As we look to the future of recruitment, it's clear that AI is making a big impact. From deep learning to natural language processing and the latest large language models, embracing AI-powered tools could help recruiters stay competitive, efficient, and effective in managing recruitment data. But, how can AI tools truly benefit recruitment—and recruiters?
In this article, we’ll explore the rise of AI in recruiting, and the ways that AI-powered tools can affect your database, sourcing, and overall efficiency.
The Rise of AI in Recruiting
Although the field of AI has been around for decades, in the last few years AI has become a hot topic with a lot of influence on recruiting.
Deep learning, natural language processing (NLP), and (especially!) Gen AI have all had large impacts on recruiting technology.
Deep learning is a method of training neural networks with large amounts of raw data. NLP enables computers to understand and generate human language, and LLMs are, according to IBM, deep learning models trained on raw data that can generate specific outputs when prompted. Together, these technologies are revolutionizing recruitment by automating processes, improving candidate screening, and enhancing the overall hiring experience.
LinkedIn’s Future of Recruiting 2024 found that 62% of surveyed recruiting professionals expressed optimism about AI’s impact on recruitment, and the recruiting industry has seen the impact of AI-powered technology already.
AI is being applied to a wide variety of use cases in the industry. Large Language Models (LLMs) in particular carry a lot of potential for staffing and recruiting operations, with LinkedIn reporting that 57% of recruiters using Gen AI tools found it faster/easier to write job descriptions, while 45% found it helped automate tasks so they could spend time on more fulfilling work.
How AI Tools Can Benefit Recruitment
Maximizing Your Recruitment Database with AI
With so much data available to recruiters, it’s common for recruiters to find candidate data from several sources, like social media networks, job boards, or their internal database.
Often, this overload of data can make it difficult for recruiters to find the candidate information they’re looking for, and without proper data entry procedures, it’s hard to properly load unstructured data into an ATS or CRM, and easy for data to become disorganized, out of date, or duplicated.
To illustrate the problem with unstructured data, imagine an avid collector of vinyl. For years, this collector has been trying to find one particular jazz album, searching at vinyl stores and flea markets to track it down. But, unbeknownst to the collector, that album had been in their collection all along, purchased in a bulk acquisition they’d made years ago.
Now instead of a vinyl collector, picture a recruiter, who’s spent money on job board views, only to discover that those same candidates existed in their database, buried deep in unstructured data and unorganized files.
Here’s where AI comes in: by leveraging AI and natural language processing, today’s AI-powered solutions can streamline data processing to parse and organize resumes with a contextual understanding of each candidate’s skills and experience. Plus, some tools can even recognize duplicates in your internal database, which can make a big difference in keeping your in-house database clean and reliable.
See how Frank Recruitment Group reduced their resume processing time by 90%
Enhancing Candidate Search with AI
In particular, AI has changed the way recruiters search for talent. In addition to improving the speed at which recruiters can search through large amounts of data, it’s also provided more flexibility and precision in the searches themselves.
For example, machine learning (an application of AI that helps computers learn) and term expansion (which uses natural language processing to find related terms and aliases for the search terms a recruiter is using) help Daxtra Search users craft highly specific, relevant and customizable searches—without spending time crafting complicated Boolean search strings.
AI-powered tech can also help search tools rank candidates based on the context of their skills and experience (a useful feature in the era of skills-based hiring). For instance, Daxtra’s AI-powered solutions score each candidate in search results, giving recruiters insight into why each candidate received their ranking, and placing the most relevant, best-matched candidates at the top of each list of results—so recruiters don’t have to scroll through multiple pages of search results to find the best match.
"If Daxtra Search Nexus says a candidate is number one, that candidate is number one. You don’t have to search through hundreds of candidates. It’s like magic. But, you also have the ability to see starred rankings of candidates to provide transparency in the ranking process, so you know which candidates are a good match and why—that is huge.” – Brian Cunningham, Allen Recruitment
Speeding Up the Recruitment Process with AI
Today’s recruiters wear a lot of hats. Dealing with an overwhelming number of resumes and manual data entry processes can lead to recruiters to deal with tedious issues like poor source attribution, and lead to them losing valuable time that would otherwise be spent connecting with candidates.
"Over the years, I’ve found the amount of time recruiters have spent communicating and building relationships has declined. Now, they’re creating search strings and saving them in a Word doc or Excel file, or trying to prompt ChatGPT to create better content or search strings. They’re bouncing around from their ATS to 10 or 15 different tabs, all while trying to engage with candidates in an increasingly competitive environment.” - Chris Wirt, Daxtra
When AI solutions are trained on the right datasets (i.e., trained on recruiting data for recruiting-focused use cases), they can process large amounts of information more quickly than humans can - and they’re less prone to manual data entry errors like typos. The end result? With properly implemented AI tools, recruiters can reduce their day-to-day workloads, streamline data management processes and make data entry more accurate.
Successfully Leveraging AI in Recruitment
Used effectively, AI can help empower recruiters to improve efficiency and effectiveness by making the most of existing data. However, it’s important to remember that data quality is key to AI’s effectiveness for recruiting operations.
If your team is looking to implement AI, make sure your tech strategy involves key stakeholders, leaves room to properly evaluate each tool you consider and allows for your organization to implement new tools strategically.
Looking for more guidance on leveraging AI in recruiting? Check out Daxtra’s Guide to Gen AI in Recruiting, where we use Daxtra’s 20+ years of experience in AI to break down:
- How recruiters can leverage Gen AI
- What recruiters and technology leaders they should look when evaluating AI tools
- Our outlook on the future of GenAI in recruiting.
