Human Algorithms

Human algorithms refer to the logical, behavioural and decision-making patterns people apply when interacting with systems, organisations and technology. In IT and business contexts, the concept is used to understand how human factors influence user experience, process design, automation, AI and enterprise systems such as ERP and CRM. It complements technical models by highlighting the informal rules and behaviours that shape workflows in real life.

Human algorithms are defined by:

• Behavioural patterns: Habits, cognitive shortcuts, and decision strategies that affect how people use digital systems.

• Interaction logic: How users interpret and respond to system interfaces.

• Process impact: Human choices shape practical workflows even when formal processes exist.

• AI complementarity: Helps identify where human judgment should augment or balance automation.

• Relevance in digital development: Used in UX, change management, solution design, and data-driven initiatives.

The term emerged alongside digitalisation and human–computer interaction research from the 1980s onward. With the rise of AI and automation, human algorithms gained renewed relevance as a framework for combining human and machine decision-making.

Within Microsoft’s ecosystem, the concept influences solution design across Microsoft 365, Dynamics 365, and Power Platform. It supports understanding how users adapt workflows, apply automation through Power Automate, and make data-driven decisions using Azure services.

Human algorithms describe how human behaviours shape digital processes and technological outcomes. Recognising these patterns helps organisations build more effective, user-centred and sustainable systems–especially when working alongside AI.