Skills
what you know and need to learn to work with ai
Working with AI asks for a mix of old and new skills: judgment about sources, plus a feel for how to prompt, check, and edit machine output. This card helps a team name what they already know and what they would need to learn. It treats skills as something to build, not something you either have or lack.
Questions to explore
- Which existing journalistic skills matter more, not less, when AI is in the mix?
- What can each person on your team already do with these tools, and what feels out of reach?
- How would someone on your team learn to spot a flawed AI output?
- Who could teach these skills internally, and who would you need to bring in?
- What is the cost of not building these skills over the next year?
Expert voices
“Every journalist should understand AI basics, regardless of whether they use it directly. Build baseline literacy across the whole organization.”
“A two-tier newsroom is a problem. Bridge the data skills gap so everyone, not just specialists, can understand AI data insights.”
“Younger professionals risk never developing core skills because the tasks they used to learn from now go to AI. That deskilling raises a hard question: where will future journalists come from?”
“As AI takes over routine tasks, early-career journalists lose the repetition through which fundamentals are learned. Those skills disappear, with long-term consequences for the profession.”
Things to consider
- Core reporting skills like verification become more valuable, not less.
- People learn these tools faster with real tasks than with abstract training.
- Map skills across the team so knowledge is not stuck with one person.
Pull Skills when it is relevant and set it aside when it is not. Pair it with the other AI Conversations cards, lay them out on a table, and use the questions above to get everyone on the same page. Capture what you discuss on sticky notes or in a shared doc.
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