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One of the many business functions that see a significant transformation via Generative AI-based question-answering capability is HR service delivery. HR functions display the complex nature of administrative work.
Some ask about the status of the quarterly performance report, while salary or hire-to-retire-related stakeholder queries are bound to be hectic on the nervous systems.
More labor-intensive HR tasks comprise documentation for onboarding, final settlement during the offboarding procedures, appraisal, and constant communications between stakeholders and HR systems for payment sanctions or approval needs.
Unfortunately, heavy-loaded HR priorities that need high-level attention may pose a hurdle to task management and employee service delivery while impeding the most significant strategic HR functions.
So, the HR help desk is limited by constraints on the inability to provide help for common employee questions comprising 一
These questions often come up via emails, so they get lost in the inbox and go unnoticed.
Though automated HR support can answer these questions, they can be limited and outdated. As a result, traditional HR service delivery or FAQ-based knowledge base of articles that help automate employee queries and service delivery can be repetitive for follow-up questions, resulting in a decline in employee experience.
Additionally, AI tools in HR have not been widely used in the HR space. Generative AI has changed this mindset in the human resource landscape with its unique ability to create content and perform NLP tasks for HR discipline, giving executives a better way to make HR processes more powerful and efficient.
At the same time, Generative AI for HR support has massive potential to augment automation capabilities for common employee queries and empower human resources to be productive and efficient across many HR support tasks.
HR functions are endless. Generative AI tends to automate these tasks by allowing organizations to streamline HR operationsusing various large language model use cases.
At the same time, organizations can look to free HR professionals to become more efficient towards strategic business priorities and help them drive business growth.
A business will grow if it aligns with the ever-changing business needs as new technologies and tools emerge.
There are productivity tools, project management tools, communications tools - and many more for productivity gains across different projects for product-based or service-based companies.
If a new technology trend arrives, businesses must ensure their people also know it and use it wisely to progress.
Say ChatGPT is trending, and the business is aware of its business potential as well as risks. Employees not trained in these tools are less likely to drive effective business results.
GenAI-based HR copilot can help the HR team, and stakeholders get a view into employee performance or reveal which employee lacks appropriate expertise or needs a push to learn and excel.
Generative AI syncs with HR systems and creates a copilot to be widely used to prepare a new learning and development strategy for employees in a more personalized way.
In this particular scenario, Generative AI can fetch data across various HR systems or internal applications where employees work, or employee data inhabit to help build a personalized learning program.
Additionally, Generative AI offers HR teams conversational workflows through integration with business or communication systems. It allows internal employees to leverage essential learning and development materials and upskill themselves easily without expecting HR intervention autonomously.
As a result, HR executives can harness the power of Generative AI and empower employees to contribute to core business functions and drive business resilience.
GenAI helps draw real-time benefits from crucial HR practices like hiring or recruiting.
Generally, we see HR executives need to create a more meaningful job description that best conveys the right message to the applicants and drives cost-efficiency for recruitment drives across various job portals.
Being unable to create descriptions tailored to specific job roles in time, the recruitment process gets delayed.
The longer the time you need to write a description, the more your business suffers.
Known to create exceptional content, HR practitioners can leverage Generative AI to create hyper-tailored job descriptions using large language model systems.
GenAI removes the need for a subject matter expert to create job descriptions. Instead, managers or executives can seek help from junior personnel in crafting a job description using business-specific information available on HR systems or through data systems giving accurate information about a specific role with significant responsibilities.
In addition to this, GenAI can help build a human-centric workplace experience. With HR executives saving time from mundane and repetitive tasks, they can offer more empathetic responses to candidates through the hiring journey, making recruiting a more seamless HR process.
An onboarding process isn’t quite a good experience for HR and employees either.
It is a huge list of tasks that need to be done accordingly so a new hire feels connected, and your organization need not create an opportunity that results in attrition.
Generative AI conversational workflows are as good as you can expect them to be.
There is no constant question and answer from a new hire, yet employee onboarding takes place peacefully and without much chaos or confusion.
Be it a remote setting or an onsite arrangement, GenAI-based onboarding workflows can efficiently connect with the candidate and allow him to be self-reliant in performing necessary actions.
Generative AI for HR, when implemented with your human resource system, new hires are expected to obtain personalized HR support to perform all formalities and get started easily and successfully.
The new hire can experience a seamless benefit because he can effortlessly get massive HR support through a GenAI-based workflow system that guides him to proceed with documentation processes, get the necessary applications, receive welcome messages, or get access to organizational knowledge bases or specific role-based knowledge articles to learn and perform better.
Like onboarding, GenAI also makes it easy and seamless to handle offboarding processes for a leaving employee using conversational workflows.
With automated workflows, employees can follow instructions to get deactivated from organizational systems, settle final payments, etc., which is otherwise very cumbersome and hectic when handled manually.
Generative AI-based HR support is highly preferable for users today because it has a self-service interface backed by personalized and summarized answers.
In the past, HR service delivery could see little adoption of self-service portals due to the need for tailored employee support.
Say an employee wants access to a project management tool for a particular information on a client project.
A rudimentary chatbot surfaces links to documents. After reading through these lengthy documents, it is found that the company has migrated to a new project management tool.
Not only does this lead your team member to lose precious time after navigating these articles, but it also doesn’t solve his problem, leaving him to seek an agent’s help to find the latest information and work.
The cost of employee frustration and disengagement is another piece of employee grievances.
It is a friction-free experience for your employees as and when they leverage Generative AI-based conversational workflows to fetch the latest information and get productive using summarized and straightforward answers in place of a lift of related document folders or links.
The same flexibility can make the HR experience more enriching. In a particular scenario, HR can quickly surface summarized notes of employee interactions through a ticket journey. This translates into significant benefits for agents as they can easily fetch the history of user requests, making it seamless for agents to handle queries and solve them at scale, whether a similar agent handles the case or not.
One more efficacy of a Generative AI self-service interface is that HR executives can quickly generate responses according to user’s request and reduce the time to solve a case.
Employee well-being is integral to any company’s growth. However, providing employees with a safe and healthy work culture constitutes a thriving workplace, helping businesses maintain data compliance and ensure social responsibility.
GenAI-based HR workflows can automate tasks and harness advanced insights through integrations with HR systems or other business applications.
Playing around with this huge volume of data gives you deeper insights into which employees dedicate more hours to business operations, who have uninterrupted hours at work without any vacation, which employees lodge complaints, and so on.
These insights can be handy in allocating necessary resources to align with employee expectations, building a better strategy to help employees thrive, and giving them more personalized services to enjoy their work and succeed.
BCG confirms that Generative AI can create content three times faster using company insights and data. This use case is extremely helpful for HR practitioners in automating NLP-based HR tasks.
Generation of recruiting or hiring notifications or job descriptions can be automated using NLP-based queries inside the Generative AI-based HR systems. HR professionals can save time by prompting GenAI-based tools to create any form of content, such as short and condensed forms of hiring alerts for social media channels, very comprehensive job descriptions to be used on the company website or other dedicated job portals, employee policy, a revised employee policy, company culture playbook, etc.
With HR tasks becoming flexible and easy, HR teams can handle many other critical tasks that take time or drive data-driven decisions for more efficient task enablement.
Instead of selecting candidates manually, HR copilots can provide insights into skills that closely match the candidates' profiles and help proceed to the next step.
HR tasks such as company-wide announcements have become a task for junior-level HR executives, giving senior executives more time to focus on growth and a competitive edge in the market.
An HR copilot is effective in harnessing insights into employee performance to decide appraisal or performance bonus structures.
Similarly, communicating salary breakups, bonuses, or probation performance pay is easy through Generative AI chatbots.
HR copilots always have the latest data to update employees or HR professionals via NLP-based queries in a chatbot.
The effectiveness of automated HR communications is such that HR teams can reduce the load of responsibilities at a large scale yet help employees be satisfied with unique questions.
Boston Consulting Group, in its report, confirmed that Generative AI for HR reduces the time to create content to only 9 days from 42 days. Learning and development courses need fewer iterations and can be approved with 20% of customized suggestions.
Conversational AI with GenAI capabilities enables employees to fetch more meaningful answers from the intuitive interface and helps employees solve problems autonomously. As a result, businesses derive faster problem-solving using QnAs through FAQs or comprehensive and custom answer generation capabilities. This extended capability allows businesses to deliver faster approval times by 40% and reduce the number of HR tickets to the HR help desk.
HR executives can have more flexibility to experience progress on a task on all boards. GenAI can accelerate content generation 3 times faster, driving down the number of HR teams to contribute to content generation and approvals. At the same time, companies can gain 60% cost savings on L&D content, email generation, company policy development, etc.
In our previous articles, we have provided enough context as to why LLM-powered chatbots or question-answering frameworks can limit the accuracy and relevancy of employee queries.
LLM or large language model contains internet-scale data, meaning LLM-powered chatbot trained on data comprising ebooks, various websites, messaging tools, Wikipedia, interviews, and many more data sources.
However, one constraint is that the data has a cutoff time for a certain period valid for employee support only to that specific time and not beyond.
LLMs unable to absorb the latest data continuously can expose users to irrelevant probabilities, resulting in inaccurate and less meaningful answers.
At the same time, black-box theory being integral to LLM data sources, it is tough to discern which source an answer is being retrieved from. As a result, LLM-powered answers lack veracity and produce hallucinations, which may otherwise lead employees to perform some inappropriate actions, impacting business results and reputation.
If your GenAI-based question-answering interface for HR pulls data from a large language model, your HR people cannot provide or access accurate company-related information. Instead, they can get vague answers, which is useless to solve a problem.
Say an HR needs to assess an employee's performance for a specific client project on cloud migration to determine his performance bonus calculations. An HR system backed by an LLM-powered chatbot or interface can surface information that is very generic and incomplete.
Though it automates response, businesses are unlikely to get a resolution and leverage real-time business results.
Generative AI with an RAG model connected to the HR domain data structure or company-wide data can help your organization overcome the limitation of an LLM-powered HR system and offers HR discipline incredible possibilities in retrieving domain-specific HR information or people data.
Focusing on a similar challenge for finding information for an employee on a cloud migration project, if your GenAI-based HR system has a RAG connector with your HR data, you can retrieve crucial data that could help you decide performance contribution to various segments and calculate accurate bonus percentage.
RAG brings several benefits in providing accurate and relevant information to employees and HR for a particular task.
Whenever a new update or event occurs, a RAG model pulls up that data and enhances information accuracy.
At the same time, if your bottom-line budget is limited, yet you want to drive similar business performance and results like that of RAG, Knowledge AI is also an efficient tool to redefine your existing HR processes and make employee support simpler and more intuitive.
A slight difference exists in how Knowledge AI is trained from an RAG being trained.
Knowledge AI appears to be a cost-effective solution for SMBS to augment knowledge search and transform HR use cases or tasks since its training isn’t comprehensive like RAG, which needs custom training solutions with databases and computational resources.
Workativ delivers what SMBs or enterprise leaders expect to drive from Generative AI capabilities.
Workativ conversational AI is a powerful machine learning tool to simplify employee collaborations and communications through effective knowledge discovery and autonomous problem-solving on the employee query side.
To make it easy for existing users and business leaders growing Generative AI interests to leverage the large language model capabilities for HR support, Workativ allows easy integration of Knowledge AI with conversational AI.
With the integration of Knowledge AI in its conversational AI platform, business leaders can allow employees to ask common, sometimes more personal, or custom questions in an ongoing conversation chat window and get answers to solve productivity issues.
Workativ’s platform solves common queries conveniently for employees through a chatbot inside familiar communication channels where employees stay. As a result, HR service desks have less frequent ticket requests to handle and have more time to engage in critical problems and reduce downtime.
Using Workativ’s platform, users can solve everyday employee problems related to,
In addition to offering employee benefits related to common problem-solving, Workativ’s Knowledge AI, open to being trained with Workativ data, external data, or internal data, delivers accurate and contextual answers by launching a semantic search.
Users are twice as likely to increase adoption flexibility with Knowledge AI and gain autonomous problem-solving capabilities for common and unique problems.
Want to know how can you leverage Generative AI in HR through Knowledge AI and take control of HR support? Schedule a call with Workativ today.