Estimated reading time: 10 minutes
The field of Human Resources is evolving beyond traditional practices by integrating AI into various facets of employee management and engagement. From automated onboarding to analyzing employee performance, the use cases of Gen AI in HR are aplenty.
However, unlike past AI technological trends, AI Agents created using GenAI have much more to offer than mere data analysis. They can be used to creatively generate content, condense complex information, and automate repeated tasks, thereby offering HR teams many new and improved capabilities.
From chatbots streamlining communication, to AI-powered recruitment insights, early adopters are already experiencing the efficiency and actionable intelligence Generative AI brings. As these deployments translate to tangible results, the reach of AI in HR is set to grow exponentially.
But the impact goes beyond simple efficiency!
| “76% of HR leaders believe that if their organization does not adopt and implement AI solutions, such as generative AI, in the next 12 to 24 months, they will be lagging in organizational success compared to those that do.” – Gartner |
Executive teams seek deeper, more insightful partnerships from HR, and Generative AI makes this future a reality. As AI in HR transitions from administrative tasks to leading strategic transformations, the technology becomes crucial for upskilling teams and unlocking value as their influence expands across the organization.
Companies Embracing Gen AI in HR: Real-world Examples
JustEat: Leveraging Gen AI Chatbots to Engage Candidates
Fast food giant JustEat tossed out the old resume playbook and embraced a skills-first hiring approach powered by AI. Instead of relying on traditional resume screening, they leveraged AI-powered chatbots to engage candidates with targeted questions, gathering valuable insights beyond a resume’s limitations and cognitive ability tests to measure essential skills like problem-solving and critical thinking. This led to a reduction of the company’s recruitment time by 50%.
L’Oréal: Using AI Agents to Shortlist Recruits
L’Oréal uses Gen AI-powered chatbot Mya, the AI-powered chatbot, takes center stage in the early stages of recruitment, fielding candidate questions and gathering crucial details like availability and visa status, saving recruiters precious time.
Next up, candidates meet Seedlink, an innovative AI software that analyzes their responses to open-ended interview questions. This goes beyond resumes, uncovering hidden gems who might have otherwise slipped through the cracks. In one success story, the company reported a remarkable 200-hour time savings while hiring 80 interns from a pool of 12,000 strong!
Through intelligent surveys, organizations can systematically collect data on what truly makes employees tick, paving the way for a more inclusive and fulfilling work environment. These tools act as smart detectives, pinpointing areas for improvement and recommending strategic actions that benefit the entire team. Think of it as a GPS for employee engagement, guiding companies towards positive business outcomes.
Panasonic: Analyzing Data via an AI Agent to Impact Employee Experience
Take Panasonic North America’s adoption of the Visier People Insight platform as a prime example. This AI-powered solution has transformed their HR management by providing accurate and actionable insights to shape people strategies. By leveraging data, analytics, and real-time feedback, they’ve seen a tangible impact on employee experience.
According to Lydia Wu, Director of HR Strategy and Technology, encouraging a healthy work-life balance has even led to increased productivity. AI isn’t just about automation; it’s about creating a workplace where employees feel valued, heard, and empowered to do their best work. With the right AI tools, companies can unlock the true potential of their workforce and pave the way for a brighter future for both employees and the organization itself.
How Are Companies Integrating AI?
SaaS tools vs Building Your Own Private AI Agents
With the advent of GenAI, there is much debate about which is the best method for implementing GenAI in an organization.
The most commonly applied method for most organizations is implementing GenAI tools thorugh a pre-set SaaS platform. This allows the company to subscribe, set up and start running AI functions such as chatbots without delay. There are several SaaS companies that offer such pre-built subscription services that enable companies to streamline their processes. However, there can be some limitations to such offerings.
Gradually, these SaaS subscriptions start to inflate, transforming into significant expenses that weigh heavily on a company’s financial statements. While SaaS tools might be a convenient option in the short-term, it can become a financial burden in the long run.
- Subscription models are often offered on a per-member basis.
- Most SaaS tools operate on a usage-based pricing, charging for metrics like every API call or data storage.
- Your data is hosted on an external cloud, which cannot guarantee security.
- A downtime at the end of the provider can delay business operations.
- There are different tools for different functions; marketing, automation, supply-chain management. All these when bundled together can make the overall costs astronomical.
The second method for companies to deploy AI applications while maintaining their privacy and security is by building AI agents from scratch. This requires extensive knowledge and understanding of artificial intelligence, engineering and machine learning. Not all organizations are able to initiate such an undertaking, especially if they have limited resources.
- It requires coding expertise as well as a deep, technical understanding.
- Requires infrastructure support
- Takes months or years of work to develop and deploy
The third option, is building your own private GenAI Agent using tools like Langchain or Lyzr’s SDKs.
Langchain is a popular framework for developing AI agents. This too, however, is time consuming and requires a certain level of technical expertise.
Lyzr, on the other hand, is the simplest agent framework that companies can use to build and deploy their own private and secure AI agents. These agents are customized on pre-built SDKs (software development kit), and require only a few lines of code and minutes to deploy.
What GenAI Agents You Should Build for Your HR Department
HR services are dependent on a lot of paperwork and processes. This can be streamlined with a set of different types of GenAI agents, catering to specific needs. Here are a few examples:
- Employee Support Agents: Chatbots powered by generative AI that can provide 24/7 support, answer common questions, and resolve simple issues for employees.
- Content Development Agents: Whether it is content for training and development modules, or for internal or corporate communication, GenAI tools can rapidly create and share content with minimal human-intervention.
- Automation Agents: Generate AI can automate repetitive tasks, such as data entry, report generation, performance review, feedback analysis, freeing up the time of HR managers for more strategic work.
Check out our demo to get a better understanding of how you can leverage the revolutionary power of Gen AI in HR to propel your business forward!
Use-cases Built by Lyzr (Open Access)
Automation in HR processes can help save time and provide a seamless experience for the company employees. Here are a few ways that Lyzr’s SDKs are being used within the HR function to help streamline processes at the organizational level.
New Employee Onboarding Chatbot
AI Chatbots play a crucial role in orienting new employees by guiding them through the onboarding process. These intelligent virtual assistants offer essential information on company policies, procedures, and culture. Additionally, they efficiently address routine queries and provide assistance in completing required paperwork.
Employee Training and Development
Conversational Analytics AI has the capability to analyze employee performance data and feedback. Through this analysis, it can personalize individual training and development programs, ensuring that they are in sync with both the aspirations of the employees and the strategic needs of the company.
HR Policy and Benefits Information
Utilizing Retrieval Augmented Generation (RAG) search engines can assist employees in effortlessly retrieving HR policies, benefits information, and other pertinent documents. This application enhances their comprehension of such materials, fostering better understanding and adherence to company guidelines and policies.
Popular Use Cases of Gen AI Lyzr Can Implement for Human Resource Management
When we think of AI in HR, we instantly picture chatbots. However, Generative AI has much more to offer. It boasts of offerings with tremendously insightful and impactful applications that go far beyond basic interactions. All you have to do is input your requirements and create an AI Agent that functions as per your business requirements. To give you an idea, here are a few use cases of Gen AI’s capabilities in the HR domain:
Data-Driven Interview Insights
Even though interviews are a mix of data analysis and gut feelings, Generative AI goes a step forward by analyzing interview transcripts, identifying recurring keywords, sentiment analysis, and even detecting potential red flags in an applicant’s responses. This allows for more objective and data-driven hiring decisions, reducing unconscious bias and ensuring you find the best fit for the role. Imagine pinpointing candidates with strong leadership potential based on their language use, or identifying inconsistencies in responses that warrant further exploration.
AI-powered Performance Reviews
Say goodbye to subjective, one-size-fits-all feedback. Gen AI in HR can analyze performance data and feedback from multiple sources, including self-evaluations, peer reviews, and manager assessments. Using this data, it can generate personalized and objective performance reviews, highlighting strengths, identifying areas for improvement, and suggesting relevant learning resources. This promotes fairness and transparency, while also ensuring feedback is tailored to each individual’s needs and development goals.
| A new SHRM study shows 1 in 4 businesses leverage AI and automation for HR activities, particularly recruitment and hiring. |
Automated Onboarding Process
From personalized onboarding emails to targeted career development recommendations, Gen AI can take content personalization to a whole new level. Imagine new hires receiving welcome messages specific to their role and interests, or employees getting learning recommendations based on their skills and career aspirations. This boosts engagement, fosters belonging, and ensures every employee feels valued and on the right track.
Predictive Talent Management
Instead of reacting to talent gaps, Gen AI can help you proactively anticipate them. By analyzing employee data and industry trends, it can predict potential skills shortages and identify high-potential employees who can be upskilled or promoted. This allows you to build a future-proof workforce and develop talent internally, saving time and resources compared to external recruitment.
Personalized Learning Journeys
Forget generic training modules. Gen AI can create individualized learning paths tailored to each employee’s learning style, current skills, and career goals. It can even deliver microlearning content in bite-sized formats, making learning more engaging and effective. This empowers employees to take ownership of their development and ensures they acquire the skills needed to excel in their roles.
These are just a few examples of how Gen AI is transforming HR beyond chatbots. By harnessing its power, organizations can unlock a more strategic, data-driven, and personalized approach to human capital management, ultimately driving organizational success and employee satisfaction.
The Future of Gen AI in HR
Although still emerging in workplace applications, generative AI is set to evolve beyond being merely a feature in HR tech to becoming a foundational enabler. This transition involves integrated functionality, spanning from supporting implementations to translating code and data sources, essentially encompassing a diverse set of skills.
Major players in Human Capital Management (HCM) systems are expected to open their marketplaces, fostering innovation at the edge. HR leaders must stay vigilant, considering additional solutions that align with their evolving needs. It is crucial for users to embrace responsible AI and explainable AI concepts as essential capabilities to mitigate the impact of negative bias.
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