Jun 25, 2024

66% of CEOs think Generative AI can drive significant value in Human Resources.

Chief Human Resources Officers (CHROs) are exploring and implementing Gen AI to streamline routine processes, resume screening, improving employee experience & retention rate.

How organisations can success by implementing Gen AI in HR. revolutionizing talent acquisition, onboarding and employee experience

Since the AI landscape is rapidly changing HR, leaders must stay ahead by understanding the core capabilities and use cases available. Many HR leaders feel a sense of urgency about moving forward with artificial intelligence (AI) in the HR function. 38% of HR leaders have explored or implemented AI solutions to improve process efficiency within their organization (Gartner).

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. HR and executive leaders can harness the power of AI to create a more efficient, effective, and employee-centric HR function for the future.

Primary Goal of Generative AI for HR Processes, Gartner

How organizational can success by implementing Gen AI in HR

Key benefits of Generative AI brings in HR management

  • Lower Recruitment Costs: By automating tasks and improving the efficiency of the hiring process, AI can help organizations reduce recruitment costs.
  • Decreased Turnover: By improving employee engagement and retention, AI can help organizations save money on the costs associated with employee turnover.
  • Increased Talent Acquisition and Retention: By attracting top talent and fostering a positive employee experience, AI can help organizations build a strong and competitive workforce.
  • Improved Innovation: When HR professionals are freed from administrative tasks, they can focus on strategic initiatives that drive innovation and growth.
  • Improved Employee Engagement: Streamlined onboarding, personalized training, and 24/7 support can lead to a more engaged and satisfied workforce.
  • Faster Time-to-Productivity: By providing targeted information and resources, GenAI can help new hires become productive members of the team faster.
  • Increased Efficiency and Scalability: 45% agree that AI in HR boosts their company’s scalability and drives business impact, (People Matters, Eightfold).
  • Enhanced Employer Brand: A positive employee experience contributes to a strong employer brand, attracting top talent.

Which sectors would benefit the most for abopting Gen AI in HR

High-Volume Recruitment Industries Sectors: Retail, Call Centers, Hospitality, Manufacturing
These sectors typically deal with a large volume of applications for entry-level or customer service positions. AI can automate resume screening, identify relevant skills and experience, and shortlist qualified candidates, significantly reducing HR workload and cost saving in this sectors.

Competitive Talent Acquisition Industries Sectors: Technology, Finance, Healthcare, Pharmaceuticals
These sectors often compete for highly skilled and specialized talent. AI can analyze job descriptions and candidate profiles to ensure a strong match, reducing skills gaps and improving hiring quality.

The benefits of AI in recruitment and HR are not limited to these specific sectors. Companies across various industries can leverage AI to improve efficiency, reduce costs, and enhance the talent acquisition process.

What is the future of Generative AI and Human Resources?

The key importance of Gen AI in HR

Generative AI will significantly influence the work carried out by the HR function. This influence encompasses HR operations; recruitment; onboarding, learning and development; and talent management.

Chief Human Resources Officers (CHROs) are keen on exploring and implementing generative AI to streamline processes, reducing monotonous routine tasks, resume screening, generating HR-related content or documentation and improving employee experience, enhancing retention rate.

Is Gen AI going to replace HR?

The future of AI in HR is about augmentation, not replacement. GenAI is more likely to collaboate & assist HR professionals in their daily tasks to improve the productivity & effciency

HR professionals play a crucial role in fostering a positive company culture and building relationships with employees. Their judgment and experience is pivotal to make strategic decisions about talent management, performance reviews, handling sensitive employee relations issues, or complex negotiations during recruitment
The future of HR likely involves a collaborative approach where GenAI handles administrative tasks and data analysis, while HR professionals leverage these insights to make informed decisions and build strong relationships with employees.

What is next for AI in Human Resource?

New Roles and Skillsets: The transition to AI-driven HR requires skilled professionals to manage change effectively and address employee concerns. HR professionals will need to become strategic partners focusing on data analysis, AI implementation, and developing a future-proof HR strategy.

Collaboration with Executive Leaders: Executives and HR must work together to ensure AI implementation aligns with overall business goals and talent management strategies. Organizations need to invest in upskilling HR professionals to develop the necessary skills for working with AI tools and data analysis.

Strong Data Governance: Implement robust data security and privacy practices to protect employee data. Increasing the reliability & accuracy of the Gen AI tech by eliminating the Hallucination & Black-box concerns & enhancing Explainable AI to build trust in AI model

Decision pointsOpen-Source LLMClose-Source LLM
AccessibilityThe code behind the LLM is freely available for anyone to inspect, modify, and use. This fosters collaboration and innovation.The underlying code is proprietary and not accessible to the public. Users rely on the terms and conditions set by the developer.
CustomizationLLMs can be customized and adapted for specific tasks or applications. Developers can fine-tune the models and experiment with new techniques.Customization options are typically limited. Users might have some options to adjust parameters, but are restricted to the functionalities provided by the developer.
Community & DevelopmentBenefit from a thriving community of developers and researchers who contribute to improvements, bug fixes, and feature enhancements.Development is controlled by the owning company, with limited external contributions.
SupportSupport may come from the community, but users may need to rely on in-house expertise for troubleshooting and maintenance.Typically comes with dedicated support from the developer, offering professional assistance and guidance.
CostGenerally free to use, with minimal costs for running the model on your own infrastructure, & may require investment in technical expertise for customization and maintenance.May involve licensing fees, pay-per-use models or require cloud-based access with associated costs.
Transparency & BiasGreater transparency as the training data and methods are open to scrutiny, potentially reducing bias.Limited transparency makes it harder to identify and address potential biases within the model.
IPCode and potentially training data are publicly accessible, can be used as a foundation for building new models.Code and training data are considered trade secrets, no external contributions
SecurityTraining data might be accessible, raising privacy concerns if it contains sensitive information & Security relies on the communityThe codebase is not publicly accessible, control over the training data and stricter privacy measures & Security depends on the vendor's commitment
ScalabilityUsers might need to invest in their own infrastructure to train and run very large models & require leveraging community experts resourcesCompanies often have access to significant resources for training and scaling their models and can be offered as cloud-based services
Deployment & Integration ComplexityOffers greater flexibility for customization and integration into specific workflows but often requires more technical knowledgeTypically designed for ease of deployment and integration with minimal technical setup. Customization options might be limited to functionalities offered by the vendor.
10 ponits you need to evaluate for your Enterprise Usecases

At Fluid AI, we stand at the forefront of this AI revolution, helping organizations kickstart their AI journey. If you’re seeking a solution for your organization, look no further. We’re committed to making your organization future-ready, just like we’ve done for many others.
Take the first step towards this exciting journey by booking a free demo call with us today. Let’s explore the possibilities together and unlock the full potential of AI for your organization. Remember, the future belongs to those who prepare for it today.

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