A Beginner’s Guide to Generative AI in Recruiting

The latest hot-button topic in the world of intelligent automation is generative AI. The technology is revolutionizing business workflows, data management capabilities and much more. However, many organizations are still determining how they can leverage the new technology to solve one of the biggest issues in this post-Covid era, finding qualified, skilled, talent.

With 85% of Shared Services Organizations (SSOs) and GBS playing a role in their organization’s digital transformation projects, according to SSON Research & Analytics, learning how to capitalize on the value of generative AI typically falls on the shoulders of shared services.

The following beginner’s guide to generative AI in recruiting will explore the opportunities generative AI is creating for recruiters and how they can adopt it in their daily routine. While it might be too broad scoped to break down every aspect of generative AI in hiring, we can at least look at what the tool is and how it can help with certain key aspects.  

What is generative AI? 

The SSON Glossary defines generative AI as “a type of artificial intelligence that enables machines to generate new content or data, such as text, images, or even entire applications. Unlike other types of AI, such as predictive or prescriptive AI, which are based on existing data, generative AI creates new data or content by learning patterns and rules from existing data.”

If you are looking to separate fact from fiction when it comes to the uses of generative AI, be sure to listen to “AI Unleashed: Transforming Global Business Services With Generative AI” from the SSONext podcast series. In the episode, Phil Searle provides a comprehensive overview of the opportunities generative AI offers GBS, the risks that need to be accounted for, and the processes most equipped to work with the technology. 

How HR has been using AI 

Over the past decade, HR departments have increasingly incorporated AI into their operations to enhance efficiency and effectiveness. AI technology is utilized across various HR functions to simplify processes, support decision-making, and improve the overall employee experience.

For example, AI-driven chatbots can facilitate paperwork and answer new employees' questions, ensuring a smoother transition into the organization. They can also recommend personalized training plans for employees based on their roles and skill gaps. Additionally, AI-driven HR chatbots are employed to assist employees with common queries and provide support.

Generative AI is offering the next step in the evolution of AI. HR departments can harness the power of advanced machine learning and natural language processing to further refine and expand their capabilities in making data-driven decisions, automating tasks, and enhancing the employee experience. 

How generative AI benefits recruiters 

This September, during the Intelligent Automation World Series, SSON was fortunate to welcome Melanie Dunbeck, Automation Strategy & Enablement Lead at Kelly Services, to the digital stage. Melanie was taking part in a discussion about her experiences with generative AI and her vision for how the recruitment agency could use the solution.

During the event, Melanie mentioned that Kelly Services is using generative AI to lighten the load for their recruiters.

“Our recruiters need to process job descriptions. They need to process resumes. There's a lot of communication required when engaging with the client and with our candidates. And so, our use case is around creating and using generative AI help with prompt engineering and transforming large quantities of information,” Melanie said. 

The following are some ways recruiters can use generative AI in their daily work: 

Resume Processing 

• Resume Parsing: AI models can extract and categorize information from resumes, such as education, work experience, skills, and contact details, making it easier for recruiters to search for specific qualifications.
• Skill Matching: AI algorithms will assess resumes to match candidate skills with job requirements listed in the description, thus helping recruiters identify the best-fit candidates more quickly.
• Sentiment Analysis: AI can quickly analyze text in resumes to understand a candidate's enthusiasm and passion for the open position, a useful tool in assessing someone’s cultural fit. 

Generating Job Descriptions 

• Language Optimization: Generative AI can suggest improvements to job descriptions to make them more engaging, concise, which hopefully increases the number of applicants. 
• Inclusion and Fairness: Generative AI can scan job descriptions for biased language and suggest alternative phrasing to promote a diverse applicant pool. 
• Keyword Optimization: Generative AI can recommend relevant keywords to ensure the job description is SEO-friendly and appears on the right job sites. 

Candidate Communication

• Automated Responses: AI-powered chatbots can respond to candidate inquiries, schedule interviews, and provide status updates, ensuring candidates receive timely feedback and recruiters are not overwhelmed with emails. 
• Interview Scheduling: Generative AI tools can coordinate interview schedules with candidates, eliminating back-and-forth email exchanges and allowing recruiters to have control over their calendars. 
• Personalized Outreach: AI can generate personalized messages to engage with candidates, acknowledging their unique qualifications and experiences. 

Risks to be aware of

As with any technology, generative AI is not fool-proof and can be wrongfully manipulated without proper oversight. Here are some examples of how recruiters can misuse generative AI, and applicants can trick the system.

Data privacy – Uploading a candidate's data into a software system runs the risk of the data being exposed in a cyberattack. For example, in September 2022, the American burger chain Five Guys reported a data breach in which 22 applicants' names and social security numbers were revealed. 
 
Bias – Although recruiters can use AI to find a more diverse array of applicants, they need to be aware of potential bias rooted in the AI’s algorithm. A 2018 study found that Amazon's AI recruiting tool had a gender bias, which resulted in the tool rating resumes from women lower than those from men. 
 
False information – While generative AI solutions are complex, they are not lie detectors. It is important to keep humans involved in the vetting process to ensure applicants who lie on their resumes are not making it to the interview stage. 

If you want to learn more about generative AI, be sure to register for SSOW, where, for the first time ever, the conference will provide one-day Bootcamps.

These Bootcamps are focused on generative AI in HR, generative AI in finance, and IT financial management. Each Bootcamp is specifically designed to bring together industry leaders with a common goal: addressing current industry challenges in a specialized and focused setting. Ultimately, this program will help leaders navigate the benefits and intricacies to better support business goals and stay competitive in the market.