Impact of Artificial Intelligence on Organizational Transformation - Группа авторов

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their company within 5 years. The research found that 77% believe that AI would result in better job, while 33% expect that AI would do more human task. In addition, 50% thought that they would need to retrain the worker to make them able to work side by side along with the machines. Only 20% of the respondents took it as a threat on their job.

      Survey by the Gallup found that 31% of the employees are working remotely without office and helping them with tools of team management, live chat through video conferencing, and other ways to coach and engage the people.

      As per the survey done in 2018 by McKinsey on AI, the report showed that 47% of the business has added at least one AI capability in the process of the business in contrast to only 2% in 2017. The growth of more than the double shows the increasing popularity and use of AI in business.

      Investment in AI is growing at very high rate and it is predicated that percentage of AI would rise from 12.5$ billion in 2017 to 46%$ billion by 2020. It will have a great effect on across the world.

      The AI plays a very crucial HR by transforming the way it used to work earlier. Using various algorithms, based on the machine learning and NLP and the chatbots, the AI in HR is creeping slowly to strengthen its roots. The various branches in HR are discussed below which helps the HR persons in performing the task differently.

      3.5.1 Machine Learning

      It is the branch of AI that helps or makes the machines able to study the data and makes future forecast based on the collected data. The source of machine learning lies in the pattern and appraising the data based on the algorithm. According to Davenport and Ravenki [5], machine learning possesses the ability of identifying probable matches based on the most similar data and can also be associated with the same person and the beauty lies in the fact that the data may appear in slightly different formats across databases. Machine learning helps in following areas in HR context.

       3.5.1.1 Variance Detection

      Variance detection identifies the items, events, or observation which shows some deviation from the expected pattern or the routine task in the database. The said algorithm can be used tom study the constant behavior of the employee behavior and the deviation from the same can be used to study the reason behind so.

       3.5.1.2 Background Verification

      Models based on the machine learning can get the meaning and blow the warning signals for the structured and unstructured data from the resume of the applicant.

       3.5.1.3 Employees Abrasion/Attrition

      It helps the employer to recognize the employee who is at the border of abrasion and makes the HR manager to involve actively with this employee and try all the remedies to hold them.

       3.5.1.4 Personalized Content

      It provides a more tailored made employee engagement by using the predictive analytics to endorse career goals based on professional growth programs or to enhance the career based on data of the prior action of the applicants collected from different sites.

      3.5.2 Deep Learning

      Deep learning is a division or branch of machine learning that prepares a technical device like computer or laptop to learn and comprehended from great amounts of data through neural network construction. As it is the more developed stream of the machine learning, it divides the data into layers of impression. Deep learning makes the computers able to set up primary basics about the data and trains them to learn and execute by its own by recognizing the patterns using multiple neural network layers for working.

      Deep learning algorithms can start working after sufficient training; Deep learning can instigate to make forecasts or elucidations of very complex data.

       3.5.2.1 Important Use of Deep Learning in HR Context

      3.5.2.1.1 Recognition of Video and Image

      3.5.2.1.2 Speech Recognition

      By understanding the human voice, pitch, accent, and voice input, the machine can respond accordingly and select the candidates as per the requirement.

      3.5.3 Natural Language Processing

      The work of understanding human nature, language, tone, and context is done with the help of natural language processing (NLP) trains chatbots. NLP enables the AI system as the capable capacity builder for the organizations to continue to automate HR service delivery with chatbots.

      3.5.4 Recommendation Engines

      Digital learning capabilities mostly encompass tailored learning recommendations correlated to level of skills and the professional interests. By the use of Big Data and the Deep learning, learning experience stages can recognize learning pathways that might interest individual employees.

      In the consumer survey done by PWC of its consumer Intelligence series, they propose the following

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