Generative AI vs. machine learning: How are they different?

Machine learning
Machine learning

Machine learning and AI are transforming how businesses operate: improving efficiency, streamlining workflows, maintaining security and compliance, and creating new opportunities for revenue and growth.

The numbers are impressive. According to industry research, the machine learning market is expected to reach a valuation of over $200 billion by 2029, while AI offerings are projected to be worth over $1 trillion by 2030.

As machine learning and AI advance, the emergence of generative AI offers new ways of processing and using complex data, but it also poses new challenges for businesses. Before embarking on any AI initiative, IT and business leaders should understand the fundamentals of machine learning and recent advances such as generative AI.

What is machine learning?

Machine learning is a field of software engineering that analyzes data to find patterns, then uses those patterns to assist humans in decision-making based on enormous volumes of similar new and existing data. In essence, machine learning algorithms look at past decisions or cause-and-effect patterns and then seek to predictively replicate those same decisions to assist users or businesses.