The field of artificial intelligence is growing so fast that it can be hard to keep track. But there are fundamental processes that underlie many of the AI applications in the human resources field.

Here’s a quick primer, courtesy of Charity Digital’s glossary:

• artificial intelligence - the simulation of human intelligence in machines that are programmed to think like humans.

• algorithms - an exact list of instructions that conduct specified actions step-by-step in software- or hardware-based routines; often used as specifications for performing data processing and play a major role in automated systems.

• data analytics - the act of deriving insights from information.

• machine learning - the use and development of computer systems that can learn and adapt without following explicit instructions, by using algorithms and statistical models to analyse and draw inferences from patterns in data.

• automation - the use of software or physical robots to perform repetitive, routine, or predictable tasks with minimal human intervention.

• natural language processing - a field of AI focussing on the interaction between computers and human language, enabling generative AI models to understand, generate, and manipulate natural language text.

• large language model (LLM) - type of AI algorithm that uses deep learning techniques and massively large data sets to understand, summarise, generate, and predict new content (ChatGPT is an example).

• domain-specific LLMs are trained on narrower sets of data to bring them to a higher, specialised level of expertise in a single subject or handful of subjects (for instance, an LLM trained in finance and market analysis can analyse market trends, condense financial reports into actionable data, or rate potential investments).

• stack ranking - a statistical approach that compares employees’ performances against each other.