Since ChatGPT publicly launched in November, AI has been the hottest topic of discussion in every domain of business. Indeed, the benefits for many professions are evident. Generative AI can be used to write code, design products, create marketing content and strategies, streamline operations, analyze legal documents, provide customer service via chatbots and even accelerate scientific discovery.

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According to a recent study by McKinsey, which examined 63 use cases across 16 business functions, about 75% of the value that generative AI use cases could deliver falls across four areas: customer operations, marketing and sales, software engineering and R&D.

Even though HR is not one of the highest use cases, every HR tech vendor is now creating AI-based products, posing opportunities and challenges for HR leaders to see beyond the hype and decipher how to introduce AI in HR.

Deciphering AI in HR: 3 vendor categories

First, it’s critical to understand the vendor market as it relates to AI. The HR technology landscape can be classified into three categories:

1. Emerging AI

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Most HR tech vendors fall into this category. These vendors add AI to their existing tech offerings. For instance, HCM vendors like ADP may present HR managers with recommendations for pay adjustments via payroll systems or generate reports pinpointing diversity or gender pay disparities. Although these systems might not extensively rely on neural networks or generative AI, they deploy advanced analytics to deliver valuable organizational insights. Applicant tracking systems (ATS) can now autonomously craft job descriptions, draft candidate communications and tailor interview scripts.

2. First-generation AI

These solutions offer built-in AI features. Embracing “single-use” ML models, they often provide intelligent recommendations to users. For example, learning experience platforms (LXPs) or HCM systems may advocate courses based on job roles, activities or specified competencies. A multitude of ERP providers, including Workday, SAP and Oracle, alongside numerous applicant tracking systems, fall into this category.

3. Second-generation AI

These “next-generation” systems are built on AI. Companies like Eightfold AI, SeekOut, Gloat, Beamery and others have crafted their entire platforms around AI-enhanced cores. Data-centric in essence, these companies use deep learning, natural language processing (NLP) and large language models (LLMs) within their core architecture, extending their capabilities by developing models that accommodate a copious array of data elements, scaling from thousands to tens of thousands. Importantly, these systems must transcend bias, maturing into advanced and impartial tools.

See also: To build an AI-fueled culture, leadership views can’t be a ‘mystery’

Solving business problems with AI

While it’s important to clearly determine what AI-based systems you have in your HR tech stack and which you may want to consider, it’s even more important to be clear about how any of these solve business problems for you.

Accuracy, compliance and data quality

Josh Bersin
Josh Bersin

The world of HR is full of textual data, a prime opportunity to utilize generative AI to analyze policies, review compliance procedures and assess data-quality issues at scale and speed. Beyond just monitoring compliance with HR policies and procedures (think about PTO plans, benefits programs or attendance, for example), advanced AI tools can even predict upcoming violations and prevent them from occurring in the first place. Payroll, time and attendance, and benefits processes are all ripe for this type of intervention.

Efficiency and cost savings of HR operations and routine questions

A myriad of documents—encompassing compliance manuals, diversity guidelines, safety regulations, process blueprints and support systems—aid employees in tasks ranging from benefits selection to grasping corporate policies or even password resets.

This intricate domain of “knowledge enablement” and self-service lends itself seamlessly to generative AI. Microsoft’s innovative Power Platform interface to OpenAI facilitates the integration of workflows, empowering interactions with the system. Picture instructing a chatbot to “apply for family leave and request manager approval” or “log an IT case for laptop upgrade.” These use cases provide ample opportunities to save costs and streamline HR operations.

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Improved employee and candidate experience

Generative AI can be a huge differentiator in candidate or employee experience. For example, McDonald’s uses Paradox’s AI assistant (aptly named McHire) to make finding a job at the fast-food giant as fast as ordering a meal, walking candidates through a series of quick, phone-based messages to identify a match and get fast-food workers hired the same day. Starbucks is doing the same with Eightfold AI, even personalizing the new hire experience by bringing in their personal favorite drink on day one.

Opportunities to improve the employee experience improvement are also vast. They include helping employees route and resolve issues quickly and at scale, listening to signals from many different sources to personalize interactions and “magically” transforming the often lackluster employee experience into anticipating needs that people might have before they even express them. Medallia, Qualtrics and Perceptyx all use AI to segment workers into different groups, listen passively and actively, and activate action with the right stakeholders. 

Effectiveness, culture, diversity and closing talent gaps

Arguably the most strategic opportunity to solve problems is to increase the effectiveness of HR (e.g., find the right candidate, develop the right skills, move people strategically to high-priority projects based on skills, etc.).

Kathi Enderes, The Josh Bersin Company
Kathi Enderes

Companies like Nestle, Mastercard, Novartis, Syngenta, Seagate, HSBC and Schneider Electric are using AI-based talent marketplaces from Gloat (using AI skills insights) to match people with opportunities. Recruiting tools like Eightfold, Phenom and Beamery help companies find the “needle in the haystack” and tailor recruiting outreach to increase the chance of luring people to the new organization.

AI-based coaching solutions like BetterUp or Torch help build leaders with transformation skills—and as we know from our pacesetter research, these are the most important skills. Learning solutions like Cornerstone or Degreed help with learning and development of critical skills, further closing the skills gap. And pay equity solutions aimed at creating a more inclusive environment are also built on AI, as they don’t just analyze existing pay equity issues but also predict and prevent these issues further down the line.

With so many use cases, it’s now more critical than ever to strategically think through the sequence and priorities of solutions and decide which business problems are the highest priority at this time—essentially fall in love with the problem, not the solution. Otherwise, you may end up in an “overnudge” scenario (as we heard from a leader in one of the largest transportation companies) where employees and managers ask to turn off the nudges that interfere with doing their work.

For more, tune in to our upcoming HRE webinar “HR Technology for the Future” (11 a.m. PST Aug. 30), read our free research report on the topic and listen to our latest podcast. For members of The Josh Bersin Company,  we offer industry studies, collections, reports, tools, case studies and advisory sessions. Join the Josh Bersin Academy for our latest fully mobile learning experience on AI in HR, built on dozens of learning resources hand-crafted for you.

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