Beginning around 1970, the development of expert systems marked a significant shift in the field of artificial intelligence. These computer programmes were designed to emulate the decision-making capabilities of human experts by applying specialised rules and vast stores of knowledge to complex problems. By moving beyond general-purpose computing, these systems demonstrated that machines could provide valuable assistance in highly technical domains, including medicine, engineering, and business.

The rise of expert systems represented a pivotal stage in the history of applied artificial intelligence. Rather than relying on broad algorithms, these systems utilised a knowledge base and an inference engine to reason through specific scenarios. This approach proved that computers could effectively navigate intricate professional tasks, provided that the necessary expertise could be formalised into a structured set of logical rules.

Despite their innovative potential, these systems faced inherent challenges that limited their widespread adoption. The primary obstacle was the difficulty of capturing the nuanced, often intuitive knowledge held by human professionals. Translating this expertise into a rigid, machine-readable format proved to be a laborious and complex process, which often constrained the flexibility and scope of the software.

Key characteristics of expert systems included:

• The use of specialised knowledge bases to store domain-specific information.
• The application of logical rules to assist in professional decision-making.
• A focus on solving complex problems within fields like medicine and engineering.
• The attempt to codify human expertise into a computational framework.

Ultimately, while expert systems were restricted by the limitations of their era, they served as a foundational development in the evolution of modern computing. By proving that machines could function as expert advisors, they paved the way for future advancements in intelligent systems and helped define the trajectory of AI research for decades to come.