AI has the wide applicability potential. However, the current AI can add value to many business processes. We are in the early stage of adopting these technologies such as Artificial Intelligence, Machine language, Deep Learning and there are many developments to be happen.
Everyone knows about AI but all are still not familiar with what actually AI can do for the betterment and what are the potential harm through it.
So, let see where AI can add more value. As per Michael Chui, AI can create more value to the company who indulge in creating value through Marketing and sales. The organization where operational excellence matters, AI can provide assistance in improving the efficiency.AI can enhance the processing in banking, health, Insurance Industry.
Ai enabled Robots can provide assistance in warehouse operations. Many retailers use automated replenishment system (ARS) integrated with vendors to manage inventory. ARS is a system that automatically orders inventory when it reaches below the minimum level.
AI can provide assistance in almost every field such as automating the business processes, improve customer support and service, faster means of communication, evaluating employees' performance and managing human resource in a strategic way. It means the impact of AI enabled technology is rising on workplace, lifestyle, individual, society and most importantly on employment.
The developments in AI are providing more accuracy in predictions and estimation which is based in data available.AI can result into revenue growth, provide opportunity for innovation and helps in informed decision making. The biggest challenge with AI is that it requires large amount of labelled data to complete the complex tasks.
David Schwartz believes that there are still many field to be discovered to gain positive impact of AI. Along with advancement in AI technology people's concerns are growing about its potential drawback.
Michael Chui also gives an idea about what potential harm AI can do. He said that it is difficult to understand what algorithm is actually doing, why it is making choices and what forecasting it is doing, are the algorithm are transparent.
It shows are programmer are programming computers to perform a specific task. In doing so they are teaching and training the computers but what about the fact that computers are self-learning while processing its functions. AI while facilitating self-driving car collects huge data and works on it to learn more.
With AI, data labeling also comes into question. As data collection is essential but data labeling is significantly important. For this, programmers are using Reinforcement theory to collect labeled data from the actions and behavior of Robots. This may disappoint researcher to invest further investment and they sometime opt for wait and see attitude.
Thus, Artificial intelligence along with its sub set such as machine language and deep learning requires Reinforcement learning which is basically a carrot and stick approach which helps a robot to learn a specific behavior and improve its performance. Deep learning requires huge data in records to improve the efficiency of data model and facilitate better classification of data.