Artificial Intelligence (AI) in Recruiting & the Future of Work

People talk about the artificial intelligence (AI) revolution as if it’s something in the future. But the reality is that AI in recruiting is already here, and the possibilities it holds are immense.

But beyond the impact in the process and work of talent acquisition, AI will change something more fundamental: the nature of work itself. This shift will have major implications across industries and disciplines—including IT, engineering, automotive, etc.

Whether or not your particular industry or area of expertise will be enhanced by AI in recruiting, read on to see how you can’t avoid being impacted by the AI revolution.

If you do some Googling on the impact of AI in recruiting, you’ll come up with no shortage of titles like the following: AI is…

     …coming for [X industry]

      …eliminating jobs / putting people out of work

     …going to displace [X number] jobs

     …going to kill [X job]

While good for clickbait, these headlines are wildly misleading as to the actual impact of AI. For starters, AI isn’t something that’s “coming.” It’s already here, as professionals in IT, engineering, automotive, etc. already know:

• 33% of tech, media, and telecom employees use AI as part of their work
• 38% of companies expect more than 20% of their employees will need to be reskilled as a consequence of AI
• On the other hand, a mere 18% of companies anticipate reducing their workforces by 10+% in response to AI displacement

What’s more, according to the same McKinsey report referenced above, 78% of high AI-performing companies expect to reskill 30+% of their workforce over the next three years.

It seems, then, that according to the most recent data—which is always subject to change—the biggest change AI will bring to the industry is that of reskilling, not replacement or displacement. This is a very important reality that employers and job seekers need to keep in mind. The conversation we’re having should be about: how will the nature of work change (or stay the same) as AI becomes more ubiquitous?

Still, people are nervous about this new technology. Decades of cautionary tales from Hollywood and the news media haven’t helped. So let’s break down what AI actually is—especially the difference between predictive AI and generative AI.

Predictive AI, as the name implies, makes predictions or forecasts based on patterns derived from historical data. It involves using machine learning (ML) algorithms, particularly supervised learning and regression techniques, to analyze data and predict future outcomes or classify inputs into specific categories. 

Examples from everyday life include:

• Personalized shopping recommendations
• Virtual assistants
• Spam filters
• Predictive text and autocorrect

Generative AI is concerned with creating new data that resembles the patterns found in training data. One of the most popular methods for generative AI is the use of Generative Adversarial Networks (GANs), where two neural networks, the generator and the discriminator, compete against each other. The generator creates synthetic data, and the discriminator tries to distinguish between real and generated data. 

Through this process, GANs become proficient at generating highly realistic data, such as images, audio, and text, that closely resembles the training data. 

Examples from everyday life include:

• Text generation (like ChatGPT)
• Deepfake videos
• Virtual avatars & characters
• Music generation

Most of the time, when we’re talking about how AI is changing the future of work, we’re looking at the latter category.

With all that in mind, how should you consider the impact of AI on your own career development? Or, if you’re an employer, how should it change your recruiting and staffing strategy? 

One of the ways we like to think of it is to treat AI like a promising new hire. For our purposes, let’s use Sales as an example. No one hires one salesperson at a time—instead, you hire two. The goal is to create an environment where there’s both comradery and competition. When you hire just one rep, you put all your eggs in one basket, which is a risky proposition.

Similarly, one of the risks of AI adoption is transitioning too fast without a clear idea of where it adds value (and, conversely, where it subtracts value). 

And one of the things we’ve noticed is that AI doesn’t have to be revolutionary. In fact, many of the ways that we’ve seen AI positively influence hiring and talent acquisition are quite subtle:

• Automating manual tasks to free up team members for more strategic and creative work
• Speeding up execution and time to market for new products—without sacrificing QA
• Gathering information more efficiently to provide more holistic insights in key areas of inquiry

For talent, it’s also important to think about how AI is going to impact your career. More likely than not, you’re going to need to develop some familiarity with AI-powered tools specific to your field. For example, many systems engineers are using AI-powered modeling and simulation programs to spend less time physically testing new components, speeding up time to market and overall team productivity.

Here’s the bottom line: AI is here to stay. The more familiar you are with AI-powered tools, the better you’ll be positioned to succeed:

• Employers will not only improve their talent acquisition strategies, but also equip their employees to maximize performance by providing access to state-of-the-art tools, platforms, and resources
• Job seekers will position themselves as on the cutting edge of their field by demonstrating competence with innovative technologies that improve their ability to perform

At the end of the day, it’s not AI vs. not AI. It’s good use of AI vs. poor use of AI. The difference, then, is entirely up to you.

If you want support and help in integrating AI into your career growth and development, contact a member of our team today.