AI is no longer a future concept; it is already embedded in content creation and publishing.

For many news organisations, the challenge is not whether to use AI but how to define its role. Should it handle routine tasks, support research, or help repurpose existing stories? And just as importantly, where should it not be applied?

The central question is how to put AI to work responsibly so it strengthens efficiency without undermining credibility.

Define AI’s boundaries

Deciding where AI belongs is the first step toward responsible adoption. Tasks such as generating headline variations, drafting meta descriptions, or condensing long-form copy are natural fits. These applications improve efficiency without putting credibility at risk.

But there are also clear areas where AI does not belong, such as investigative reporting, crisis communications, executive bylines, and sensitive topics. These require human judgment, accountability, and nuance that AI cannot replicate.

Establishing boundaries around where AI should and should not be used prevents misuse and provides clarity across teams.

Train AI to reflect your voice

Generic output is one of the fastest ways to undermine reader trust. AI will only reflect your standards if it is actively trained to do so. Developing a style guide that outlines tone, preferred vocabulary, and examples of high-performing stories gives AI a stronger foundation.

Prompt templates can also help. By embedding cues about audience and tone, organisations can generate drafts that feel more consistent with their editorial identity.

Even with these resources, human review remains essential to ensure content sounds authentic and aligns with established brand standards.

Keep human review at the centre

AI can generate copy quickly, but only editors can ensure it is accurate, credible, and trustworthy. Every AI-assisted draft should undergo a review process checking for factual accuracy, editorial voice, and perspective.

A simple set of questions is useful: Does the piece read naturally? Does it reflect the publication’s point of view? Are the facts correct and properly attributed? If not, the work is not ready for publication. This review step prevents overdependence on AI and reinforces human responsibility for the final output.

Track and measure AI use

Once AI becomes part of the workflow, it’s important to track how and where it is being used. Documenting its role creates accountability and makes the process more transparent. Comparing the performance of AI-assisted content with human-only work can also show whether the technology is improving efficiency or adding extra steps in editing.

This kind of evaluation serves two goals: identifying where AI is providing real value and ensuring it does not creep into areas of the process where human judgment is essential.

Support journalists, don’t replace them

AI should support stronger journalism, not replace it. Training programmes give staff the opportunity to experiment safely, share effective practices, and build confidence with the tools. When positioned correctly, AI reduces repetitive tasks and frees journalists to focus on analysis, creativity, and deeper storytelling.

The most effective approach is to treat AI as a capable assistant: helpful and efficient, but ultimately secondary to human perspective and editorial judgment.

Build governance that adapts

AI is evolving rapidly, and editorial policies must keep pace. Governance frameworks should define where AI is appropriate, how it is reviewed, and who is accountable for oversight. Consider appointing an AI steward to lead quarterly reviews of risks, performance, and ethical standards.

Since what feels acceptable today may not be tomorrow, governance must remain flexible. Regular reviews ensure policies remain relevant and keep the use of AI aligned with industry standards and audience expectations.

Putting AI in its place

Finding AI’s place in the editorial process is not a one-time decision. It requires clear boundaries, consistent oversight, and adaptability. Used wisely, AI can streamline workflows, support processes, and introduce new efficiencies — but only when its role is carefully defined and kept in balance with human judgment and creativity.

The news organisations that succeed will be those that put AI to work responsibly by accelerating production while preserving credibility and supplementing journalists rather than substituting for them. AI belongs in the editorial process when it strengthens quality and trust — not when it replaces them.

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