Concerns in regards to the disruptive impact of artificial intelligence on the workplace often dominate discussions about how the brand new technology will impact the job market.
Many comments on the subject range from dire predictions about job destruction and the obsolescence of traditional skills to praise for individuals who can use AI to enhance their performance.
However, for some employers and teachers, AI is already helping to facilitate skill acquisition and improve existing jobs. They say the technology may help firms assess their employees' skills, plan for brand spanking new needs and train their employees – thereby increasing company productivity and employees' profession prospects.
“We found that the most effective ways to find out about AI is to make use of AI,” said Jim Swanson, executive vp and chief information officer at Johnson & Johnson.
The pharmaceutical company uses an AI-driven process called “Skills Inference” to evaluate and plan the whole workforce in a way that might not be possible manually. “It is proving to be a crucial asset in helping us understand and improve the capabilities of our workforce,” says Swanson.
DHL, the international delivery company, uses AI to match worker skills with those needed in open positions. Through the Career Marketplace, employees might be directed to the suitable training to advance their careers more effectively, and managers might be supported in filling vacant positions.
This use of AI promotes internal hiring, which is cheaper and faster than external hiring, explains Ralph Wiechers, executive vp of human resources at DHL. It also signifies that candidates usually tend to be a very good fit for you.
AI offers further uses in quickly identifying and creating training materials for brand spanking new skills – ideal when business needs are rapidly evolving. “For a corporation to be adaptable. . . “In order to amass the suitable skills, it must be automated, unlike previously where you possibly can prescribe a training pattern that remained stable,” says Wiechers.
Many firms that use AI of their human resources management derive skills from data generated across the organization—for instance, existing job titles, staff work, technology activities, and reports from supervisors.
At J&J, a dedicated team developed a company-specific competency taxonomy with 41 “future-ready” competencies, akin to data management or process automation. The AI ​​was then trained to find out where these skills exist within the organization based on employees' previous experiences, roles and current positions. Workforce management systems updated by employers and managers create a knowledge set to coach AI models, evaluate skills, and rate them at a competency level from zero (no skill identified) to 5 (thought leadership).
In addition, the AI ​​also creates tailored learning and development recommendations and suggests users the courses they need to take to advance their careers in the corporate. Mapping the organization's capabilities in this fashion “helps our leaders make informed decisions about hiring, retention and talent movement,” Swanson says.
Other organizations are using AI to enhance training itself – through simulations or by giving more people access to personalized feedback.
At Bank of America, employees can use AI to practice difficult conversations – for instance, discussing sensitive topics with customers. By trying out approaches with a simulation, employees can “practice real-world interactions in a totally protected environment,” says Michael Wynn, senior vp of innovation and learning technology.
“It gives them a likelihood to construct some confidence and test their skills.” . . “This will not be possible with traditional methods,” says Wynn. Managers can see where employees are improving faster by responding to AI feedback, in addition to where employees are struggling – a sign of which areas educators must concentrate on.
“One thing that actually helped us navigate the maze of technology was realizing that our learners don’t wish to learn the identical way,” Wynn adds. “They don’t just wish to read or watch training materials; You wish to be an lively participant.”
Nick van der Meulen, an MIT scientist who focuses on helping organizations undergo technological change, says AI automation allows employers to evaluate more skills, perhaps with greater accuracy than existing approaches.
“They can provide people insight into how their skills are performing. . . You can say that that is the extent you want to reach for a certain role and that is how you possibly can get there,” says van der Meulen. “You can’t try this across 80 skills through lively testing, that might be too expensive.”
Although the technology is “tremendously promising,” van der Meulen can also be aware of its limitations – and the incontrovertible fact that developing the infrastructure requires work.
Similar warnings from other experts underscore the concept that, despite the hype, it should still be difficult to transfer judgments and decisions to artificial intelligence. Competency assessments are only pretty much as good as the information they’re trained on, and human input is critical to the functioning of a system.
“You need a definition (of capabilities) that is straightforward to grasp and useful for an algorithm,” says van der Meulen. He acknowledges that AI is probably not “one hundred pc accurate” and problems can arise if, for instance, employees “don't trouble to make sure that their digital footprint is complete.”
This signifies that typically it’s a rough assessment of skills that employees and managers can correct and complement, fairly than something definitive.
To solve this problem, J&J allows employees to edit their skills history and add information – goals, interests, certifications – that is probably not routinely included in records, ensuring the AI ​​can use as much information as possible.
Because of those limitations, caution still must be exercised when using the technology, says Nimmi Patel, head of skills, talent and variety at Tech UK, the UK trade body. “AI can process large amounts of knowledge in a short time. But algorithmic assessment because it exists today may struggle to grasp the nuances of individual growth and development trajectories.”
She believes that “high-stakes valuation and growth decisions are best suited to stay under human oversight through a hybrid approach.”
At J&J, Swanson emphasizes that AI skills assessment will not be utilized in day-to-day performance management. Participation is optional for each J&J and DHL. However, early numbers show that AI platforms are popular with each organizations. “It's about understanding the large picture of our organization's capabilities and helping people know exactly where they need to focus their learning,” says Swanson.
