Human resources professionals find themselves at a crossroads where the future of work intersects with advancements in generative AI. Generative AI is the buzzword for this year, and the evolving landscape of digital transformation within the enterprise requires HR leadership to adopt a new approach.

On the one side, Generative AI promises to reshape the HR function by automating tasks, analyzing data, improving decision-making processes, and revolutionizing the employee experience. On the other hand, it is essential to understand how to use Generative AI to its full potential, the ethical considerations, and the role humans will play when a machine can do many of their tasks.

In our latest webinar on “Unlocking HR Potential with ChatGPT and Automation”, HR experts Ranjit Pandit, Vice President of Human Resources at Zensar Technologies; Ajit Pethkar, Digital Enterprise Architect & IT Leader at Tata Technologies; Sudhindra Haribhat, Vice President – HR and Growth at AutomationEdge, Vaishnavi Joil, SME and Solution Architecture at AutomationEdge has shared their take on the buzz of Generative AI and its potential in scaling their HR process. ‘

Evolution of HR

We all have seen the evolution of HR processes and technology has been remarkable over the years. But what created the hype for adopting technologies in the HR system? Here, Ajit Pethkar, Digital Enterprise Architect & IT Leader of Tata Technologies, stated, “In the past, organizations relied on manual storage of personal files and paper-based appraisal and increment letters. Departments were filled with cabinets and files, leading to inefficiencies, and the need for streamlining and improving efficiency drove the adoption of HR software solutions.”

The introduction of Applicant Tracking Systems (ATS) revolutionized recruitment processes, making job postings, candidate screening, and interview scheduling faster and more efficient.

Many organizations have now transitioned to cloud-based HR systems like Oracle Fusion for their critical HR operations.

Also, the COVID-19 pandemic further highlighted the importance of technology in HR as remote work became prevalent. Organizations established dedicated HR technology departments to focus on tech-driven solutions.

What’s the Sudden Hype About Generative AI?

Artificial intelligence (AI) has been a topic of interest for decades, but this year holds special significance due to the emergence of generative AI, which has become a buzzword. This development is not limited to just ChatGPT; it represents a broader shift in AI capabilities. To understand this better, let’s look at the progression of AI.

Ranjit Pandit, VP of Human Resources, Zensar Technologies, has stressed here that AI primarily worked with structured data sets, which were well-defined and easily recognizable in a specific format. Decision-making based on such structured data was a common practice. However, with the rise of social platforms and other sources of information, a substantial amount of unstructured data became available. Unstructured data differs significantly from structured data, lacking a predefined format. This transition necessitated using machine learning algorithms to classify and identify patterns within unstructured data, enabling data-driven decision-making.”

The hype surrounding generative AI is justified, but its applicability and impact will unfold over time. It can potentially revolutionize industries and workflows, and its development is an exciting space to watch closely.

Potential Applications of Generative AI in HR

As discussed above, Generative AI came out as an extension to scaling existing automation solutions; businesses can utilize it in the HR process and relieve the employees to focus on the decision-making process. HR experts in this webinar have discussed some applications where Generative AI can help in HR. Lets have a look at them-


Creating Better Job Description

Creating, revising, and refining job descriptions, guides, and HR policies is often time-intensive and demanding. Generative AI offers an effective solution to streamline these processes. Generative AI can easily create job descriptions by analyzing skills profiles, work histories, and external data sources, enabling it to generate job requirements that are both realistic and unbiased. This helps foster a more inclusive hiring environment and contributes to more accurate and effective candidate matching.

Offering Personalized Employee Onboarding

Employee onboarding is a time-consuming process across the business due to time and manual efforts. Many tasks involve employee onboarding, like creating job descriptions, screening candidates, onboarding new joiners, sharing data access, and much more. Utilizing RPA, businesses can automate the tasks involved in the process and eliminate repetitive processes. However, it may not provide personalized training or adapt to individual learning styles.
Here, Generative AI can add a touch of personalization, and it can create personalized onboarding materials, answer employee questions using natural language, and even adapt training content based on individual progress and preferences, making onboarding and training more efficient and engaging.

Assist with Performance Management

Conducting performance reviews and effectively managing them can pose challenges for HR professionals and managers, often demanding significant time and effort. Many managers need help conducting thorough assessments for every employee, which is time-consuming.
Generative AI can be a savior to provide managers with valuable insights derived from employees’ work and performance data, aiding in more efficient performance reviews and evaluations. Ranjit Pandit, VP of Human Resources, Zensar Technologies, here stressed that“Generative AI can also assist in tasks such as creating performance review templates, defining key performance indicators (KPIs), conducting real-time performance monitoring, and helping managers perform training need analysis based on the given data insights.

Help in Payroll Management

Generative AI can automate various aspects of payroll processing, including data entry, calculation of salaries, and tax deductions. This reduces the likelihood of errors and saves time. Using Generative AI, employees can analyze large datasets to ensure compliance with labor laws, tax regulations, and company policies, helping prevent payroll errors and legal issues.

Additionally, Generative AI with automation can predict future payroll needs based on historical data, making it easier for HR professionals to plan for hiring, raises, and budget allocation. The HR team can also integrate bots with the generative AI and respond to employee queries related to payroll, improving employee satisfaction and reducing the workload on HR personnel.

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Potential Challenges to Overcome while Implementing Generative AI

While the potential of groundbreaking AI models that generate content is exciting, there are also significant challenges and risks associated with the risk of misuse, algorithmic bias, the intricacies of technical implementation, and the need for workforce adaptation. Our HR experts have shed light on the potential challenges that can be a roadblock while implementing Generative AI

Potential Challenges to Overcome while Implementing Generative AI

  1. Bias and Fairness

    Generative AI models can unintentionally acquire and perpetuate biases from the data they are trained on, resulting in unfair or discriminatory outcomes. This is a particularly worrisome issue in enterprise applications where the stakes are high, such as making hiring decisions.

    As per Ajit Pethkar, Digital Enterprise Architect & IT Leader Tata Technologies, “Opportunities offered by Generative AI can be overwhelming, but It’s important to ensure that the AI systems we develop are fair and do not perpetuate existing biases. Also, privacy and security are equally important components to consider when working with generative AI technologies, as it ensures fairness and accountability.

  2. Integration with Legacy System

    Integrating Generative AI models with existing enterprise systems and processes can be challenging, as it requires seamless data exchange, security hygiene, interoperability, and alignment with existing workflows. Here businesses must adopt a strategic approach to make a smooth transition.

    Vaishnavi Joil, SME and Solution Architect at AutomationEdge has shared that “One approach to integration involves utilizing pre-built plugins available in automation-rich platforms. These plugins can facilitate user interface (UI) automation, allowing data to be exchanged between the AI system and HR software seamlessly.

    Another option is to establish integration through APIs (Application Programming Interfaces). However, challenges can arise when APIs are not readily available or when they come with associated costs. In such cases, a hybrid approach may be adopted. This involves automating certain tasks through UI automation and simultaneously extracting data from the target system, even if it’s not directly related to HR processes.”

  3. Navigating Change Management

    Many organizations are currently considering AI implementation. It’s evident, both in the literature and discussions, that there’s a certain level of employee apprehension regarding job security. AI is predicted to replace approximately 75 million jobs but create around 133 million, resulting in a net gain. However, HR professionals need to take proactive steps in preparing their teams for this transition.

    Ranjit Pandit, Vice President of Human Resources at Zensar Technologies, has shared that one approach can be straightforward and transparent. It involves communicating the organization’s AI strategy to employees and highlighting the value they will gain from it. This includes explaining the benefits of AI, how it can augment their work, and, Additionally, sharing success stories can help employees understand the tangible benefits and foster greater acceptance of AI implementations.


Generative AI holds significant potential to add value, especially in the context of RPA (Robotic Process Automation). While RPA primarily focuses on task automation, adding a conversational AI layer, like an HR assistant bot, can bring a more interactive and engaging dimension to the automation process. This layered approach can lead to the creation of additional use cases and enhance the overall employee experience.
This transformation extends beyond HR alone, impacting functions like onboarding, payroll, audit, and employee experience. It’s an opportunity for organizations to start automating repetitive tasks, progress to AI, and explore the possibilities offered by generative AI.