While HR departments were traditionally slower to embrace digitalization, the tides shifted dramatically with Covid-19, as companies were forced to adapt almost overnight, taking on digital hiring, training, and remote team management. With this acceleration of technology adoption, HR managers are starting to embrace digital literacy and discover the potential of automation. The HR department is now primed to harness the transformative power of generative AI. In addition, the HR department’s extensive network of applications and interfaces makes it a perfect candidate for quick success in Gen AI implementation, showcasing the effectiveness of the technology.
Before we dive into the use cases, it is good to keep in mind the strengths and weaknesses of Gen AI to better understand its application in the use cases.
Gen AI Strengths
Firstly, Gen AI is very versatile and efficient in processing unstructured data such as texts. It can convert these unstructured data into a structured format such as tabular data which is more useful for tasks. As such, many manual tasks involving large amounts of documents and texts can now be automated at scale. Secondly, Gen AI is very good at generation tasks such as generating a reply based on a query and generating personalized recommendations. This allows more human-like interactions between systems and users which previously were performed through a human agent or the system user interface. Thirdly, Gen AI is also good at understanding language, summarization and translation tasks.
Gen AI Weaknesses
However, Gen AI do have a few weaknesses to note. Firstly, while Gen AI seems to be good at understanding and performing maths, it is often falls short in logical reasoning and deduction, and multi-step planning without additional support systems. Secondly, it is difficult to control the outputs and make adjustments to the Gen AI models. These models are mostly black boxes, making it difficult to understand why a certain output is provided. This could be a critical weakness in many use cases where transparency, explainability and controls are crucial. Thirdly, Gen AI is not deterministic in nature, meaning that it may provide different outputs given the same inputs. This lack of reproducibility would be a concern for many systems with high precision or accuracy requirements. Gen AI systems are also highly dependent on the data it is trained with. It will display the same bias that exist in the data, and mitigating these biases is extremely difficult without going through the time and resource-intensive re-training of the model.
In short, Gen AI excels at processing unstructured text and imitating human-like responses, making it especially useful for tasks such as document processing, data entry, as well as providing suggestions and recommendations. However, for tasks that require high-precision, involve high-risk decision-making, or where transparency and control are critical, it is not recommended to rely solely on Gen AI without additional validation measures.
Top Use Cases in HR
The following applications illustrate the capabilities of Gen AI to respond to real-time employee queries, improve employee learning and knowledge sharing, and improve the daunting challenge of performance management.
Managing Employee Queries
Industry: All industries
Problem: HR departments frequently receive a high volume of employee queries, and responding via emails or Slack channels often lead to manual work and delayed responses. Moreover, employees need to navigate various contact points for different inquiries, only to receive general answers in shared channels. Ensuring consistency in responses while addressing individual needs is a significant challenge for HR departments.
Solution: By leveraging its ability to understand meanings and nuances of natural language, Gen AI powered virtual assistant can respond to a wide range of employee queries in real-time, ensuring consistency and accuracy in the information provided. This tool reduces the manual workload for HR staff and enhances employee experience by offering immediate, personalized assistance.
Example: Through its conversational interface, HR assistants can answer a wide variety of queries based on the provided company policies, including:
Compensation: salary and bonus, promotion and raise, stocks and options, awards and recognition programs, etc.
Benefits: vacation and other leaves, insurance, health and wellness programs, training and education assistance, retirement accounts, etc.
Travel and expenses: hotel/car/flight bookings, reimbursements and approvals, expense reports, corporate card usage, safety supports, etc.
Diversity and inclusion: anti-harassment, diversity training, discrimination, etc.
If the Gen AI tool is integrated with existing HRMS/HRIS, latest information regarding the employee records can be referenced for the automated reply.
Industry Example 1: AskHR, the internal virtual assistant of IBM, provides instant responses to queries relating to employee benefits. Employees can easily get personalized answer regarding HR policy, including their tenure, location, and days of vacation already used, without having to ask an HR staff or dig through a maze of portals. [1]
Industry Example 2: Care.com, a caregiving technology platform, used AI Intelligent Assistant to augment their employee services and improve the remote equity of their workforce. MeBeBot was installed as an app in Slack and configured to align with the Care.com policies, business processes, and culture. Employees globally can receive answers immediately and at any time and help improve the responses using the “helpful” or “not helpful” feature. [2]
Facilitating Learning & Development
Industry: All industries
Problem: HR departments and employees often find themselves at odds over learning & development (L&D) initiatives. While HR aims to provide training materials within their budget constraint, they often face low employee satisfaction and engagement. On the other hand, employees have diverse development needs and struggle to find suitable courses. These challenges could lead to gaps in knowledge and decreased productivity, and even hinder company’s overall potential.
Solution: Gen AI has the potential to transform employee training experiences, as it addresses the challenges of traditional training programs by creating dynamic training courses, crafting personalized training paths, and offering targeted learning assistance.
Interactive and Engaging Content: Gen AI can assist in creating a variety of learning content, such as images, videos, quizzes, game-like modules, and interactive simulations. These diverse formats keep learners motivated and enhance knowledge retention.
Personalized Learning Journeys: Gen AI can customize training plans to individual needs, taking into account their learning patterns, knowledge gaps, and interests. This ensures that everyone, from industry experts to new hires, receives the most relevant content.
Targeting learning assistance: Leveraging its ability to understand contextual data, Gen AI can respond to learners’ unique questions and provide continuous feedback, offering guidance and support for further improvement.
Example: Implementing Gen AI in L&D can significantly enhance the learning experience for employees. Instead of watching the pre-recorded videos, learners can enrol in customized courses, participate through quizzes and games, receive immediate answers to their questions, and benefit from continuous feedback and analytics on their progress. Additionally, creating new courses could become as simple as uploading a file, which promotes learning and knowledge sharing within the company.
Industry Example: Veriff, a global identity verification service company, sought to upgrade its learning tools and chose Sana as its end-to-end learning platform. The AI-powered tool transformed course content by incorporating interactive features like quizzes, polls, and flip cards, encouraged knowledge sharing, as evidenced by a sixfold increase in content creators, and fostered a culture of continuous improvement. [3]
Empowering Performance Management
Industry: All industries
Problem: While performance reviews are crucial for effective HR management, they can be time-consuming, unproductive, and unpleasant for both managers and employees. This stems from the challenges of setting clear goals, providing unbiased and actionable feedback, and conducting productive performance conversations. If these challenges remain unaddressed, they can result in employee dissatisfaction, decreased morale and unproductive teams.
Solution: Gen AI can be used to gain insights into employee performance and improve communications between managers and employees, thereby reducing the time, stress and complexity associated with performance reviews. The AI tool achieves this by addressing the following three challenges:
Helping employees set clear goals that aligns with the team’s and company’s goals: AI tools can analyse performance data of each employee to suggest personalized and measurable goals, while ensuring alignment with company objectives.
Providing unbiased feedback: AI tools can analyse diverse data sources like performance metrics, employee surveys, and peer feedback, and provide more comprehensive view of employee accomplishments, leading to greater trust and better career planning.
Guiding productive conversations: AI tools can generate conversation prompts tailored to each employee’s performance, goals, feedback, and other data, to help managers address key takeaways and foster open and productive dialogues.
Example: With the implementation of a Gen AI-powered performance management tool, performance reviews can be more efficient and effective. For instance, by leveraging the AI “assistant” to draw on data from various sources, managers can provide more objective feedback to employees, allowing them to express clear expectations and offer targeted advice, which will lead to improved team engagement, boosted team morale, and enhanced productivity.
Industry Example: A global hotel and resort chain partnered with Betterworks to develop a fluid goal-setting process anduse the Conversations module, which provides managers with guided support for betterconversations with employees. This led to more impactful dialogues and improved employee satisfaction. [4]
Keep an eye on this page (WIP) as we continuously gather and share the most interesting use cases of Generative AI in different areas.
If you're keen to dive deeper into the world of Generative AI, explore our recommended articles on fundamentals of Gen AI, the cost of LLMs, how to assess Gen AI projects, the EU AI Act, and and our latest compiling of Gen AI use cases in accounting.
Note: The information provided in this article is for informational purposes only. We do not have any business relationship with the vendors and solutions mentioned herein, nor do we endorse or recommend them in any way.
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