According to a recent LinkedIn survey, the average recruiter spends about 30 hours a week on admin — sourcing candidates, screening CVs, scheduling interviews and coordinating applications across multiple platforms. This article explores how artificial intelligence (AI) can help hiring teams streamline recruitment processes, find the right candidates more easily, and gain a competitive advantage.
Identifying suitable candidates from a vast talent pool is a concern shared by 52 per cent of talent acquisition leaders. In response, HR teams have already integrated software that aids aspects of the process, such as job advertisement creation, candidate sourcing, application screening and tracking of applicant progress.
The work required to manage applications across different software platforms can be a burden that slows the screening process, raises hiring costs and increases the risk of losing candidates to the competition. Ultimately, administrative tasks can be a distraction from the core function of the role, connecting the right applicant with the right employer.
Recruiters are increasingly using AI to streamline the hiring process, looking at how it can automate administrative tasks. The Sage Group estimated that, in 2021, 24 per cent of companies had started using AI for talent acquisition.
AI-powered tools can use predictive analytics to quickly screen candidate data, CVs, and social media profiles, ranking the candidates against job requirements. Recruiters can also mine data from various platforms to find potential candidates and use AI-enabled chatbots to handle inquiries, schedule interviews and more. This frees up time so recruiters can focus on tasks that require human intuition, such as holding interviews and weighing up the strengths of different candidates.
Not another tool
Recruiters have access to various softwares that support different areas of the hiring process. While these tools may be effective individually, if a software platform or AI tool doesn’t integrate with existing systems, such as calendars and the applicant tracking system, it can cause more fragmentation. Data kept in separate platforms then requires recruiters to extract information from disparate sources, limiting visibility over the entire process.
While many software systems have an application programming interface (API) to collect data in a structured format, businesses also collect vast amounts of unstructured data in files, emails, online messages and other, unconnected systems. Without effective integration, AI tools may only serve a limited purpose and there is no guarantee that different systems will communicate or can be effectively scaled up. One way around this is using a customisable AI data management tool, which can aggregate data from all sources across the business — both structured and unstructured. An effective AI tool can connect and gather all data, from emails and CVs to online application forms, enabling recruiters to find everything they need on one simple platform.
Integrating natural language processing (NLP), such a chatbot that can interpret questions and provide human-like responses can provide further support. Instead of extensive data analysis, recruiters can type simple queries about an application and the tool can answer quickly with a report, chart or written response, making it much easier to extract valuable information quickly. These chatbots can also be useful to applicants who need a quick answer on something related to the role.
Bias is a key concern when applying AI tools to recruitment. AI models are trained on existing datasets, so if there are historical biases, the AI model may reinforce them. An AI tool may also struggle to understand the context of statements, leading to biased interpretations. Addressing bias concerns in AI is integral to ensuring a fair hiring process, and software consultants can build guard rails and train AI tools to help accommodate for this.
For companies that want to carefully manage who can access sensitive, personal data Open AI platforms can introduce privacy concerns. While businesses can limit for how long OpenAI APIs can hold data, using private or customised AI models can give recruiters data ownership, ensuring candidate information is kept secure.
No one wants to spend the majority of their week on administrative tasks that distract them from more meaningful ones, especially not for 30 hours of the week. By implementing AI data management tools, recruiters can reduce the volume of administrative tasks, connect disparate systems and shorten response times to candidates, increasing the changes of securing top talent.