Computer vision: Computer vision is the field of AI that lets software interpret images and video: recognizing objects, reading text, detecting defects, tracking movement, or describing a scene. It powers everything from phone photo search to warehouse inspection cameras.
A computer sees an image as a grid of numbers. Computer vision models, usually deep neural networks trained on millions of labeled images, learn to turn those numbers into meaning: this is a forklift, that is a barcode, this weld has a crack, this receipt total reads $84.12.
Common workplace forms include optical character recognition (OCR) for scanned documents, object detection for inventory and safety monitoring, quality inspection on production lines, and image classification in insurance claims. Today's multimodal assistants fold general-purpose vision into chat, so you can upload a photo and ask questions about it.
Vision systems fail in predictable ways: unusual lighting, angles, or items they were not trained on. They can also raise privacy questions when pointed at people. If a system will make decisions about employees or customers from camera data, involve legal and HR before deployment.
Example at work
A regional distributor installs cameras at the receiving dock. A computer vision model reads carrier labels, counts pallets, and flags visibly damaged cartons as they come off the truck, creating a timestamped photo record. Disputes with carriers now start with evidence instead of memory.
Why it matters
Any process that currently depends on someone looking at something, whether counting, checking, reading, or matching, is a candidate for computer vision. Knowing the term helps you spot those opportunities and ask vendors the right questions about accuracy and failure modes.
Related terms
- Multimodal AIMultimodal AI is a model or system that can understand and produce more than one type of content, such as text, images, audio, and video. Modern assistants that can read a screenshot, describe a chart, or listen to speech are multimodal.
- Optical character recognition (OCR)Optical character recognition (OCR) is technology that converts text in images, scans, and PDFs into machine-readable, searchable, editable text. Modern AI models extend it to read messy layouts, tables, forms, and handwriting.
- Deep learningDeep learning is machine learning that uses neural networks with many layers, which lets a model learn complex patterns directly from raw data such as text, images, or audio. It is the technique behind today's language models and image generators.
- Machine learning (ML)Machine learning is the branch of AI in which software learns patterns from examples instead of following rules a programmer wrote by hand. Nearly every modern AI tool, including chat assistants, is built on it.
- Neural networkA neural network is a computing system made of layers of simple connected units that pass numbers to each other, with connection strengths (weights) adjusted during training until the network produces useful output. It is the building block of modern AI.