6 Do’s and Don’ts for Using AI to Humanize Hiring

In these early days of the AI boom, it can be easy to spot AI-generated content when looking at semi-realistic images or listening to robotic voices. In hiring, it can be harder to discern among tools based on AI versus automation, and where to apply these technologies to hire the humans who carry out the day-to-day tasks of your business. SmartRecruiters’ mission brings clarity to these times; our updated mission in 2024 is to humanize hiring in an age of automation.

Rebecca Carr , Chief Product Officer and Acting CEO at SmartRecruiters, recently shared her perspective on the best applications for AI in the webinar Future-Proofing Talent Acquisition for 2024: Leveraging AI Effectively with Andrea Kirby at Talent Table .

Differentiating AI from automation

To begin the conversation, Rebecca addressed the common misperception that AI in recruitment is the same as automation. “Automation is a set of rules that perform the same task over and over,” she said. “AI unlocks the ability for that task to respond dynamically based on how people behave. It adapts to the information it collects.”

In speaking about SmartRecruiters' new mission, she said, “Automated and AI-driven hiring processes can feel cold. We want to take all the great things about recruiting software and add innovations that solve key problems that hiring teams face every day.”

As a product leader, Rebecca considers the application of technology in terms of customer outcomes. In this post, we’ll discuss the three positive outcomes of AI and machine learning—the Do’s, and three areas that Rebecca cautioned us about—the Don’ts. Let's dive in.

Do’s for embracing AI in hiring

1. Empower candidate discovery

The need to identify top internal and external talent never goes away, but that could get harder if recruiters get swamped with resumes due to candidates’ use of AI. A Canva survey found that 45% of candidates report using generative AI to build or update their resumes, and some candidates use AI-powered systems that enable them to apply to hundreds of jobs at once.

Recruiters and hiring managers need a quick way to surface best-fit candidates, and the AI-powered SmartAssistant fulfills that role. Other applications for candidate discovery include conversational AI and chatbots like SmartPal, as well as external sourcing tools such as those listed in the SmartRecruiters Marketplace.

2. Look for ways to unlock efficiency

“In the current economic climate, some recruiting organizations have decreased in size and are expected to do more with less,” Rebecca said. “There’s a need to automate more manual tasks and administrative work.”?

With AI-powered automation like SmartWorkflows, teams can configure automated processes more quickly and eliminate manual data entry. In addition, generative AI co-pilots like those in the latest SmartRecruiters product release can draft email copy and help develop recruitment marketing campaigns. Generative AI can also assist with building scorecards and summarizing video interview content.

3. Leverage proactive insights

Asking questions of data is the best way to find out what needs improving, but you may not always know the right questions to ask. “AI-driven insight can surface the data that shows what you can be doing better, or what you might be doing wrong,” Rebecca said. “Then you can adapt your workflows to hire faster, hire more efficiently, and save money.”

As a leader who’s seen many ideas through to product delivery, Rebecca is very clear that AI is in its first phase of widespread usage. “There will be many more phases of adaptation,” she said. “By focusing on these three outcomes, teams will be better positioned to experiment in ways that deliver results.”

Don’ts for AI in Hiring

4. Don’t focus on everything at once

Deciding where to apply AI in your recruiting process can be daunting—but you don’t have to do it all at once. “Focused use cases get faster results,” Rebecca said. “Narrow AI applications will deliver better experiences and drive measurable improvements in efficiency.”?

SmartRecruiters' new AI co-pilots generate interview questions and email content for candidate communications and recruitment marketing campaigns in SmartCRM. “The co-pilot in SmartCRM is focused on the singular use case of nurturing people who have not yet applied for jobs,” Rebecca said. The co-pilot adapts to the content customers feed it and how candidates interact with the emails.

“These narrow applications usually deliver a better experience because people can see results they can react to and feel confident in,” Rebecca said. Given the complexity of recruiting across roles, hiring teams, and locations, it’s worth it to wait for the technology to catch up rather than risking unproven solutions that claim to do it all, especially with compliance at stake.

5. Don’t invest in skills-based hiring without clear goals

“Skills” is the hottest buzzword in HR as companies seek to upskill and re-skill employees while at the same time looking for skilled candidates. Yet few companies have a consistent way of identifying skills, and AI-based skills tools can be known to go off the rails.?

For example, a marketing manager job description that lists “air traffic control” as a clever metaphor could be read by an AI as a needed skill that no applicant would be likely to have.?

“The big players in the market (such as HCMs) have their own proprietary skills taxonomies that don’t necessarily match the skills taxonomies of other solutions,” Rebecca said. These discrepancies can set teams up for headaches—and international variances only make it worse.

To standardize skills across the European region, SmartRecruiters is aligned with the European Commission’s ESCO skills pillar, which is integrated into SmartAssistant, our AI-based candidate discovery tool.

6. Don’t use incomplete or inconsistent data

AI operates based on the data that it receives. “One of the biggest challenges that organizations face today is the collection of consistent and accurate data,” Rebecca said. She offered an example of an internal candidate being hired outside of the ATS, which would leave that hired candidate’s data (such as their resume) out of the input an AI could learn from.

“An AI learns from how your organization operates, looks at historical trends, and optimizes with external inputs to give you recommendations,” Rebecca said. “Making sure that you have a simple, clean baseline process and easy-to-follow workflows will help capture the right data to support algorithmic learning.”

Hiring practices evolve with the business

“The way we recruit and the way we operate in the context of HR is changing as we speak,” Rebecca said. “You can think of AI as your super suit. The more you know about it, the more you start to adapt to it, the more you get comfortable with it, the more you’ll be prepared for the conversation that will come from your CIO or your CTO about AI optimization in the workplace.”

If that’s a lot harder than it sounds, it’s time to talk to an expert. Get in touch with us today to find out how we’re using AI to help identify and select the most qualified humans to fill your open roles.