Artificial intelligence in business

Artificial intelligence (AI) is a branch of computer science. AI technologies aim to reproduce or surpass abilities in computational systems that are generally deemed intelligent if performed by a human. These abilities include:

• learning
• reasoning
• pattern-recognition
• problem-solving
• visual perception
• language-understanding

Different types of artificial intelligence

There are two main types of artificial intelligence:

• Applied AI - is more common and includes systems designed to intelligently carry out a single task, eg move a driverless vehicle, or trade stocks and shares. This category is also known as 'weak' or 'narrow' AI.
• Generalised AI - is less common and includes systems or devices that can theoretically handle any task, as they carry enough intelligence to find solutions to unfamiliar problems. Generalised AI is also known as 'strong' AI. Examples of true strong AI don't currently exist, as these technologies are still in very early stages of development.

Many modern AI applications are enabled through a sub-field of AI known as 'machine learning'.

What is machine learning?

The roots of machine learning (ML) are in statistics. ML uses algorithms and statistical models to perform a specific task without using explicit instructions, instead relying on patterns and inference. For example, ML applications can:

• read a text and decide if the author is making a complaint or a purchase order
• listen to a piece of music and find other tunes to match the mood
• recognise images and classify them according to the elements they contain
• translate large volumes of text in real time
• accurately recognise faces, speech and objects

Generative AI leverages machine learning to interrogate vast amounts of data, and then generate original and realistic content based on the learned patterns. Find out more about generative AI for business.

How are AI and machine learning used in business?

Over the years, AI research has enabled many technological advances, including:

• virtual agents and chatbots
• suggestive web searches
• targeted advertising
• pattern recognition
• predictive analytics
• voice and speech recognition
• face recognition
• machine translation
• autonomous driving
• automatic scheduling

Many of these are now commonplace and provide solutions to a great number of business challenges and complex, real-world problems. For more AI use cases, see also how businesses are using artificial intelligence.

See also what is Industry 4.0 and discover examples of digital innovation in business.