cannabis Verticals

The predictive modeling applications for cannabis are numerous, ranging from improved yields during cultivation to more accurate and effective financial planning. Here are just a few of the ways your company can utilize AI.


Use cases for AI in cannabis begin at the root of the industry – growing the product. Predictive modeling can help better forecast weather and anticipate how weather patterns will shift over time. You can combine this technology with machine learning and sensors that monitor pH, carbon dioxide and light exposure to maximize product yield. Unlike a Farmer’s Almanac of the past, these predictions update with every new data point, constantly adjusting to give you the best possible prediction.

By combining your models on weather patterns and the aforementioned sensors, you can automate the delivery of fertilizers and nutrients into the soil. As a result, you have a better understanding of how a plant is growing and can produce a more consistent and fruitful yield. This helps you establish your brand through more consistent strains and removes some of the guesswork as to why a plant grew the way it did.

When you can control these variables, and measure them, you’re forging the path to a more sustainable business because you can more accurately predict how much cannabis you can produce. You’re more scalable, better able to deliver on projections and have greater yield and consistency of plants.

Product mix

Your company has basic sales data that tells you the performance of certain strains, as well as assorted products such as pen cartridges or edibles. However, AI gives you the ability to analyze more data sets that sales data doesn’t provide. You can look at sales in comparison to production that year, external market factors and more in-depth purchasing behavior.

AI can offer you greater forecasting accuracy, which can help streamline your supply chain by perfecting product distribution and get items on the shelves based on customer demand. You can identify which products are critical to success and how to allocate the right amount of land to grow them. Maybe there’s a product you should get rid of, or one you need to increase production on.

Once your product is in the dispensary, you can determine whether you’re selling the right product for the right price. You can better track profit margins by analyzing how much effort goes into developing certain plants and how you can use those plants to create various products. You can also determine whether certain plants are better utilized to make pen cartridges, flower, edibles, etc.

Ultimately, AI allows you to look at ways to increase profit margins with your product mix. It’s demand forecasting for your customer base. You use historical data, monthly trends, seasonality and growth trajectory to know how much product you’ll need. This equips you to go to your distributor and cultivator with an accurate prediction on the demand for certain products in the coming year and how production will need to keep pace.

Inventory tracking

Since marijuana is a consumable and has a set shelf life in some of its forms, it’s important to allocate warehouse and inventory space appropriately. You should maximize short shelf lives while still being prepared for surges as they happen. By using improved data on which product types to make and financial forecasting to plan future sales, you can optimize inventory levels.

From a logistical and warehousing standpoint, you can also better predict the need for auxiliary supplies on items like fertilizer, nutrients, soil, equipment, etc. This enables you to reduce inefficiencies because something like heavy machinery could have a five-week turnaround. And not having a critical item could hold up your entire organization.

Staffing is another logistical issue that’s very difficult to manage, especially with seasonal workers making up a large part of the cannabis industry’s labor force. With a more accurate forecast on how much cannabis you should grow and the types and amounts of products you should keep on hand, you can reduce overhead by more accurately predicting the number of people you’ll need to hire at a given time, whether it’s to harvest crops or staff a warehouse.


Historically, distribution has been expensive and complex for the cannabis industry. Because traditional mail carriers won’t deliver marijuana, companies must put a lot of thought into their distribution operations.

Predictive modeling can optimize distribution networks and reduce fuel costs. You can use AI to map out your delivery network and find the most efficient routes – and even eliminate some delivery trips entirely. As your business grows, AI can play an even more vital role in helping you decide whether you need to add new delivery lines, trucks or distribution networks.

Should you open a new distribution center? Is a prospective retail location profitable? By introducing external demographic data sources into your analysis, picking the best retail locations for your product is no longer just guesswork. These are important questions that you can solve better and quicker with automated distribution forecasts, so you can scale in an efficient and controllable way.

Regulatory compliance

If your business operates in multiple states, each location has different and evolving laws and regulations. AI can help you monitor your contracts and your compliance with changing regulations without needing a human to go through them manually (and possibly make mistakes).

Additionally, as medicinal and recreational marijuana legalization expands nationally, you can use predictive modeling to estimate the size of new markets. So, you can forecast how profitable it may be to begin operations there and how effectively you can distribute to them. This gives you the opportunity to leverage new legislation to adjust your operations in new and changing markets.

Looking Forward

The ability to predict the future can boost nearly every facet of an organization. Whether it’s improving yield, streamlining your supply chain, optimizing your distribution network or better managing regulatory compliance, you can use AI throughout the seed-to-sale pipeline to pull your company’s historical data and enable greater forecasting capabilities.

As the cannabis industry continues to expand, it’s critical to utilize every tool at your disposal to gain a competitive advantage. Implementing AI into your processes could be the leg up you need to successfully grow your business.

Learn more about how your cannabis organization can navigate the future using AI.

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