AI recruiting technology is continuing to yield quietly impressive results, with a recent analysis of Avature’s explainable matching tool demonstrating 80 percent accuracy in recommending candidates for a given role. This means that out of the top ten candidates suggested by AI, human talent experts deem eight as relevant.
In a similar analysis, Avature’s AI Resume Parser obtained 90 percent accuracy in extracting relevant candidate information and presenting it ready for use by recruiting teams.
This level of reliability makes it possible to relieve TA teams of often administratively burdensome, time-consuming tasks. Instead, they can focus on more value-added activities, such as engaging with applicants directly and providing strategically relevant market insights.
Focus On Integrated Use Cases to Derive Immediate Value from AI Recruiting Technology
Commentary on AI’s capacity to revolutionize the workplace is impossible to avoid. But a recent report from MIT states that in many fields, it is falling short of expectations and delivering only limited ROI.
The report suggests that to manage expectations and derive immediate value, it’s important to distinguish between an ambiguous AI-driven overhaul of operations predicted by many commentators and those AI tools that integrate easily into existing workflows, apply to defined use cases and are therefore able to provide an immediate boost to efficiency.
Avature’s Natural Language Processing (NLP) team carried out the research to determine the effectiveness of two AI features that fall very much into that second category. The news of their proven reliability comes at a critical time for many talent teams dealing with a frequently unmanageable number of applications.
AI Matching Tools Providing a Timely Productivity Boost For Talent Teams
A cursory glance at the jobs on LinkedIn should be enough to tell you that TA teams have a lot on their hands. In an age of ‘easy apply’ options and AI-assisted serial applicants, it’s not uncommon for companies of all sizes to receive hundreds of applications for a single position.
Manually sifting through this volume of applications can use up much of a recruiter’s capacity, distracting them from value-added work while increasing the risk of errors.
By contrast, AI recruiting technology can efficiently rank candidates according to their fit with a position’s requirements. To do so, matching AI identifies and compares job titles and key skills data from the job description and candidate resume and scores suitability according to predefined weighted factors. Alternatively, recruiters looking to model their search on a previously successful hire can find similar candidates based on experience and skills.
But one of the most compelling advantages of AI in recruiting goes beyond efficiency: it lies in the ability to make hiring decisions more objective.
AI Helps Achieve Fairer, Skills-First Hiring Based on Merit
Traditional resume screening can sometimes favour candidates who “look good on paper” but who are later found to lack what it takes to succeed.
Avature’s explainable AI addresses this by ranking candidates based on the skills and experiences most relevant to a role, ensuring suitability is determined by capability rather than surface impressions or job titles alone. Recruiters can then use the interview process to explore these areas in more detail.
This has a two-fold benefit of helping to filter out those candidates who seem impressive on first glance but lack the required skills to perform the job, while also bringing to the fore those hidden gems who might otherwise have slipped through the cracks.
Of course, any discussion of AI in recruitment must consider the risk of bias. Algorithms trained on historical data can inadvertently replicate past preferences, favoring certain demographics or educational backgrounds. To mitigate this, Avature’s machine learning team has taken proactive measures. Personal identifiers, such as name, gender, age and ethnicity are excluded from training datasets, reducing the risk of biased outcomes at the source.
By applying skills-first evaluations of a candidate, Avature’s AI empowers talent teams to build richer pipelines, surface hidden talent, and make hiring decisions that are both faster and fairer.
AI Agents Set to Further Shake Up The World of Recruiting
Resume parsing, skills extraction and matching, and candidate ranking are already having a huge impact on the work of many talent teams. However, things are about to take an even more significant leap forward.
The introduction of AI agents to undertake much of the repetitive, burdensome administration with greater autonomy is likely to provide a true game-changer. We are now entering an age in which a combination of AI agents drawing on a deep understanding of both HR-specific data and a company’s contextual information will be able to work together to take on whole sections of a recruiting workflow.
This may be as simple as drafting and sending an email in line with the organization’s brand voice, drawing up contract offers in line with company and local guidelines, scheduling and drafting questions for candidate interviews or transcribing and collating decision-maker feedback into a coherent document for review. In every case, human oversight is paramount, but the boost in productivity promised will be more than apparent.
We are only starting to explore the vast potential of AI recruiting technology to deliver new efficiencies and lead us to further evolve how we work. Given the sheer breadth of possibilities, it is difficult to predict every use case and benefit at this time.
For the time being, quick wins and real ROI can be found in the smart automation of mundane and time-consuming administrative tasks and the ordering of large volumes of applications into actionable lists of recommended candidates. But as new opportunities continue to emerge to refine how we engage and hire, it couldn’t be a more exciting time to work in talent.
Interested in learning more about Avature’s AI? Speak to our NLP team to learn more.