How does Artificial Intelligence Help To Transform Employee Productivity?
Every company moves towards becoming a tech company, and AI-enabled computers and bots will enter the field of how recruitment, on-boarding, training, and working happens at our workplaces. Here are just some of the areas where successful artificial intelligence courses used by tech companies to train smart machines could be used in the foreseeable future.
Onboarding and recruitments:
Did you know that many companies use AI-enabled systems to scan and identify the right person for the job in most smart tech companies? They can effectively and accurately wade through millions of applications and gain foresight from their profile sampling techniques to invite the deserving candidate.
Pymetrics uses neuroscience-inspired "games" to assess Artificial Intelligence Courses with emotional and cognitive features of the profile avoiding any human bias on gender, status, race or socioeconomic factors. They compare the new profiles to their inhouse data of profiles of persons who were successful at the job being recruited for. It can also make lateral options a choice for candidates who are not just right for the particular job but fit other open vacancies.
Similarly, Montage, with the top 100 amid Fortune 500 companies as clients use an AI-driven interviewing tool which can undertake automated scheduling, on-demand text interviewing and such to reduce unconscious biasing in recruitments.
Chatbots are not just for customer service and help the new recruits settle in better. Unabot, used by Unilever is a good example of using NLP (natural language processing) to answer queries on payroll and HR with advice to employees in plain and simple human language.
On-the-job training:
The entire learning process and training is full of examples of AI-interventions. They help garner from older experiences and transfer to new recruits the wealth of information required for being successful on the job. Honeywell uses AR/VR to capture the work experience and learn “lessons” from it to be passed on to new hires. Such tools keep records, use image recognition technology, play these back, provide real-time feedback, issue reminders, and help in a VR experience of the role.
Augmented workforce
Fears that AI will replace workers and take over their jobs, is baseless. The very aim of AI is to aid the workers and one should exploit the help in increasing productivity, efficiency and augmentation of the workforce since AI brings many benefits to its applications. Humans can better use their faculties for creative and human-interaction based areas of work in artificial intelligence courses since machines do need human interaction and maintenance too.
Machines have proven skills in repetitive tasks, providing insights into large volumes of data and the potential for predictive trend analysis. PeopleDoc, Betterworks and such can go a long way in bettering the day-to-day workplace experience with monitored processes and workflows and processes and RPA-robotic process automation.
Surveillance in the workplace
Are you aware that according to a Gartner survey, half the companies with 750million USD make gainful use digital data-gathering tools to monitor employee performance and activities? This includes employee engagement and satisfaction levels. Some companies use tracking devices to monitor bathroom breaks and audio analytics to determine voice stress levels. Others use the carrot of fitness and exercise programs through traceable Fitbits. Workplace Analytics is used by Humanyze on staff email and IM data, and microphone-equipped name badges. Not all AI is bad as bullying, stalking and security are good goals. Right?
Workplace Robots
Physical autonomous movement robots are fast becoming the means of access for warehousing and manufacturing installations. Robots like Segway have a delivery robot while, security robots like Gamma 2 keep the trespassers away, and ParkPlus helps you find parking slots. Include the automatic shuttles and driverless cars at workplaces and wonder why we humans are still complaining.
Conclusion:
Though the concepts have been around for ages the past two decades have seen a phenomenal and sustained increase in ML/AI applications. Artificial intelligence is the ability of machines to simulate neural networks and human intelligence without the use of any human intervention or explicit programming. Machine learning is a subset of AI technology that develops complex algorithms based on mathematical models and data training to make predictions whenever new data is supplied to it for comparison.
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