The simulation of human intelligence in machines that are programmed to perform tasks that normally require human intelligence, such as learning, reasoning, perception, and problem-solving.
AI uses various techniques and algorithms, such as machine learning, natural language processing, computer vision, and robotics, to analyze data, recognize patterns, make predictions, and interact with the environment.
AI is well connected to knowledge management:
- Offering better solutions to Knowledge Management products, based on the new technologies
- Using Knowledge Management to run better AI projects
- While augmenting the machine and human to produce better solutions.

A tool, designed by the US military to learn from past actions, both successful and unsuccessful.
The tool now serves as the most popular tool worldwide for debriefing and includes four (4) questions to be answered:
a. What was expected? Outlining authentic expectations
b. What happened? Focusing on gaps between expectations and reality
c. Why? Root core analysis, explaining deep reasons driving gaps
d. What next? Drawing recommendations for the future.
Many methodologies were developed, making the AAR a very effective and efficient tool for learning and developing new knowledge.

An iterative customer-centered approach to project management, aiming to drive flexible projects and quick, successful results.
Agile was first developed in the software sector, collaboratively writing an agile manifesto that defined its principles.
Over the years, specific IT implementations were developed, including SCRUM as one of the popular ones.
Nowadays, the agile approach is commonly used in Knowledge Management projects, enabling more customer engagement and better customer satisfaction.