| |MARCH 20239Change is the only thing we can be sure of. Strive for innovation and greatness now in order to stay competitivedigital transformation will mean ­ in practical we talk about automating operations, about people, and new business models. It is more important to understanding what digital means to a company ­ whether it is a financial, agricultural, pharmaceutical, or retail institution ­ is essential.What to remember before moving with digital transformation strategy?InnovationChange is the only thing we can be sure of. Strive for innovation and greatness now in order to stay competitive. Digital transformation is often viewed as an implementation of digital technologies into all areas of business in order to build more sustainable solution and better understanding the needs of business.Artificial Intelligence (AI)Everyday everyone talks about AI and ML but before supplement AI and ML with Processes and Technology we should understand Business Requirements first. Last year when I was the part of franchise meet, our Franchise partners were worried about Shrinkage and practically it is happening for all the brands in retail. So we create a Team with operation guys to understand actual scenario. On the basis of understanding we have integrated CCTV Setup and POS Application with AI to identify and count all the Articles on billing counter with date and timestamp. Now we have real-time report to analyse with POS Report and only after 45 days we minimized shrinkage issue by 70 percent. AI is just a concept for Training Computers with human intelligences to enable problem-solving, and decision making functionality.We have seen multiple applications of AI in business in the form of1. Chatbots 2. Predictive analytics3. Voice recognition4. Online chats, email marketing, and social media messaging5. At the time of online shopping everyone can see best use of AI and ML. Machine learning (ML)Machine learning itself is not a part of Data Science or AI. ML is a way of programming to predict or act in a way we want. `Garbage in, garbage out' concept still applies to Machine learning too. Machine Learning will not make Business Analysts redundant, but it will make them different. Currently ML has been used in multiple fields and industries such as: medical diagnosis, image processing, prediction and more.ImplicationsMachine learning is very closely tied with Data Science and AI, which means its implications must be considered too. These implications may be challenging for established business culture when AI and Machine Learning are introduced into business operations1. Machine Learning is not rule-based and therefore traditional business rules will not work in solutions, based on Machine Learning2. Machine Learning is example-driven. In order to `train' an algorithm to behave in a desired way, a business must provide a set of relevant data examples from their real practice3. Most of Machine Learning algorithms lack the transparency of business rules4. Machine Learning will not make Business Analysts redundant, but it will make them different ConclusionAI and ML are critical for Business Analysts because both are based on Learning and data set examples provide by Human.
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