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Human Resources has become an increasingly important part of enterprise AI transformations everywhere. According to Gartner, 38% of team leaders are exploring how AI in HR—and generative AI solutions in particular—can improve process efficiencies within their departments. And they’re feeling the pressure—from their executive leaders above and from their competitors all around. In fact, 76% believe if their organization does not deploy generative AI in HR operations within the next 1-2 years, they will lag their industry peers.
Fortunately, advances in HR-specific AI use cases are helping organizations close that gap (and in a fraction of the time). Generative AI for recruiting has become a particularly important focus area, as digital talent acquisition has become the de facto norm. Let’s explore the evolving role of AI in HR and how enterprises are leveraging this game-changing technology to gain an advantage in today’s highly competitive talent market.
Why HR needs AI today
It’s no secret talent acquisition is costly: screening candidates, conducting interviews, onboarding new hires, etc. This process alone can already amount to three to four times the position’s salary, according to the Society for Human Resource Management (SHRM). It’s also becoming more difficult. According to a Glassdoor survey, 76% of recruiters consider attracting the right job candidates their biggest challenge. That’s largely because job roles themselves have evolved with technology. Today, more positions involve collaborating with AI than ever before. That leaves a massive skill gap between AI-savvy candidates and traditional candidates who may need additional upskilling.
In fact, the top challenges IT and technology talent leaders expect to face moving forward are all skill-based: their ability to attract skilled candidates (40%), increased competition for hard-to-find skills (35%) and growing scarcity of specialty skills (32%). That’s according to 2024 Talent Trends research by Randstad Enterprise. The report also revealed that more than half (54%) of enterprises say their HR departments are being asked to do more with less this year. For talent teams grappling with ballooning recruiting costs, chronic talent scarcity and a widening skills gap, that’s a serious wakeup call for needed improvements in productivity and candidate experience.
That’s where AI comes in. Today, the HR teams making the biggest impact—in top talent acquisition, candidate experience and recruiting cost reduction—all have one thing in common: they’re leveraging AI to make better hiring decisions and to operate more efficiently. What’s more, they’re starting small, using sharp, foundational use cases (like candidate screening and real-time interview guidance) to improve domain-specific models and establish workflow after workflow. And it’s paying off in a big way—with recruiting costs reduced by up to 30% and a 20% improvement in hire quality at leading companies.
How AI is transforming the role of HR in talent acquisition
From assisting recruiters during live interviews to supporting the hiring and placement decisions of managers, there are many applications of AI in HR today. Let’s explore the top three impact areas enterprises considering deploying AI in HR should focus first on:
AI’s impact on recruiters
Imagine having an elite hiring professional at your side at every step of the recruiting process. Now imagine that professional sidekick also has an intimate knowledge of your business and of the role you’re trying to fill. That’s how an AI-driven recruiting copilot works. Combining computer vision, conversational, generative and emotion AI (including tonal and sentiment analysis) and HR knowledge management, advanced copilots, like Uniphore’s Q for Recruiting, streamline both candidate-facing and backend tasks, summarizing resumes, generating live interview questions and prompts, analyzing candidate engagement and more. The results: faster hiring, better candidate matches and an improved candidate experience.
AI’s impact on hiring managers
AI isn’t just a tactical tool for recruiters engaging with candidates; it’s also a valuable source of talent-based intelligence for hiring managers and decision makers. Using AI-driven analytics and interview summaries, hiring managers can quickly review candidates, maintain consistent interview practices and improve the quality of insights available to decision makers. These capabilities (and others) are essential for fostering data-driven HR strategy and planning.
AI’s impact on candidate experience
Another popular use case of AI in HR is recruiter coaching and guidance. Remember that recruiting copilot we mentioned earlier? Managers can use the data from candidate interactions, interviews and more to help recruiters hone their skills and develop areas identified by AI for improvement. This includes empathy and rapport building skills, which can be difficult to assess without being in every meeting. Using emotion AI, advanced conversational intelligence software, like Q for Recruiting, can measure a recruiter’s level of engagement and empathy during candidate interactions. Managers can then use this information to evaluate performance and craft skill-building programs to fit recruiters’ individual needs—ultimately improving the experience for both the recruiter and the candidate.
Implementing AI within your HR department
By now, the benefits of AI in HR should be clear: more effective hiring, faster onboarding and training and better employee retention, just to name a few. Let’s now shift to how individual departments can successfully implement AI in HR operations:
Develop an AI blueprint that includes HR
The companies with the best AI transformation track records all have one thing in common: an enterprise-wide AI blueprint. That includes provisions for developing AI in HR. Starting with a foundational multimodal AI and data platform, enterprises can transform their data into AI-ready knowledge that can then be used by HR-specific AI applications (including generative AI applications, like Q for Recruiting). This includes data from a variety of recruiting sources, such as LinkedIn, a company’s applicant tracking system (ATS) and more. This foundational approach creates a self-improving feedback loop: the more employees interact with AI in HR—across recruiting workflows—the more effective the technology becomes. What’s more, data taken from candidate interactions can be used to improve other employee-driven AI applications, both within HR and across other functional areas such as Sales and Customer Service.
Prepare talent acquisition teams to work with AI agents
Because human employees will be working alongside AI in HR, it’s important to drive adoption early on. This starts with hands-on experience at the Agent or Application level. Pre-built, domain-specific applications can accelerate this adoption. Q for Recruiting’s intuitive interface, for example, encourages user engagement, accelerating recruiter proficiency with minimal training. As recruiters become more familiar with next-generation tools like AI agents, the more likely they are to use them regularly and effectively.
Continuously improve how—and where—you use AI in HR
The more teams interact with AI in HR, the more effective the technology—and its users—become. By starting with a few foundational use cases enterprises can quickly build a vast corpus of knowledge that can be used to develop other applications or to explore entirely new use cases. That’s the beauty of a unified AI and data platform—its infinite flexibility and scalability. And as enterprises everywhere enter the AI Era, those with the ability to improve and grow their core HR functions won’t just attract the best talent, they’ll monopolize it.
Get started with AI in HR
Take the first step with Uniphore’s generative AI solution, Q for Recruiting.