How artificial intelligence and machine learning help employees improve their skills

Nowadays, technologies are being improved so quickly that companies need to change their approach to learning and development and adhere to a more personalized approach. Artificial intelligence and machine learning can help them with this.

How exactly? Read in this translation.

“If your company does not strive to improve the skills of its employees, staff will not be able to quickly adapt to new tasks and maximize the benefits of modern technology,” said Jim Link, director of personnel at the personnel agency Randstad North America. “And if employees do not develop, then the company is doomed to stagnation.”
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In fact, staff development — that is, training them in additional skills — is becoming an increasingly important condition for success, because companies often lack highly qualified employees who are expensive in the labor market. Employees can be upgraded 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 quickly adapt to constant changes in the workplace and in the world of work.

Trish Uhl, founder of the Learning and Development Agency Owl's Ledge, says that machine learning offers a range of possibilities, including making it easier to create instructions, giving valuable feedback, improving reference systems and personalizing training.

“The advantage of cognitive technologies is that they are able to quickly and accurately process huge amounts of structured and unstructured data in order to select training courses suitable for the experience and skills of [employees],” said James Cook, global staff development partner at IBM. “We believe that this is a great opportunity for human resources departments from different industries to take the path of digital transformation.”

Machine learning has great potential for advanced training, but so far this technology is in its infancy. Now it is necessary to identify useful metrics that will help improve the effectiveness of training. Thanks to third-party tools it will be possible to start experiments earlier. And in the future, machine learning will help employees improve not only technical skills, but also personal qualities.

Staff development with the help of AI: the beginning

Bruce Kronkvist, manager of training and development programs at Dell, said that the use of AI for advanced training is a relatively new practice. More than six months ago, simple analytical tools were used to study and optimize the Dell advanced training program at the company. And recently, the EdCast platform, which with the help of AI offers training strategies for employees, was adopted.

AI and machine learning help the system give additional guidance on what skills the participants and people with similar interests should improve. According to Kronkvist, it is too early to assess the success of the program, but other companies report positive results.

Metrics for successful training

To create a successful training platform, important metrics need to be identified. 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 my own plan, I ask 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 Kronkvist 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? With the help of questions with ready-made answers, he determined what software managers expect from new employees.

This information was not in existing Dell reports, so Kronkvist began to collect metrics from the start of projects to the sending of working code to production applications. The metrics were collected a year before and after experimenting with the advanced training process. Guided by these metrics, Dell managed to reduce the adaptation time of employees from 50 to 8 days, and new employees sent their first code to production within 37 days after they got to work, and not after 100, as before.

Commercial machine learning tools in advanced training experiments

To use AI and machine learning in advanced training, a company can either create its own tool or purchase third-party software. To make experiments faster, Dell decided to contact third-party vendors. For example, Kronkvist and Dell are experimenting with software that, through machine learning, identifies gaps in the competencies of education services employees who want to do more.

Cronquist says: “A major project is being planned - we identify the skills needed for each level in a given position, and then create a kind of assessment system to test these competencies.” Sometimes filling in the gaps is as easy as advising employees to complete the necessary training in a third-party tool on the learning site. But everything is 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 within the entire company.

Companies like IBM are increasingly adapting their commercial AI tools to improve employee skills. For example, the IBM Watson Career Coach solution is designed to help employees grow with cognitive tools. Each Career Coach employee gives advice on which step to take next. Among the recommendations are a number of job options that will suit an 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 current development guidelines. Users can independently adjust their development plans, taking into account how their needs and desires change.

New approaches to improving communication skills

Randstad's Link says: “Although the AI ​​can be of great benefit to a multitude of tasks, it can never learn from human creativity, emotional perception, or complex communication skills.” He believes that when improving staff skills, it is necessary to pay special attention to skills that AI does not possess, including strategic and abstract thinking, leadership, ability to solve problems and communicate. “What is interesting is that these skills are most often honed by younger employees,” says Link.

The AI ​​cannot duplicate these communication skills, but can help improve them.

According to Uhl, AI and machine learning can help HR professionals connect metrics to solve tasks such as combating absenteeism and increasing employee engagement. It is necessary with the help of analytical tools to measure these communication skills, and then, using AI and machine learning, determine which teaching methods will enable people to become better in all their working competencies.

Six machine learning techniques for successful training

According to Uhl, machine learning will change approaches to corporate training, with particular attention to staff development. Machine learning improves employee development in six ways:

• Personalization . Machine learning is designed to find an individual approach to learning and development - not just solving problems, but solving problems of a specific person. Thanks to this, each person will receive the necessary personalized training, chosen taking into account all the features and conditions of work.
• Acceleration . Thanks to machine learning, newcomers will be able to become experts faster - training can be reduced from a few years to a matter of months.
• Optimization . The exchange of views and continuous, automated support at work provide everything needed to develop the necessary skills to the maximum.
• Forecasts and installations . With the help of performance indicators, you can make success even closer - correcting shortcomings in advance, rather than look back and learn from the rules of the past that may not be applicable in the future.
• Efficiency . Machine learning should help in real time to monitor the effectiveness and payback of the program, which will save resources and reduce training costs.
• Results. Improving staff skills through machine learning platforms will help achieve the desired performance results, namely, encourage people to develop and achieve significant results for the company.