McKinsey's generative AI explainer is the business-language version worth sharing with colleagues who ask what the fuss is about

Most technical AI explainers lose business audiences in the first paragraph. McKinsey's generative AI piece https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-generative-ai is specifically written to translate AI concepts into practical business language and it is the version I share when the question is coming from someone who cares about outcomes rather than architecture.

The distinction it draws between generative AI and earlier AI forms, which were primarily about classifying or predicting from existing data, is the conceptual anchor that makes the productivity and content generation applications legible without requiring technical background.

The enterprise adoption and organisational change framing is where the article is most useful for business audiences. Not just what generative AI can produce, but what changes when organisations actually integrate it into their operations: decision-making speed, content production economics, knowledge worker productivity and the new skills required.

This is a good post to link when someone in the forum is trying to explain to a sceptical manager or board why AI adoption matters and why the timing matters.

Where has generative AI created the most measurable change in your own work or your organisation and how would you describe that change to someone who has not yet experienced it?