AI refers to the simulation of human intelligence by computer systems, enabling organizations to enhance efficiency, profitability, and revenue. By leveraging data, AI helps unlock insights that drive automation and improve decision-making across various industries.

AI implementation occurs in two main phases: training and inferencing. Training involves data scientists developing and optimizing models using curated datasets, while inferencing applies these trained models to new data to derive insights and automate processes.

Businesses should first define their desired outcomes and assess whether they have a clear business case for AI. They must decide between building in-house capabilities or purchasing commercial solutions, and consider their budget and infrastructure needs. Understanding data sources and types is also crucial for successful AI implementation.