Leveraging Generative AI in Human Capital Management

June, 2023

Technology is improving the way organizations attract and hire talent. Applicant tracking systems, online job boards, and social media platforms have made it easier to source, screen, and evaluate candidates. Digital platforms and learning management systems have facilitated the training and development of employees, allowing people managers to efficiently upskill and reskill their workforce. In addition, the introduction of self-service options and automation for multiple HR functions and the development of advanced analytics solutions have transformed the way HR departments operate. For example, nearly 43% of service providers are offering AI-powered virtual chatbots to expand self-service options in HR operations, as noted in our SAP SuccessFactors Services 2023 RadarView™.

Generative AI solutions are taking these HR process improvements to the next level, increasing efficiency and effectiveness. This research byte explores how integrating generative AI with human capital management (HCM) solutions offers a wide range of benefits and augments multiple use cases within the HR landscape.

Generative AI’s influence on HR platforms

Prominent HR platform providers, such as SAP SuccessFactors, Oracle, UKG, ADP, and Workday, are exploring and testing large language model (LLM)-based technologies from the following four dimensions:

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1.Posting job vacancies:

HR professionals invest significant time and effort in conducting research to build market-competitive job descriptions for multiple job requisitions. It involves browsing through large volumes of data regarding skill landscapes within the organization, qualifications required for open roles, and market conditions. Generative AI solutions integrated with HCM platforms can reduce the human effort required in creating job descriptions by automating such time-consuming tasks. For example, HR platform vendors are integrating Microsoft Copilot, a digital assistant based on OpenAI’s GPT-4, with HCM platforms, such as SAP SuccessFactors, to automate the process of designing a job description with required accuracy to reflect the right skill sets, qualifications, and responsibilities for a given open position.

2.Screening and selecting candidates:

The initial evaluation of candidates to determine their suitability for job roles involves HR professionals reviewing resumes, assessing qualifications, and comparing candidates against job requirements. This is another use case where generative AI tools can help shortlist resumes for a specific job description.

After the initial screening, recruitment managers spend significant time writing interview questions to effectively assess candidate skills, qualifications, and suitability for a particular role. By integrating AI models such as Azure OpenAI Service with the HCM platform, interviewers can receive customized suggestions on interview questions based on candidate resumes and job descriptions for similar roles.

3.Upskilling employees:

Generative AI has the potential to streamline learning management for employees by providing personalized and adaptive learning experiences. For example, employees can receive tailored learning recommendations aligned with their career and self-development goals using Copilot in Microsoft Viva Learning, which is integrated with HCM platforms. This enables HR professionals to efficiently bridge the skill gap by delivering targeted training programs that cater to individual needs and enhance overall workforce talent.

4.Personalizing employee experience:

Employee engagement and satisfaction are crucial for organizational success. Generative AI can help HR professionals create personalized experiences for employees by analyzing their social preferences, career goals, and learning needs. For instance, UKG, an HR platform provider, partnered with Google Cloud to leverage its generative AI and LLM-based solutions to analyze proprietary employee data from Great Place To Work®, an independent research institute specializing in the field of employee engagement and organization culture, to offer a personalized experience on its HR platform.

Way forward

The integration of LLMs and generative AI solutions with HCM platforms presents a multitude of possibilities for future development. Although the canonical use case for generative AI revolves around content creation and data analysis, prominent product vendors such as SAP, Workday, Oracle, UKG, and others are exploring ways to elevate generative AI use for strategic tasks by leveraging data-driven business insights.

Using generative AI in an enterprise environment also evokes considerations such as ensuring data privacy and security, addressing algorithmic biases, and maintaining transparency in AI-driven decision-making. As enterprises continue to explore the benefits of generative AI models, it is important to establish mechanisms to monitor their performance in HCM solutions and implement accountability frameworks to address any unintended consequences or ethical concerns. Being more vigilant in selecting generative AI solutions that adhere to ethical guidelines will help mitigate potential biases and ensure fairness and equity in HR processes.

By Gaurav Dewan, Research Director, and Premal Shah, Lead Analyst, Avasant