What is Artificial Intelligence (AI)?


As a field of computer science, Artificial Intelligence (AI) is the science of making a computer, a computer-controlled robot, or software think intelligently, in a similar manner to intelligent humans.

The aim of Artificial intelligence (AI) technologies is to replicate, reproduce and even surpass those abilities and tasks that are generally thought to be intelligent, and would usually be performed by a human.

These tasks are typically classified into three categories, namely mundane, formal, and expert:

  • Mundane or general tasks – Routine tasks which require common sense reasoning. For example, natural language, perception, robotics, vision, speech.
  • Formal tasks – Tasks which requires logic and constraints to function. For instance, mathematics, gaming (chess, backgammon, checkers), verification.
  • Expert tasks – Tasks which require high analytical and thinking ability, a task that only professionals can do, such as, consulting, financial analysis, engineering, medical diagnostics, scientific analysis.

When conducting these tasks, AI systems will demonstrate some of the following behaviours associated with human intelligence: knowledge representation, learning, manipulation, motion, pattern-recognition, planning, problem-solving, reasoning and visual perception, and to a lesser degree, creativity and social intelligence.

Types of artificial intelligence

Broadly, artificial intelligence can be split into two types:

  • Narrow Artificial Intelligence – Also known as ‘weak’ AI, is the more common type and refers to systems designed to carry out a single task intelligently. Narrow AI has a vast number of emerging applications, for example, organising personal and business calendars, responding to simple customer-service queries, helping radiologists to spot potential tumours, flagging inappropriate online content, and detecting wear and tear in elevators.
  • Artificial General Intelligence – Also known as AGI or ‘strong’ AI, and is very different from weak AI. Strong AI includes systems or devices that can theoretically handle any task. These systems or devices have adequate intelligence to identify solutions to unfamiliar problems. Artificial general intelligence is the type of adaptable intellect found in humans.  More commonly seen in the movies, AGI is mainly theoretical at this present time. Strong AI technologies are still in very early stages of development; valid examples of strong AI don’t currently exist.

Many of the current applications of AI are made possible through ‘machine learning’.

What is machine learning?

A subset or application of artificial intelligence, Machine learning is the application of AI which provides systems with the ability to learn and improve from experience without being given a specific set of instructions. Machine learning emphasises the development of computer programs which can access data, using it to learn for themselves.

The foundations of machine learning (ML) lie in statistics. The learning process starts with sample data, also known as “training data”.  Using learning algorithms and statistical models, machine learning looks for patterns in the data to produce a mathematical model, to make improved decisions in the future.

The aim is to allow computers to learn, unsupervised, and adjust their actions accordingly. For instance, ML applications can:

  • After reading a piece of text, determine if the author is making a complaint or a purchase
  • Find other tunes to match the mood after listening listen to a piece of music
  • Identify images and categorise them according to the elements they contain
  • Recognise faces, speech and objects with a high degree of accuracy
  • Translate significant volumes of text in real-time

Machine learning itself is reliant upon an inter-linked system of algorithms, referred to as neural networks.

What are neural networks and deep learning?

Neural networks are the key to the process of machine learning. Vaguely inspired by biological neural networks, neural networks are interconnected algorithms.  These algorithms, or neurons, “learn” to perform tasks by considering examples, generally without being explicitly programmed.

The algorithms that make up a neural network, feed data into one another.  They are trained to carry out specific activities and tasks by augmenting the importance attributed to the input data as it passes through the layers.

Deep learning is a subset of machine learning which makes use of Neural Networks.  Deep learning is where neural networks are expanded into multiple interconnected networks with a large number of layers, trained using large volumes of data. The ability of computers to carry out tasks such as speech recognition and computer vision have been enabled by development in deep neural networks.

How is artificial intelligence (AI) used in business?

Today AI is ubiquitous. AI is used to make online purchase recommendations, used by virtual assistants such as Google Assistant and Amazon’s Alexa to understand what you say, recognise people, place and objects in a photo, identify spam, or detect credit card fraud.

At least 30% of companies globally will use AI in at least one portion of their sales processes


In business, AI is already widely used in automation, data analytics, and natural language processing.  Automation reduces repetitive or even dangerous tasks. With data analytics, businesses gain insights never before possible. While natural language processing enables intelligent search engines, chatbots, and better accessibility for customers.

Globally, businesses today with the help of these three fields of AI, are leveraging AI technologies to optimise their operations, improve efficiencies and acquire an increase in profits.

Artificial intelligence and machine learning have become the latest tech buzzword everywhere.  Since the first piece of AI, the artificial neuron, developed in 1943 by William McCulloch and Walter Pitts, research in artificial intelligence has driven many technological advances, such as:

  • Autonomous driving
  • Chatbots and virtual agents
  • Facial recognition
  • Machine translation
  • Pattern recognition
  • Predictive analytics
  • Suggestive web searches
  • Targeted advertising
  • Voice and speech recognition

Many provide solutions to a significant number of business challenges and complex, real-world problems, and are now commonplace.

In the next several years, supply chain management is also poised to make significant AI-based advances. Providing companies with accurate and comprehensive insight to monitor and improve operations in real-time.

Other areas where significant AI-based advancements are expected to be seen include healthcare,  data transparency, and the security industries. For more AI use cases, see also Practical applications of artificial intelligence in business.

See also What is Internet of Things (IoT)? and discover the business benefits of digitalisation.

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