A Glossary of Key AI & Machine Learning Terms for HR Automation with Make.com
The rapidly evolving landscape of Artificial Intelligence (AI) and Machine Learning (ML) is fundamentally transforming human resources and recruiting. For HR and talent acquisition professionals aiming to streamline operations, enhance candidate experiences, and make data-driven decisions, understanding the core terminology is no longer optional—it’s essential. This glossary demystifies the critical concepts shaping HR automation, providing clear definitions tailored to how these technologies can be leveraged within your organization, particularly through powerful integration platforms like Make.com. Equip yourself with the knowledge to navigate this new era of intelligent HR, automate with precision, and drive unprecedented efficiency.
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 a vast array of applications, from automating routine tasks like screening resumes and scheduling interviews to advanced capabilities such as predictive analytics for identifying top talent or flight risks. When integrated with platforms like Make.com, AI tools can be seamlessly connected to existing HRIS or ATS systems, allowing for intelligent data processing, automated communication, and smarter decision-making without manual intervention, significantly reducing the administrative burden on HR teams.
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 task, ML algorithms improve their performance over time as they are exposed to more data. For HR and recruiting, ML is invaluable in tasks like predicting candidate success based on historical data, personalizing learning and development paths for employees, or identifying biases in hiring practices. Through Make.com, HR professionals can automate the feeding of data to ML models, trigger actions based on ML-driven insights (e.g., automatically sending a follow-up email to a high-potential candidate identified by an ML model), or integrate ML-powered tools directly into their recruitment workflows, enhancing accuracy and efficiency.
Natural Language Processing (NLP)
Natural Language Processing (NLP) is a branch of AI that gives computers the ability to understand, interpret, and generate human language in a valuable way. NLP is crucial for processing unstructured text data, which is abundant in HR. Applications include analyzing resumes for relevant keywords and skills, extracting key information from applicant essays, performing sentiment analysis on employee feedback surveys, and powering chatbots for candidate inquiries or employee support. By leveraging NLP through integrations with Make.com, HR teams can automate the parsing of vast amounts of textual data from various sources (e.g., email attachments, web forms), route specific inquiries to the right team, or generate personalized candidate communications, transforming how HR interacts with and understands language-based information.
Generative AI
Generative AI refers to AI models capable of producing novel content, such as text, images, code, or even video, based on the data they were trained on. Unlike predictive AI that identifies patterns, generative AI creates new outputs. In HR, generative AI can draft personalized job descriptions, create engaging outreach emails to candidates, summarize long interview transcripts, or even generate learning content for employee training modules. Integrated with Make.com, generative AI tools can automate the creation of first-draft content for various HR communications, allowing recruiters to focus on refining and personalizing rather than starting from scratch, thereby significantly accelerating content creation workflows and ensuring consistency in messaging.
Large Language Models (LLMs)
Large Language Models (LLMs) are a type of generative AI that has been trained on massive datasets of text and code, enabling them to understand, summarize, translate, and generate human-like text. LLMs are the technology behind popular tools like ChatGPT. For HR, LLMs can instantly answer complex HR policy questions, assist in crafting nuanced employee communications, perform sophisticated resume analysis, or even act as a conversational interface for internal HR support. By connecting LLMs with HR systems via Make.com, companies can automate advanced content generation, intelligent search within internal knowledge bases, and provide highly responsive, AI-driven support channels, dramatically improving efficiency and employee experience by offering immediate access to information.
Predictive Analytics
Predictive Analytics uses historical data combined with statistical algorithms and machine learning techniques to identify the likelihood of future outcomes. In HR, this means forecasting future trends and behaviors crucial for strategic workforce planning. Examples include predicting employee turnover risk, identifying which candidates are most likely to succeed in a role, estimating future hiring needs, or even foreseeing skill gaps. Integrating predictive analytics tools with HR platforms via Make.com allows for automated data collection, real-time dashboards for HR leaders, and triggering proactive interventions based on predictions (e.g., initiating retention programs for employees flagged as high-risk). This empowers HR to move from reactive problem-solving to proactive, data-driven strategy.
Robotic Process Automation (RPA)
Robotic Process Automation (RPA) involves using software robots (bots) to automate repetitive, rule-based digital tasks that typically require human interaction with computer systems. RPA is distinct from AI, as it focuses on automating existing manual processes rather than simulating human intelligence or learning. In HR, RPA can automate data entry into HRIS, onboarding paperwork processing, payroll verification, or the generation of routine reports. Make.com, while more focused on API-based integration, can orchestrate RPA bots by triggering them based on certain events or feeding them necessary data, creating comprehensive automation workflows that bridge the gap between structured integrations and GUI-based automation, significantly reducing manual effort in high-volume, repetitive HR tasks.
Chatbot
A chatbot is an AI-powered program designed to simulate human conversation through text or voice interactions. Chatbots can understand user queries and respond with relevant information or perform tasks. In HR, chatbots are widely used for candidate screening, answering frequently asked questions about benefits or company policies, scheduling interviews, and providing 24/7 support to employees or applicants. With Make.com, chatbots can be integrated with various backend systems like ATS, HRIS, or calendaring tools. This allows a chatbot to not just answer questions but also update records, create tasks, or book meetings automatically, providing a seamless and efficient experience for both candidates and employees while freeing up HR staff for more strategic work.
Data Bias
Data Bias refers to systematic errors or prejudices introduced into data collection, processing, or analysis, leading to skewed or unfair outcomes, especially concerning AI and Machine Learning models. In HR, data bias can manifest in hiring algorithms that inadvertently favor certain demographics over others, performance review systems that penalize specific groups, or predictive models that perpetuate existing inequalities. Recognizing and mitigating data bias is critical for ethical AI deployment in HR. While Make.com facilitates data movement and integration, HR professionals must consciously design their data pipelines and evaluate AI outputs for fairness. Automation, when responsibly applied, can help identify discrepancies and ensure that data used for training AI models is representative and unbiased, promoting equitable outcomes.
API (Application Programming Interface)
An API (Application Programming Interface) is a set of rules and protocols that allows different software applications to communicate and interact with each other. It defines the methods and data formats that applications can use to request and exchange information. APIs are the backbone of modern integration platforms like Make.com, enabling seamless data flow between various HR tools such as Applicant Tracking Systems (ATS), Human Resources Information Systems (HRIS), payroll software, and learning management systems. For HR automation, APIs allow for real-time updates (e.g., a new hire in ATS automatically creates an employee record in HRIS), eliminates manual data entry, and ensures data consistency across disparate systems, forming the essential connective tissue for complex workflows.
Webhook
A webhook is an automated message sent from an application when a specific event occurs. It’s essentially a “reverse API” that delivers real-time data from one application to another without the need for constant polling. For HR automation with Make.com, webhooks are incredibly powerful. For example, when a candidate moves to a new stage in an ATS, the ATS can send a webhook to Make.com. Make.com then “catches” this webhook and can trigger a subsequent action, such as sending an automated email to the candidate, updating a spreadsheet, or notifying the hiring manager in Slack. Webhooks enable instantaneous reactions to events, making automation workflows highly responsive and efficient, and are a core component for event-driven HR processes.
CRM Integration (Customer Relationship Management)
CRM Integration, in the HR context, refers to connecting a Customer Relationship Management system—typically used for managing client relationships—with HR and recruiting tools. While CRMs are traditionally sales-focused, many recruiting teams use them to manage candidate relationships, treat candidates as “customers,” and build talent pipelines. Integrating a CRM (like Keap or Salesforce) with HR systems via Make.com allows for a unified view of candidate interactions, automated communication sequences based on engagement, and seamless data transfer between recruiting and eventual onboarding. This approach ensures a consistent and personalized candidate experience, enables long-term talent nurturing, and provides valuable insights into the effectiveness of recruitment marketing efforts by consolidating all interaction data in one place.
Workflow Automation
Workflow Automation is the use of technology to automate a series of tasks or processes that previously required manual human intervention. It involves defining a sequence of steps, conditions, and actions that should occur when a specific event is triggered. In HR, workflow automation can range from simple tasks like automatically sending a welcome email to a new candidate to complex multi-step processes like onboarding a new employee across multiple departments and systems. Platforms like Make.com specialize in building and orchestrating these automated workflows by connecting various applications through APIs and webhooks. This leads to significant time savings, reduces human error, improves process consistency, and allows HR professionals to focus on strategic initiatives rather than repetitive administrative tasks.
Data Security and Privacy (GDPR, CCPA)
Data Security and Privacy refer to the measures and regulations put in place to protect personal information from unauthorized access, use, disclosure, disruption, modification, or destruction, particularly concerning sensitive employee and candidate data. Key regulations like the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) emphasize the rights of individuals over their data, requiring transparency, consent, and secure handling. In HR automation, ensuring compliance is paramount. While Make.com facilitates data transfer, it’s the user’s responsibility to configure workflows that adhere to these regulations, including secure storage, appropriate consent mechanisms, and timely data deletion. Automating privacy-by-design principles helps HR teams maintain compliance, build trust, and mitigate legal risks associated with handling personal data.
Ethical AI
Ethical AI is a framework and set of principles guiding the responsible development and deployment of Artificial Intelligence systems, ensuring they are fair, transparent, accountable, and beneficial to society, without causing harm or perpetuating discrimination. In HR, ethical AI is crucial given the profound impact AI can have on individuals’ careers and livelihoods. This includes addressing algorithmic bias in hiring tools, ensuring transparency in AI-driven decisions (e.g., explaining why a candidate was recommended), respecting data privacy, and maintaining human oversight over critical AI applications. As HR teams implement AI solutions, especially with automation platforms like Make.com, it’s vital to regularly audit the AI’s performance, challenge its outputs, and design systems that prioritize human values, equity, and fairness, preventing unintended negative consequences.
If you would like to read more, we recommend this article: The Definitive Guide: Migrating HR & Recruiting from Zapier to AI-Powered Make.com Workflows
