What is generative AI?

Generative AI refers to AI systems that independently create new content — text, images, code, music, or video — based on training data and a user prompt.

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DEFINITION

Generative AI is the category of AI systems now ubiquitous in everyday work. ChatGPT writes text, Midjourney generates images, GitHub Copilot suggests code. All of these are generative AI systems. The difference from classical AI: classical systems recognise or classify something; generative systems create something new. The model has learned from millions of examples what good text, images, or code look like, and produces a new output based on the input — not copied one-to-one, but newly composed. Generative AI fundamentally changes the relationship between humans and computers: control runs through descriptions instead of clicking. The result demands human judgement and refinement. The craft shifts from execution to discernment.

CONNECTIONS

Leadership

Generative AI fundamentally changes leadership tasks: reports, presentations, and analyses are produced faster. Transformational leadership is needed to guide teams through this shift and integrate AI use meaningfully into work processes.

Agility

Generative AI accelerates agile ways of working: retros can deliver deeper insights through AI-supported analysis, backlog items are created faster, and user stories are refined automatically.

Project Management

In projects, generative AI can create routine documents such as status reports and checklists. Stakeholder updates become faster and more consistent when AI delivers the first drafts.

KEY POINTS

  • Generative AI creates new content: text, image, code, audio, video.
  • It differs from classical AI, which recognises rather than creates.
  • Best-known examples: ChatGPT, Claude, Midjourney, Stable Diffusion.
  • The input (prompt) directly steers the output.
  • Generated content must be judged and refined by humans.

EXAMPLE

A communications team uses generative AI for four tasks at once: an LLM drafts press releases, an image model visualises campaign concepts, a code assistant builds the landing page, and an audio model generates a podcast jingle. What used to take weeks now takes days. Creative direction judges, selects, and refines — instead of producing everything from scratch.

MISCONCEPTIONS

Is generative AI the same as artificial intelligence in general?

No. AI is the umbrella term. Generative AI is a subfield that produces content. Other AI systems classify, recommend, or optimise without generating anything.

Can I trust generative AI outputs blindly?

No. Generative models produce plausible-sounding results that can be wrong, biased, or incomplete. Checking with your own judgement is always necessary.

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