A Glossary of Key AI Terminology for HR & Onboarding Professionals

In today’s rapidly evolving professional landscape, Artificial Intelligence (AI) is no longer a futuristic concept but a practical tool reshaping how HR and recruiting professionals operate. Understanding the core terminology is essential for leveraging these powerful technologies to enhance efficiency, improve candidate experience, and make data-driven decisions. This glossary provides clear, concise definitions tailored for HR and onboarding specialists, illuminating how these AI concepts translate into real-world applications within your department. Embrace this knowledge to navigate the AI revolution with confidence, driving innovation and strategic advantage for your organization.

Artificial Intelligence (AI)

Artificial Intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions), and self-correction. In HR, AI powers systems that can automate routine tasks like resume screening, schedule interviews, and personalize learning paths. For onboarding, AI can create tailored welcome experiences, answer common new hire questions, and guide employees through compliance requirements, significantly reducing manual administrative burdens and ensuring a consistent, efficient start for every new team member.

Machine Learning (ML)

Machine Learning (ML) is a subset of AI that enables systems to learn from data, identify patterns, and make decisions with minimal human intervention. Instead of being explicitly programmed for every scenario, ML algorithms improve their performance over time as they are exposed to more data. In recruiting, ML algorithms can analyze vast datasets of candidate profiles, past hiring successes, and job descriptions to predict which candidates are most likely to succeed. For HR, ML can forecast attrition rates, optimize workforce planning, and identify training needs by analyzing employee performance and engagement data, leading to more proactive and strategic talent management.

Natural Language Processing (NLP)

Natural Language Processing (NLP) is an AI discipline focused on enabling computers to understand, interpret, and generate human language in a way that is valuable. This includes capabilities like text analysis, sentiment analysis, and machine translation. For HR and recruiting, NLP is invaluable for automatically parsing resumes and job applications to extract key skills and experiences, eliminating manual review time. It can power intelligent chatbots that answer candidate questions, conduct preliminary screenings, and provide real-time support for new hires during onboarding, making information more accessible and processes smoother.

Robotic Process Automation (RPA)

Robotic Process Automation (RPA) involves using software robots (bots) to automate repetitive, rules-based digital tasks traditionally performed by humans. Unlike more complex AI, RPA typically doesn’t “learn” but follows predefined scripts to interact with applications. In HR, RPA can automate data entry into HRIS systems, generate offer letters, process payroll inputs, and manage employee data updates across disparate systems. During onboarding, RPA bots can automatically provision software access, set up email accounts, and enroll new employees in benefits programs, ensuring accuracy and freeing HR staff to focus on more strategic, human-centric tasks.

Generative AI

Generative AI refers to AI models capable of generating new content, such as text, images, code, or other media, rather than just classifying or analyzing existing data. These models learn from existing data to create unique, original outputs. In HR, generative AI can assist recruiters in drafting compelling job descriptions, personalize outreach emails to candidates, or even create unique onboarding content like welcome messages and training module outlines. It can also help HR teams quickly generate policy documents or internal communications, enhancing productivity and ensuring consistent, high-quality messaging.

Large Language Models (LLMs)

Large Language Models (LLMs) are a type of generative AI that has been trained on immense datasets of text and code, enabling them to understand, summarize, generate, and translate human-like text. They are the technology behind tools like ChatGPT. For HR, LLMs can act as powerful virtual assistants, helping to refine interview questions, summarize long employee feedback reports, or generate tailored responses to common HR queries. In onboarding, LLMs can create personalized learning content, answer complex policy questions, or even simulate conversational scenarios for new hire training, providing adaptable and intelligent support.

Predictive Analytics

Predictive analytics involves using statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. It moves beyond simply describing what has happened to predicting what will happen. In recruiting, predictive analytics can identify candidates most likely to accept an offer or predict future hiring needs based on business growth projections. For HR, it can forecast employee turnover, pinpoint factors contributing to low engagement, or predict the success of training programs, allowing organizations to proactively address challenges and optimize talent strategies.

Chatbots & Conversational AI

Chatbots are AI programs designed to simulate human conversation through text or voice interfaces. Conversational AI is a broader term encompassing chatbots and other technologies that allow natural, human-like interaction with machines. In recruiting, chatbots can engage candidates 24/7, answer FAQs about roles or the company, and even conduct initial screening questions. For onboarding, conversational AI can serve as a virtual guide, answering new hires’ questions about company culture, benefits, or IT setup, providing instant support and ensuring a smooth transition without requiring constant human intervention.

Data Bias

Data bias refers to systematic errors in the data collection process or in the data itself, which can lead to skewed or unfair outcomes when used by AI systems. If the data used to train AI reflects existing human prejudices or historical inequities, the AI will learn and perpetuate those biases. In HR and recruiting, biased data can lead to AI systems unfairly favoring certain demographics in resume screening or performance evaluations, undermining diversity and inclusion efforts. Identifying and mitigating data bias is crucial for ensuring AI tools promote equitable hiring and talent management practices.

AI Ethics & Governance

AI Ethics and Governance refer to the frameworks, principles, and regulations designed to ensure AI systems are developed and used responsibly, fairly, transparently, and accountably. This includes addressing concerns around privacy, bias, job displacement, and decision-making transparency. For HR and recruiting professionals, understanding AI ethics is paramount when implementing AI tools. It involves ensuring AI systems used in hiring are free from bias, data privacy is protected, and employees understand how AI impacts their roles and evaluations. Establishing clear governance policies helps mitigate risks and builds trust in AI adoption.

Candidate Experience (CX) with AI

Candidate Experience (CX) with AI focuses on how AI tools can be leveraged to enhance the overall journey and perception a candidate has when applying for a job, from initial awareness to onboarding. AI can personalize communication, provide instant feedback through chatbots, streamline application processes, and offer transparent status updates. For HR, optimizing CX with AI means creating a more engaging, efficient, and positive experience for potential hires, which can significantly improve employer branding, reduce drop-off rates, and attract top talent in a competitive market.

Automation Workflow

An automation workflow is a sequence of automated tasks and processes designed to achieve a specific business outcome without manual intervention. It involves integrating various tools and systems to execute steps based on predefined triggers and conditions. In HR, automation workflows can manage the entire employee lifecycle, from initial recruitment to offboarding. For onboarding, a workflow might include automatically sending welcome emails, initiating background checks, setting up new hire documents, and scheduling orientation sessions, all triggered by a new employee record. This ensures consistency, reduces errors, and saves significant time.

Skill Gap Analysis with AI

Skill gap analysis with AI involves using AI technologies to identify discrepancies between the skills an organization currently possesses and the skills it needs to achieve its strategic objectives. AI tools can analyze employee profiles, performance data, project requirements, and industry trends to pinpoint specific skill deficiencies. For HR, this enables targeted training and development initiatives, optimizes internal mobility, and informs recruitment strategies to acquire necessary future skills. It transforms skill development from reactive to proactive, ensuring the workforce remains competitive and adaptable.

Hyperautomation

Hyperautomation is an advanced approach that combines multiple AI and automation technologies, such as RPA, machine learning, natural language processing, and intelligent business process management, to automate as many business processes as possible. It extends beyond individual tasks to orchestrate complex end-to-end processes. In HR, hyperautomation could manage the entire recruitment funnel, from sourcing and screening to offer generation and initial onboarding, with minimal human touchpoints. For onboarding, it means an integrated system that not only automates tasks but also intelligently adapts processes based on individual new hire needs, creating a seamless and highly personalized experience.

AI-Powered Personalization

AI-powered personalization involves using AI algorithms to tailor experiences, content, or recommendations to individual users based on their unique data, preferences, and behaviors. This goes beyond simple segmentation to offer truly individualized interactions. In recruiting, AI can personalize job recommendations to candidates, customize communication based on their engagement history, or tailor interview questions. For onboarding, AI can deliver personalized training modules, suggest relevant internal resources, or connect new hires with mentors based on their background and interests, significantly enhancing engagement and accelerating time-to-productivity.

If you would like to read more, we recommend this article: The Intelligent Welcome: AI Onboarding for Next-Level HR Efficiency and Employee Experience