AI in Talent Management as a Competitive Advantage for Companies

4 min read

CEOs recognize that “talent risk” is the number one threat, according to the KPMG 2020 report.

Losing key employees and attracting specialized talent have a critical impact on future business performance. AI-powered talent management software provides companies with predictive analytics that helps managers identify problems before they impact the business. As a result, without AI, companies will struggle to compete when it comes to retaining talent, but those who adopt AI today will have a significant competitive advantage. To be specific, IBM AI predicts with 95% accuracy which workers are about to quit their jobs, so AI has so far saved IBM nearly $300 million in retention costs, according to IBM CEO Ginni Rometty.

Internal mobility with AI as a business advantage

For many organizations, the second most expensive thing is losing capable people. Studies show that replacing a good employee can cost up to 150% of that person’s annual salary and benefits package, according to Forbes.

Over the last years, famous and profitable companies like Unilever, Hilton, IBM have been working to improve internal talent mobility with the help of Artificial Intelligence. Not only does it save money on recruiting, but it also enables companies to find internal expertise which is often hidden in the organization. High-performing employees strive for trying new things, learning adjacent skills, and getting a chance to work with different leaders.

Today internal mobility is far less about “careers” and much more about “skills”. So companies need systems that can continuously identify and check employees’ skills (skills assessment), arrange these skills so people can find corresponding positions (skills matching), and systems that help individuals develop themselves for the skills of the future (reskilling & upskilling).

Skills Assessment with AI

 96% of employees say that they want to hear feedback regularly, while 72% of respondents believe that their performance would improve with corrective feedback, according to the research

Skills assessment and performance feedback are a regular part of any workplace. However, 69% of companies still rely on annual or bi-annual performance reviews that fail to capture the full picture of an employee’s potential, while 94% of employees would prefer their manager to address mistakes and opportunities to improve in real-time. 

Understanding of competencies and skills is essential for effective management. With AI-powered assessment tools, managers know exactly what skillsets they have in the company, including specific proficiency levels. It also helps managers to give timely feedback and find the best person-job fit.

Imagine you have a talent pool, the next step is to define who has the highest level of the skills required for the position. Such a dashboard could be very helpful, couldn’t it? Thanks to the implementation of AI, a manager will end up with a list of candidates ranked in order of their strength for the skills the company needs. 

Using machine learning algorithms, the software automatically grades and ranks job-ready skills of every applicant, identifying the skill set a person needs to excel in their role. Then connects a learner with corresponding training programs.

Skills Matching with AI

67% of recruiters say they lack skilled and high-quality candidates to meet the needs of their business, according to Jobvite’s Recruiter Nation Survey.

Each job position requires a set of specialized skills. The important thing is that based on the skills assessment, AI technology can predict who has the potential needed. Turnover decreases. Instead of employees leaving for new challenges, they find them internally because their company knows where their potential can be of value. It’s about who can do the job, not just who has done this job previously.

AI-powered skills matching tools allow employees to explore internal career opportunities based on skills matching and helps managers rapidly transition talent through AI-driven skills match identification.

For example, while searching for a Business Systems Analyst, a manager can see how many candidates match the job requirements based on their skills, how strong the skills match is, and what skill gaps an applicant has – all in one interface. 

Employees can also apply for an open position on the condition that their skills match the job requirements. Personal profiles allow employees to match their skills not only to jobs open internally, but also to cross-functional projects and gigs. AI algorithm finds successors for any role. An employee can see the positions for which they’re a strong match, and why they’re a match. This gives them the confidence to apply for the jobs.

As an alternative, thanks to the implementation of AI, candidates can upload a resume and instantly match relevant jobs according to their skills, experience, and interests. And apply with only one click.

Reskilling and Upskilling with AI

9 in 10 executives currently see or expect workforce skill gaps within the next 5 years; under 50% knew how to deal with the problem (McKinsey Global, 2020)

Employees often leave jobs because they don’t see how they can grow within their own organizations and it’s often easier to advance by changing employers. Thanks to AI-powered platforms, employees can upskill and reskill within their company. Now they see which roles they fit in the organization and see a clear pathway to get there. This process contributes to internal mobility as employees can transition career paths, reskill to fill immediate needs within the organization, and gain essential skills needed for future requirements.

A key part of reskilling & upskilling is using artificial intelligence to provide insights to talent executives. The leaders can see how the skills of their workforce stack up to business strategy, and where there are gaps in terms of the capabilities employees need to compete in emerging areas. Companies can then take actions such as adding employees with the right capabilities; helping employees build their skills; and supplementing their workforce with contingent work in growth areas. 

Focused directly on employees’ reskilling and upskilling, software developers use AI algorithms to create personalized training programs that build on workers’ existing skill sets to prepare them for future opportunities.

Employees have profiles that serve as a portal to their career growth. See below the reskilling process in the employee’s profile. Senior Machine Learning Engineer is the target position for an employee who currently is a Senior Data Scientist. The shift requires a set of skills listed in the timeline. After mastering all the skills required for the position, an employee will be suggested as a strong match for a currently open position.

You can add automatic actions for a certain skill level. For example, if a learner achieves more than 85% on a competency the rule unlocks the next training module. If a learner stays between a 30% competency level for more than 7 days, the rule sends an alert to them with recommendations on how to improve in that area.

Summing up, internal career mobility with AI gives leaders a necessary competitive edge over talent in comparison with their peers, who are often relying on outdated L&D methods. It greatly increases the ability to evolve. The company with the best talent is likely to win in its market, and retain the best talent effectively.

What do you think about using AI in corporate learning and development? Share your thoughts with us!

Dmitry Baraishuk I am Chief Technology Officer (CTO) at Belitsoft with over 15 years of EdTech. Passionate about AI and the eLearning industry, author of 50+ articles about eLearning, blogger.

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