AI is multiple technologies combined to sense, think, and act as well as to learn from experience and adapt over time. Sense refers to pattern recognition, machine perception, biometrics, speech recognition, computer vision, and affective computing. Think refers to natural language processing, advanced analytics, knowledge representation and reasoning, machine learning, deep learning, conversational interfaces, and cognitive computing. Act refers to search, question answering, recommender systems, expert systems, planning and scheduling, robotic process automation, chatbots, virtual assistants, robots, autonomic computing, and autonomous systems.

The mission of knowledge science is transformation. Humans encode thoughts, represent knowledge, and share meanings using patterns and language. Knowledge representation is the application of theory, values, logic, and ontology to the task of constructing computable patterns in some domain. The computational theory of knowledge predicts that ultimate economies and efficiencies can be achieved through variable-length, n-ary concept coding and pattern reasoning resulting in designs that are linear and proportional to knowledge measure.

AI for human communication is about recognition, parsing, understanding, and generating natural language. The concept of natural language is evolving. Natural language processing (NLP) is the confluence of artificial intelligence (AI) and linguistics. A key focus is the analysis, interpretation, and generation of verbal and written language. Other language focus areas include haptic, sonic, and visual language, data, and interaction.

Enterprise AI transforms business, impacts performance, and increases efficiencies in multiple ways: (1) Insight generation—using big data and cognitive analytics to extract previously unknown understanding from structured and unstructured data. (2) Customer engagement—using AI, information, analytics, and communications technology to involve someone’s interest, attention, interaction, and participation towards some end. (3) 
Business acceleration—augmenting staff and automating knowledge generation to drive cost savings, competitive advantage, and new business lines through smarter deployment of resources; and (4) 
Enterprise transformation—change associated with the application of digital technologies and artificial intelligence to all aspects of the business, its ecosystem, and human society.