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Glossary

Complete list of terms and definitions.

A
AI Assistant

An AI-powered tool that helps users complete everyday tasks—like scheduling, drafting emails, or summarising text—through automation and natural language processing.

AI for data analysis

Technology that enables computers to learn from data, recognise patterns, and make decisions without direct human supervision. 

AI Process Optimisation

AI-driven improvement of workflows by analysing patterns, identifying inefficiencies, and recommending optimised actions.

AI-First Culture

A work environment where AI is regularly used, discussed, and integrated into strategy.

Algorithmic Bias

Systematic and repeatable errors in a computer system that create unfair outcomes, such as favoring one group over others, which can be caused by unrepresentative or flawed training data.

Artificial Intelligence (AI)

Systems or machines that mimic human intelligence to perform tasks and can iteratively improve themselves based on the information they collect

Automation

Technology that performs rule-based, repetitive tasks automatically with minimal human input.

C
Chatbot

A chatbot is an AI-powered system that automatically answers customer enquiries. It can resolve standard questions, relieve the burden on customer service and be available around the clock. Example: An online shop chat that answers questions about delivery times.

Churn Prevention

Churn prevention encompasses strategies and measures to predict when customers might leave and actively prevent this from happening. AI models recognize risk patterns so that companies can react early. Example: Automated discounts or offers for at-risk customers.

Computer Vision

An AI capability that analyses visual data (images, videos) to detect patterns, defects, or objects.

D
Data Cleaning

The process of removing errors, duplicates, and missing values to ensure data quality and reliability.

E
EU AI Act

A comprehensive European Union regulation (effective from 2024, with phased implementation) that categorizes AI systems by risk levels and imposes requirements for safety, transparency, and accountability.

F
Feature Engineering

Creating new, more informative variables from existing data to improve the accuracy of machine learning models.

G
GDPR (General Data Protection Regulation)

EU law on data protection and privacy that addresses the export of personal data outside the EU and requires consent and lawful processing of personal data.

Gradual Adoption

The step-by-step introduction of AI tools into business operations, starting with simple use cases and expanding over time

H
Human Oversight

The practice of reviewing, verifying, and taking final responsibility for actions suggested or completed by AI systems.

Human-in-the-loop

A fundamental principle for the responsible use of AI, which means that a human professional must always be involved in the process, supervising the AI's work and making the final decisions.

Hyper-personalization

The process of adapting products, services, or messages to an individual customer through the use of detailed data and advanced analytics, allowing for much more relevant and effective communication.

M
Machine Learning

A subset of artificial intelligence that uses algorithms to learn from data and improve its performance over time.

O
Off-the-Shelf AI

Pre-built, ready-to-use AI tools that require no coding or development.

P
Predictive Analytics

The use of AI and data analysis to forecast future trends, customer behavior, and market demands, helping businesses make data-driven decisions.

Prompt

A specific instruction or query given to an AI model to generate a desired response or output.

Q
Quality Control

Ensuring products or services meet defined standards through inspection, monitoring, and corrective action.

R
Recommendation Engine

A recommendation engine suggests suitable products or content to users. It is based on algorithms that analyze user behavior and preferences. Example: "Customers who bought this product were also interested in ..."

ROI (Return on Investment)

A measure of the value a business gains compared to what it spent.

S
Scaling AI.

The process of expanding AI use from small experiments to wider business operations.

Sentiment Analysis

Sentiment analysis is an AI process that recognizes moods and opinions in texts. It categories content as positive, neutral or negative. Application: Automatically evaluate customer feedback from surveys, social media posts or reviews.

T
Task Automation

Automating specific high-volume tasks, such as emails, scheduling, or invoicing.

Task Visibility

The ability for all team members to see the status, ownership, and deadlines of assigned tasks in a shared system.

V
Voice Bot

A voice bot is a voice dialogue system that automates telephone calls or voice interactions. It is often used in call centers to answer calls and resolve simple issues without human agents. Example: A hotline that automatically queries account balances.

W
Workflow Automation

The process of using AI tools to handle routine operational tasks automatically, with minimal human intervention.


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