Abstract
Perfection is an ambitious goal. However, it’s right to say that in-Service Management we aspire to do the best we possibly can. We improve our performance through practice, but for real acceleration, we need to take a fresh approach. “IT is the backbone of the modern enterprise”—if this is the case and we demand a consistently high level of performance from our IT staff now is the time to think about how best to achieve this. With the use of AI powered autonomous micro-learning coupled with machine learning, employees can now be evaluated and coached by providing instance learning and feedback in real time so as to improve process performance.
Highlights
Today’s business leaders are faced with multifaceted issues of managing talents in the organization
The process of managing performance is more complex which has led to organizational managers to seek out a novel and more effective performance in the IT services using machine learning, continuous micro coaching and feedback, and other management techniques (Mike, 2018)
The AI engine could direct the developer in how to build the most efficient and highest-quality application. 1.7 Identify Regression and Poor Practices during Testing Using Machine Learning (ML) In continuous feedback mechanism in the I.T service, machine learning in the future would be applied to other stages of the development of the software life cycle
Summary
Today’s business leaders are faced with multifaceted issues of managing talents in the organization. From declining employee commitment levels (only 33% of U.S employees were retained as of Oct. 2017, according to Gallup) to increase turnover rates, the issues hounding the modern workplace can’t be solved using outdated feedback approaches (Sushman, 2018). Appraisal periods are stressful and high overhead for both the employee and manager. They take a long time to prepare and deliver and often end up as a chore, rather than something to look forward. Even with bi/annual appraisals, we are limiting ourselves to very www.scholink.org/ojs/index.php/rem
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