Generative AI

Generative AI is the technology behind tools that write, summarize, translate, generate images, produce code, and answer questions in natural language. Unlike earlier AI systems that classified or predicted from structured data, generative AI creates new output—a draft, a response, an image—each time it's used. The same underlying capability powers a customer support chatbot, a coding assistant, a document summarizer, and a marketing copy tool. What they share is a model trained on large amounts of human-produced content, which it uses to generate plausible, contextually appropriate responses.

Generative AI is already inside the organization, whether it has been formally approved or not—in the tools employees download, the browser extensions they use, and the platforms vendors are embedding it into. The business case for productivity is real: faster drafts, better summaries, quicker research. But the risk is specific and easy to underestimate—generative AI produces confident, fluent output regardless of whether it's accurate, and employees without domain expertise may not catch the errors. Leaders who set clear rules about what tools are approved, what data can be shared, and what output requires human review before it's acted on are managing a real exposure. Leaders who don't are leaving that judgment to individuals.