"How AI is Transforming Employee Onboarding: Faster and Better!"

Bringing new employees into a company is an important job for leaders in human resources (HR). The way this is done can make a big difference in how new workers feel about belonging to the team.

More and more companies are using artificial intelligence (AI) and other digital tools to make the onboarding process more personal, efficient, and tailored to each new hire. A recent survey found that over two-thirds of companies are already using AI in onboarding, and 87% plan to use it even more in the future.

At the recent CNBC Workforce Executive Council Summit, Taylor Bradley, the Chief Human Resources Officer at Turing, a generative AI company, shared how AI is changing their onboarding process.

Earlier this year, Turing’s CEO, Jonathan Siddharth, called Bradley to say they would be onboarding up to 300 new employees the next week and needed a quick program to introduce them to the company. Bradley humorously noted that Jonathan didn't demand immediate results.

Bradley’s HR team had been working with a large language model named A.L.A.N., which stands for “Always Learning, Always Nimble” and also pays tribute to mathematician Alan Turing. Thanks to AI, Bradley’s team completed the onboarding tasks in under six hours, a process that usually takes two to five weeks without it.

A Quick and Effective Process

To kick off the onboarding, Bradley's team met with engineering leaders to record videos lasting 30 to 60 minutes. These videos explained all the steps a new engineer needed to perform their job well. The AI model then summarized the content and helped create e-learning modules for new software engineers.

Additionally, the team used transcripts from these e-learning modules to create AI-generated voiceovers for training. Bradley noted that the engineering leaders appreciated this change because it freed them from having to teach these modules themselves. Now, the HR team can easily update the content without needing coding skills.

When asked about the accuracy of the AI model, Siddharth emphasized two key points: First, it’s important to always have a human check the results, and second, there should be a good system in place to monitor the AI's outputs. He mentioned that while “hallucinations” (errors made by AI) can't be completely eliminated, they can be reduced. For example, an AI model can be trained to use answers only from the company's HR handbook instead of making its own guesses.

Bradley advised her team to think of AI as a way to enhance their work rather than replace it. “We always need a human to check things,” she said.

Siddharth and Bradley also warned that aiming for perfect AI solutions right away could slow down progress. Instead, they recommend trying different approaches on a small scale first, then expanding what works.

“If you wait three years for results, you might lose the support of your employees,” Bradley cautioned.

Sources: Internet Sources & Twitter X 

Disclaimer: This article is posted after analysing the article which already available to the internet. We just add our view point in addition to the information available in the public sources. We never endorsed or motivate or prove any authenticity of the article from which it originally originated. We just add our flavour to the News already available to the internet or any other public sources. Thank You 😊