In times past, cannabis legalization has faced significant setbacks from various political divides and the society at large due to its adverse effect stemming from its uncontrolled use. As more knowledge on its vast array of potentials in the medical world becomes available to the general public, challenges facing the cannabis industry are gradually easing up for disruptive innovations. Valued at $73.6 billion by 2027 with an ever-growing stock market, the legal cannabis industry is expected to create more money-spinning opportunities for market stakeholders. As major innovators in the biotech, pharmaceutical, and clinical sectors are looking for ways to utilize its vast advantages, the area of cannabis research is enjoying rapid growth. With growth comes an increasing demand for more cannabis products.
Where Does AI Come in?
Artificial intelligence simulates human intelligence in machines. Therefore, major processes like planting and harvesting the cannabis plant, discovering suitable strains, online marketing, supply chain monitoring, and analyzing the vast repertoire of data generated in every stage of the from-the-farm-to-the-table can be taken care of by artificial intelligence and robotics.
AI-Driven Cannabis Farming
Farmers in the cannabis sector face several challenges that are unique to hemp. Getting good quality seed with high germinating potentials is one issue. Another issue is that farmers end up getting either low-quality seeds that are different from what’s on the labels whereas, seeds and clones are expected to match. Other Cannabis farmers also complain of pest infestation and inferior root growth.
Whether you are starting cannabis farming on a small-scale or growing it on a large scale, you can now use AI-driven farm robots to plant, monitor growth, and harvest cannabis. In the planting phase, these robots can map out optimal plant spacing, weed out low quality seeds, and measure environmental inputs such as water, temperature, PH levels, sunlight, and CO2 levels for maximum yield.
At the growth phase, AI-enabled cameras can capture and analyze real-time images taken by drones to monitor plant growth rate. Besides, AI-sensors with top-grade precisions can detect sick cannabis plants and chose the best pesticides to apply. At harvest, AI-powered chatbots can work round the clock to harvest cannabis in large quantities and in good time. An example of such technology is the Bloom’s Cannabis robot which combines human precision and machine efficiency to cultivate cannabis. It is evident that various AI-driven technologies for cannabis farming are faster, more efficient, and have better accuracy than human labor.
AI-Packaging and Labelling for Cannabis Products
Using AI to label cannabis products prevents the problem of seed mismatch – a situation where the seeds in a package are different from what is on the label. Other issues in CBD product labeling are THC amounts and inaccurate claims about product marketing. During Cannabis packaging, the labeling must be accurate. The United States’ regulatory rules guiding CBD products states that “Hemp products must not contain more than 0.3 percent THC to avoid facing lawsuits for containing marijuana,” which, according to federal laws, is an illegal substance. CBD companies must comply with these guidelines.
AI algorithms and robotics take care of every stage of the CBD labeling and packaging to prevent compliance errors. They achieve this by giving precise recommendations – scanning and listing the various components, respective percentages, and side effects so that consumers are well informed. To sum it up, the presence of AI and robotic technology gives consumers realistic expectations about a CBD product. An example of such an AI tool for Cannabis labeling is Strain Brain which can label up to over 100 different strains of cannabis.
AI-themed Consumer Experience
The Cannabis distribution channel is not complete without a good consumer experience. In terms of Cannabis consumption, consumer experience varies from person to person. This variation is because of two main factors. First, consumers have different biochemical make-ups. Second, there are different strains of cannabis, each with its unique compositions. Other secondary factors like tolerance level, environment, and foods consumed can also affect the effect of cannabis on the body.
Using machine learning methods to analyze the vast gamut of consumer data helps CBD companies know what their consumers want, what components to include, improve, or remove, as well as the most sought-after cannabis product. AI can also predict and forecast changing trends. In so doing, CBD companies are well equipped to develop strategies to give their consumers the best experiences at every stage of the brand interaction. If cannabis brands are keen on standing out among other key players, they must leverage consumer experience.
AI Value-Added Supply Chain
The CBD production process isn’t complete without an efficient system to distribute specific CBD products to their final buyers. An optimized supply chain increases the production cycle while reducing the cost, but when AI powers this process, it results in a more efficient supply chain management. CBD companies in tune with AI trends drive their supply chain using AI.
They achieve this by collecting and analyzing real-time data at every stage of the supply chain network from start to finish. This includes the producers, vendors, storage sites, transport channels, distribution centers, and retailers. CBD companies now have great insights into flaw areas and what can be done to remove them. Because of AI, we have cannabis apps that provide an all-round guide on everything cannabis. With AI in the Cannabis supply chain network, Cannabis companies get more value in capacity planning, quality of produce, production, output, and cost. AI achieves this while advancing safe working conditions.
As nations across the world continue to legalize the use and production of cannabis, increasing demand and an ever-ready market will give way for the explosion of artificial intelligence and robotics to boost the various stages of CBD production.
