How artificial intelligence and machine learning help employees improve their skills

How artificial intelligence and machine learning help employees improve their skills  
Nowadays technologies are being improved so quickly that companies need to change approaches to learning and development and adhere to a more personalized approach. Artificial intelligence and machine learning can help them in this. How exactly, read in this translation.
"If your company does not seek to upgrade the skills of its employees, the staff will not be able to quickly adapt to new tasks and maximize the benefits of modern technology," said Jim Link, HR Director at the recruitment agency Randstad North America. "And if employees do not develop, then the company is doomed to stagnation."
In fact, improving the skills of employees - that is, training their additional skills - is becoming an increasingly important condition for success, because often companies lack the highly skilled employees who are valued highly in the labor market. You can improve the qualification of employees in different ways. From a technological point of view, artificial intelligence and machine learning (type of AI) allow for advanced training programs that help people adapt faster to constant changes in the workplace and in the workplace.
Trish Uhl, founder of the Owl's Ledge training and development agency, says that machine learning offers a number of opportunities, including simplifying the creation of instructions, providing valuable feedback, improving advisory systems and personalizing trainings.
"The advantage of cognitive technologies lies in the fact that they are able to quickly and accurately process huge amounts of structured and unstructured data in order to find training courses suitable for the experience and skills of[сотрудников]"Says James Cook, Global Partner for Personnel Development at IBM. "We believe that this is an excellent opportunity for human resources departments from different industries to embark on the path of digital transformation."
Machine learning has great potential in skills development, but so far this technology is in the making. Now it is necessary to identify useful metrics that will help improve learning efficiency. Thanks to third-party tools it will be possible to start experiments earlier. And in the future, computer training will help employees improve not only technical skills, but also personal qualities.

Staff development with the help of AI: beginning

Bruce Cronquist, program manager for training and development at Dell, says that applying AI for advanced training is a relatively new practice. More than six months ago, simple analytic tools were used to study and optimize the Dell skills development program. And recently we took the EdCast platform, which with the help of AI offers training strategies for employees.
AI and machine learning help the system provide additional guidance on what skills should be improved for participants and people with similar interests. According to Kronquist, it is too early to assess the success of the program, but other companies report positive results.

Metrics for successful professional development

To create a successful platform for professional development, you need to identify important metrics. Despite the fact that HR specialists can first offer their own ideas, it is equally important to ask the opinion of other participants. "After I make up my own plan, I ask the students what is important for them, to show them how successful the training has been," says Cronquist.
If these metrics are not yet available, then you need to find a way to quickly assemble them. For example, when Kronquist was instructed to improve the adaptation of new employees, he needed to find out what the tasks of the technical manager were. Provide satisfaction? Or speed up the execution of processes? Using questions with ready answers, he determined what software development managers are waiting for from new employees.
This information was not available in existing Dell reports, so Cronquist started collecting metrics - from the beginning of the projects to sending the working code to the production applications. Metrics were collected the year before and after the experiments with the process of professional development. Guided by these metrics, Dell managed to reduce the time of adaptation of employees from 50 to 8 days, and new employees sent their first code to production already 37 days after entering the job, and not through 10? as before.

Commercial tools for machine learning in experiments to improve skills

To apply AI and machine training in advanced training, a company can either create its own tool or purchase third-party software. To make experiments faster, Dell decided to turn to third-party vendors. For example, Cronquist and Dell are experimenting with software that uses machine learning to identify gaps in the competencies of training services staff who want to achieve more.
Kronqvist says: "A major project is being planned - we identify the skills required for each grade in a particular position, and then create a kind of evaluation system to test these competencies." Sometimes filling in the gaps is as easy as recommending employees to go through the necessary training in a third-party tool on the training site. But it's not so simple. To begin with, Dell launched this project for the training services team, and when all the shortcomings are polished, Cronquist plans to deploy it throughout the company.
Companies such as IBM are increasingly adapting their AI commercial tools for staff development. For example, the IBM Watson Career Coach solution is designed to help employees develop with the help of cognitive tools. Each employee Career Coach gives advice on what step should be taken in a career further. Among the recommendations are a number of options for positions that fit the employee. These options are accompanied by an assessment based on the needs of the organization and a list of suitable skills. Career Coach prepares employees for their individual career path and offers topical development advice. Users can independently adjust their development plans, taking into account how their needs and desires change.

New approaches to improving communication skills

The link from Randstad says: "Although AI can do a great job for many tasks, it can never adopt human creativity, emotional perception, or complex communication skills." He believes that when improving the skills of staff, special attention should be paid to skills that AI does not possess, including strategic and abstract thinking, leadership, ability to solve problems and communicate. "Interestingly, these skills are most often honed by younger employees," says Link.
AI can not duplicate these communication skills, but can help improve them.
According to Uhl, AI and machine training can help HR professionals link metrics to solve tasks such as fighting absenteeism and increasing employee engagement. We need to use analytical tools to measure these communication skills, and then, through AI and machine learning, determine which teaching methods will allow people to become better in all their working competencies

Six methods of machine learning for successful professional development

According to Uhl, machine learning will change approaches to corporate training with special attention to staff development. Machine learning improves the development of employees in six ways:
Personalization . Machine learning is designed to find an individual approach to learning and development - not just solve problems, but solve the problems of a particular person. Thanks to this, each person will receive the necessary personal training, tailored to suit all the features and conditions of work.
Acceleration . Thanks to machine learning, beginners can quickly become experts - the training period can be reduced from a few years to a few months.
Optimization of . Exchange of opinions and continuous, automated support at work give everything necessary to maximize the development of necessary skills.
Forecasts and installations . Using performance indicators, you can make success even closer - correcting shortcomings in advance, rather than looking back and learning from the rules of the past that may not be applicable in the future.
Efficiency of . Machine learning should help in real time to track the effectiveness and payback of the program, which will save resources and reduce training costs.
Results. Increasing the skills of employees using machine learning platforms will help achieve the desired performance results, namely, to encourage people to develop and achieve notable results for
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