Artificial intelligence (AI) is a field of computer science that mimics the problem-solving and decision making capabilities of the human mind. AI has helped make significant advancements in areas such as disability inclusion, early cancer detection, weather forecasting, security and surveillance and others.

The role of AI in marketing and AI-based capabilities are ubiquitous in our daily lives. Think: Personalized movie recommendations on your favorite streaming service or product suggestions for your next delivery order.

Below are five main subfields that are critical to how AI works

Machine learning: Machine learning (ML) is a branch of AI that uses algorithms that can learn from data to classify or predict patterns in data. ML insights are used to make informed decisions in areas that impact growth such as marketing and business operations. ML can be supervised or unsupervised. Supervised learning needs training data mapped to a known outcome and is the most commonly used in market research, predictive modeling and text parsing.

Neural networks: Neural networks or artificial neural networks (ANNs) are learning algorithms that depend on training data to learn. They are a subset of ML and structured to mimic how the human brain digests information and makes connections between different data points. Neural networks can keep learning as they process more data, improving their accuracy over time. On the flip side, you can shut off their learning and have them perform from what they’ve already learned.

Deep learning: Deep learning is a subfield of ANNs and refers to any neural network with three or more neuron layers. Deep learning algorithms are more powerful than shallower neural networks because of their enhanced learning abilities in optimizing and refining results for accuracy. It enables several AI applications from smart assistants (Think: Siri and Alexa) to other areas such as healthcare, fraud detection and facial recognition technologies.

Natural language processing: Natural language processing (NLP) is a field of AI that focuses on enabling computers to process human language. NLP models can do things such as translate from one language to another, summarize or classify text, and even generate language. This enables businesses to use AI to process customer experience data, sentiment analysis and more. It is also what powers conversational AIs like ChatGPT.

Computer vision: Computer vision is a sub-field of AI that’s focused on getting computers to efficiently process images for a number of use cases. One class of algorithms that can be applied here are convolutional neural networks (CNNs), which standout from other neural networks for their superior performance with image, speech, or audio signal inputs. Recent uses of deep learning and convolutional neural networks (CNNs) have led to breakthroughs in computer vision, enabling computers to process millions of image data and even create new images. CNNs are used in many applications such as early cancer detection, surveillance, space exploration and developing visual effects for films.

Though we are seeing continuous advancements in AI, more research is needed to explore its full potential. As it becomes a more integral part of our lives, responsible AI that considers privacy, security, transparency, fairness of intellectual property, reliability and inclusion is critical.