AI Applications and Implications for HR and L&D

by Mark Marone  |  February 20, 2021

• Human Resources and Learning & Development functions are increasingly
  adopting AI and automation to improve and personalize service delivery while reducing time-consuming, routine administrative work.
• Because these areas focus on “people” issues, there can be profound consequences on corporate culture and employee engagement if an organization fails to adequately prepare its workforce for AI.

Artificial Intelligence (AI) is increasingly becoming part of everyday business. Ironically, the areas that have been fairly quick to adopt a variety of automation and AI applications are the two core “people” functions of an organization: Human Resources and Learning & Development. In HR and L&D, AI has the potential to improve people’s work experience, job satisfaction and ability to grow in their careers.

That said, the introduction of AI isn’t without consequences. Companies that have been successful in adopting AI in various areas of their organizations recognize that they have to prepare their people for it. Otherwise, the impact on corporate culture and employee engagement could counteract all the benefits AI promises to deliver.

Let’s take a closer look at how HR and L&D are using AI, and what that means for your workforce.

Common Applications of AI in Human Resources

Research has shown that, traditionally, up to half of HR’s time is spent on record-keeping, auditing and service provision. However, chatbots and other elements of conversational interface are now automating many of those HR functions. Additionally, many companies are promoting ways to personalize the benefits of using AI to make them more valuable to employees.

Some of the common applications of AI in HR today include:

• Candidate Sourcing: Virtual assistants use proprietary AI algorithms to identify and screen candidates.
• Video Interviews: Companies offering recruiting software and intelligence platforms help organizations evaluate candidates via video interviews or chatbot conversations, and then analyze and score applicants using AI based on the information extracted.
• Sentiment Analysis: Organizations are getting deeper insights into employee sentiment using AI’s natural language processing and text analysis of emails and social media posts to gauge the tone of employee conversations and predict engagement and turnover. IBM says that its AI can now predict with 95% accuracy which workers are about to quit their jobs. The company is using this “predictive attrition program” to help improve retention.
• Predictive Modeling: By looking at data patterns and adjacent skills, IBM’s AI can zero in on a person’s strengths and uncover career paths that may not have been evident using traditional methods. Other companies offer predictive algorithms that use data on the career progressions of previous employees to make recommendations on potential career paths for others.
• Service Provision: Software is now available that helps employees with such services as identifying relevant benefits they might be overlooking or answering questions and onboarding new hires.

Common Applications of AI in Learning & Development

As for AI’s role in learning and development, a constant stream of new applications and platforms are being introduced, many inspired by innovations in K-12 and higher education. In addition, personalized AI-powered learning platforms offer training recommendations at relevant points in the learner’s journey tailored to an employee’s position, experience and the task at hand. Here’s just a sampling of what AI is bringing to L&D:

• Self-Service Onboarding: Onboarding is being put into the hands of new hires with AI-powered processes that enable self-service via a digital assistant.
• Content Management: Providers are building AI systems that can read text documents and discern concepts, and can create learning paths and appropriate assessments.
• Personalized Learning: There are numerous platforms for curating content, delivering personalized recommendations at relevant points in the learner’s journey using AI. Corporate learning is now taking a page from consumer platforms like Netflix and Spotify to provide the individualized experience that new generations of learners expect.

Preparing Your Employees When AI Gets Personal

While these are just a few of the ways HR and L&D are being transformed by AI for the better, there are also some potential downsides. When we surveyed more than 3,500 employees around the world — from CEOs to individual contributors — about their attitudes and expectations related to AI in the workplace, seven in ten told us they were positive about the potential for AI to handle routine administrative tasks so they could focus on more meaningful work. For example, these kinds of tools help take the burden off the more mundane or time-consuming administrative work that’s traditionally been part of HR.

But when it comes to the workforce, these functions are highly personal. As AI continues to spread throughout the HR and L&D worlds, keep in mind that “people decisions” like hiring, firing and career development have profound consequences. Don’t overlook the potential concerns about fairness and the resulting impact on engagement and a company’s culture.

There’s also a tension between “predictive power” and “appropriateness.” What AI delivers as a solution can sometimes conflict with what people think is fair and appropriate. And the more complex algorithms are, the harder they are to explain to people — which can also affect how much people trust their results.

What can you do to prepare your people so that you — and they — can get the benefits of AI? Our survey identified three factors that will make your people feel more positive about AI: transparency in the way AI works, trust in their leaders, and confidence that they can transition (and have the skills to adapt).

The vast majority (84%) of respondents in our survey expect the changes AI brings to be positive, but the continuing role of human leaders in AI oversight is critical. To find out more about the steps your organization needs to take to capitalize on AI applications in your “people” functions, download the full report here.

Written By

Mark Marone, PhD. is the director of research and thought leadership for Dale Carnegie and Associates where he is responsible for ongoing research into current issues facing leaders, employees and organizations world-wide. He publishes frequently on various topics including leadership, the employee/customer experience and sales. Mark can be reached at mark.marone@dalecarnegie.com.