• Automation of basic administrative activities. A lot of time is spent by teachers in administrative activities like grading and assessment of worksheets. The use of AI in education can help automate the grading and assessment of activities like multiple choice questions, fill in the blanks, etc. Another tedious and cumbersome activity for teachers is preparing the report cards of students. The use of artificial intelligence in education can help automate this as well. Automation of administrative activities means teachers can spend more time with the students, thus making the learning process more efficient.
  
  
• Personalized learning. The purpose behind application of AI in education is not to replace teachers but give them a helping hand in understanding the potential and limitations of each student. The use of AI in schools makes things easy and convenient for the teachers and students as well. By understanding the needs of every student, teachers can come up with a tailor-made study plan for every student.
  
  
• Constructive feedback. Programs powered by artificial intelligence can provide valuable feedback, both to the students as well as teachers. Use of AI in classrooms can point out to teachers how to improve the instructions provided to the learners, and also how to make learning more fun and interesting. Instant feedback to students helps them understand where they are going wrong and how they can do it better. 
  
  
• Accessible by all students. The use of AI in classrooms makes learning universally accessible for all students. Whether a student is slow learning or unable to attend school due to an illness or injury, and even students located in remote areas, AI in education is a blessing for them. The use of artificial intelligence in education helps to overcome the geographical barriers in learning. Students located anywhere around the world can learn from the best teachers through the use of AI in education.
  
  
• Smart content. When we refer to smart content we actually imply varying types of virtual content that includes digitized guides of textbooks, video conferencing as well as video lectures. The learning experience can now be enhanced by robots by developing customizable learning interfaces and digital content that is applicable to students of different grades, for elementary and post-secondary schools. The content becomes easy to grasp by separating it into coherent chunks, shedding light on integral lesson stuff, and summarizing the main points. Audio and video content can also be created. Through this, students can easily gain access to all important materials, grasp in a swifter manner, and achieve their academic targets.

• Cashier Free Stores. By cutting down employee compensation and increasing efficiency and reducing wait time robotization of stores had significant savings on operational expenses.
• Chatbot Based Solutions . With the introduction of AI chatbots, it's much more convenient for businesses to target customer needs and solve their problems in an efficient and transparent manner. AI chatbots provide a higher level of customer service, send notifications about new collections, and suggest similar products.
• Price Regulation Strategies. AI technology for retail stores has helped businesses set prices for their products more competitively to thrive in the market. It visualizes the likely outcomes of multiple pricing strategies. It reads data within seconds from the business’s earlier transactions and from the market for the product’s actual cost, promotional activities, and sales figures in the market and keeps its par for generating profits within the same threshold with higher efficiency.
• Virtual Trial Rooms. A new trend and a new way of shopping especially at a time of covid which gave this technology a big boost. These virtual trial rooms help customers save time, save money from travel expenses, and from the convenience of your home, the customer finds the perfect outfits with all elements perfectly matched in just minutes.
• Product Categorization and Inventory Management. AI-based technology combined with other algorithms of machine learning can help the stores regulate and keep a check on product categorization so as to be able to guide the people looking for a specific kind of product head to the right space of the store instead of rummaging through a lot of unwanted products. This can also work with regard to having an image of the product in-store to be able to get the idea and the location of the same product with its details, price and even size availability this would not just help in saving time but it also would help in getting the real-time inventory to the store to bring in the required stocks each day to not miss out a customer. This can help in the retail stores so as to be able to get all the products piled up ready for sale in their inventory timely, this must not be avoided. keeping the stocks in a retail store becomes important as this specifically needs time investment from the customer to be able to go and shop.
• Feedbacks and Prediction. The electronic devices which have been installed are likely to ask about the customer experience after they are done with the sales and payments. As nowadays all the customer details are noted to update them about upcoming offers and sales it gets easier for the stores to ask for feedback and calculate their customer satisfaction using Artificial Intelligence techniques and have ample room for improvement in time. This also helps in understanding the prediction of the customer based on their past purchases,  preferences, and sizes and makes them have updates on the recent products offered on the specific products only that too store wise and location wise. This will not just cause them to have a personalized experience but also makes the entire user experience be automated and efficient.

LOGISTICS

In logistics, it is essential to optimise goods' numerous movements and avoid costly errors. The volume of logistics operations implies the need to predict future demand to plan the resources that can adequately meet it.

Below you will find and infographic from Indatalabs (www.indatalbs.com) showing the application fields of AI in Logistics.

Source: www.Indatalabs.com

TRANSPORTATION

Large-scale supply chains must manage numerous vehicle assets and premises worldwide. AI in supply chain and logistics makes it easy to tackle these challenges. It helps process and classify related contracts, review long legal documents, keep customer information up to date, verify delivery data, eliminate duplicate information, and on and on.

Another example is the AI breakthrough in rail transportation. AI technologies can be used to build fully autonomous rail systems with smart infrastructure and self-driving trains for carrying cargo and people. The trains will also interconnect with other trains, exchange data, receive notifications from human managers and take notification-based actions.

There is one main methodology applied to two different goals:

• Predictive Logistic Intelligence. Developing AI for better logistics, suppliers mitigate risks and generate predictions to prevent possible breakdowns. ML-solutions combined with NLP can be used to gather meaningful data from multiple social media sources, process unstructured text, conduct sentiment analysis, and indicate possible risks. Likewise, AI-based systems can use digital and satellite maps and information about traffic to help optimize routes. The system can consider and process in the real-time mode time, place, traffic state, changing customer demands.
• Predictive Maintenance. AI-driven systems automatically gather and analyze data about assets and warn about possible breakdowns. Such systems can accumulate information about failures, draw up statistics and, based on this statistical data, schedule repairs. If a provider can guarantee the employment of available and reliable assets, it will help gain a competitive edge and trust of services consumer.

• Agricultural Robots – Companies are developing and programming autonomous robots to handle essential agricultural tasks such as harvesting crops at a higher volume and faster pace than human laborers. 
• Crop and Soil Monitoring – Companies are leveraging computer vision and deep-learning algorithms to process data captured by drones and/or software-based technology to monitor crop and soil health.
• Predictive Analytics – Machine learning models are being developed to track and predict various environmental impacts on crop yield such as weather changes.

• AI for Health Monitoring
• AI for Detection of Estrus
• Robotic System to Deliver Vaccines
• Drones & Facial Recognition for Herd Management
• Automated milking
• Training Models to detect diseases, nutritional deficiencies, etc.

A joint study conducted by BCG and Google found that by using AI and advanced analytics at scale, CPG companies can generate more than 10% revenue growth through more predictive demand forecasting, more relevant local assortments, personalized consumer services and experiences, optimized marketing and promotion ROI, and faster innovation cycles. 

The main domains of application of AI in CPG are:

• Marketing use cases: From assessing the value of in-store promotions to marketing spend optimization, AI has the opportunity to bring a data- driven approach for marketers in the CPG industry. 
• Planning and forecasting: In the age of AI and algorithms, older modeling techniques fail to incorporate the wide variety of data sources needed to produce results precise enough for the modern enterprise. AI-based systems can more precisely predict the quantity of product necessary and the delay in which they will need to be restocked. 
• AI-based supply chain optimization: In order to predict shortages in stock and arrange new shipments, CPG businesses can monitor product location and inventory using both IoT devices as well as other sources like transaction data and even third- part sources, such as the weather. AI tools can eliminate manual effort and increase efficiency in logistics.

PERFORM AI Movies:

PERFORM AI Animations:

• AI Business Process Applications. In Depth Guide to the Top 100+ AI Use Cases & Applications. https://research.aimultiple.com/ai-usecases/
  
  
• AI in Consumer Packaged Goods (CPG).
  https://www.dataiku.com/stories/reshaping-cpg-industry-with-ai/
  
  
• AI in Services. Springer Nature Switzerland AG 2019 77 P. P. Maglio et al. (eds.), Handbook of Service Science, Volume II, Service Science: Research and Innovations in the Service Economy, https://doi.org/10.1007/978-3-319-98512-1_5
  
  
• AI in Livestock Production.
  https://www.pashudhanpraharee.com/application-of-artificial-intelligence-ai-for-livestock-poultry-farm-monitoring/
  
  
• AI in Agriculture – Present Applications and Impact _ Emerj.
  https://emerj.com/ai-sector-overviews/ai-agriculture-present-applications-impact/
  
  
• AI in Logistic and Transportation.
  https://indatalabs.com/blog/ai-in-logistics-and-transportation
  
  
• How AI Is Transforming The Education Industry.
  https://www.dqindia.com/ai-transforming-education-industry/
  
  
• How AI Is Used In Education.
  https://bernardmarr.com/how-is-ai-used-in-education-real-world-examples-of-today-and-a-peek-into-the-future/
  
  
• 6 Applications of AI in Education Sector _ Analytics Steps.
  https://www.analyticssteps.com/blogs/4-major-applications-artificial-intelligence-education-sector
  
  
• How Is AI Used in Education?_mDevelopers.