AI is the science of making smart machines, particularly intelligent computer programs. Machine Learning is a subset of AI that deals with designing and applying algorithms that are capable of learning things from past cases.

1. Safety & quality:
AI frameworks deliver far more secure and precise production lines resulting in greater speed and consistency than human workers. On the processing floor, AI-based detection can be used to keep workers and equipment safer by recognizing probable dangers.
2.Waste reduction:

Certainly, The beverage industry’s waste perspective is a profoundly discussed element of the business. With AI being utilized to follow each and every step of the manufacturing and supply chain process, there is significant waste reduction.

3. Production optimization:

Application of AI and ML could incorporate quicker production changeovers – reducing the time expected to change starting with one product to the next – and identifying production roadblocks before they become a problem. As of now, an operator is as needed to ‘tune’ the formula but in the future, models will be prepared to adjust production automatically, improving output quality as well as speed.
4. Improving food safety standards:
Every country is consistently looking to enhance its food standards. Fortunately, robots that use AI and machine learning can handle and process food, minimize the chances of contamination as Robots and machinery can’t communicate infections, unlike humans.
5. Packaging
AI-driven robots are proving pivotal in meeting the ever-increasing and pressing demands of customers primarily due to the global growth of e-commerce. The complex nature of the process allows the remarkable opportunity for intelligent automation.
6. Supply chain management
AI is basically programming computers so they can receive information, access it, make a decision as per the evaluation, and then perform any given task based on the decision. This emerging technology enables the beverage industry with Supply Chain Management through logistics, predictive analytics, and transparency.