Do organisations need an AI content policy?

AI content policies are starting to show up in more places, especially among publishers, broadcasters and other editorial-led organisations. With AI playing a much larger role in how a lot of content gets produced, these policies are no surprise.

The question I’m asking isn’t whether organisations are using AI in content creation. Most already are, in some form. Even when AI hasn’t actually written a word of the final output, it’s often heavily relied on for the earlier stages – research, note-taking, summarising, repurposing, translation, sense-checking or structuring a rough first draft. For example, Canto’s recent survey suggests the most useful role for AI is often operational rather than creative. Marketers said it was particularly helpful for streamlining reviews and approvals, content reuse and repurposing, compliance and brand checks, and predicting asset performance.

The more interesting question is: should organisations be open about it?

I think they should.

Not because Google demands it (although it likes transparency), as I’ll explore later. Not because every piece needs a disclaimer bolted onto the end. And not because using AI is inherently bad. It isn’t.

Organisations that produce masses of genuine content should consider developing an AI content policy because transparency is becoming more of an expectation. For YMYL organisations in particular (broadly speaking, those who operate within the healthcare or financial sectors), that kind of openness is part of trustworthiness.

And in a landscape that’s already saturated with generic, low-quality, “content mill” writing, that matters.

What the strongest AI content policies have in common

Fundamentally, the strongest AI content policy examples don’t treat AI as good or bad. They state where it helps, where human judgement still needs to lead, and when disclosure becomes appropriate.

The best policies are actually pretty aligned.

Once you read a few of these policies, the wording changes but the principles are similar.

First off, ProCopywriters provides what I think is the most useful benchmark for agencies and commercial writers. Its guidance (rather than an outright AI content policy itself) says AI use should be disclosed when it forms a substantial part of the process or output, rather than every light-touch use being flagged automatically. Its advice is clear: “if in doubt, disclose.”

It recognises that using AI to help with ideation or editing is not the same thing as delivering largely AI-generated copy. It also keeps the focus where it should be, on trust, context and the relationship with the reader or client.

The Guardian takes a similar line from a newsroom perspective. It allows AI use within clear editorial rules, staff training and human oversight, and says significant use of generative AI in journalism will be disclosed.

The BBC goes further on transparency, saying that if AI is used in the creation, presentation or distribution of content, audiences should be told in a way that suits the context. Their use of AI must “never undermine the trust of audiences.”

CNET was one of the earlier publishers to set out an AI content policy, taking a stricter approach. It explicitly says it “does not use generative AI to write content” and that their words “are human-written”, although AI can still support prep work such as transcription and note-taking.

Where else AI is actually helping content teams

The role of AI in content production is often simplified to just writing the content itself. But in reality, that’s not where its value sits for content teams and marketers.

Among marketers in the UK and US, Canto found the biggest content challenges in late 2025 were keeping up with growing content demands, managing a rising volume of content amplified by generative AI, and finding or implementing the right technology.

And when marketers were asked what AI was actually most helpful for, the top answers were streamlining reviews and approvals, smart search to find assets quickly, and content reuse recommendations.

As well as content writing, AI can be genuinely helpful for:

• Research support
• Note-taking and summarising
• Content repurposing
• Translation (to an extent!)
• Structure and synthesis
• Workflow efficiency
• Approvals and sense-checking

None of that means it should replace original thinking. It just means it can be useful inside the process.

Does Google (or LLMs) care about AI content policies?

The big question here is if you disclose AI use, will Google reward you for it? Not directly, but it helps.

Google’s guidance states that AI-generated content isn’t inherently bad, and nowhere does it say that a website needs an AI disclosure policy. Instead, its focus is on whether content is helpful, reliable, people-first and created to benefit users rather than manipulate rankings.

Where disclosure becomes relevant is in Google’s thoughts on “Who, How, and Why”. Google’s systems reward content where:

It’s clear who wrote the content – there is an author with a clear bio

Content has been written to genuinely help people and not game the system – the why

You reference how it was written where it’s helpful to share this information – this is where the AI disclosure part comes in

On the last point specifically, Google says:

“Overall, AI or automation disclosures are useful for content where someone might think ‘How was this created?’ Consider adding these when it would be reasonably expected.”

So while an AI policy isn’t going to transform rankings of content on its own, it can still support a more people-first, trustworthy approach to content, which is clearly what Google wants to see and reward.

Should organisations have an AI content policy?

If AI plays a meaningful role in your content creation process, especially across a large content output, I think organisations should have an AI content policy that is publicly available and easy to understand.

An AI content policy helps set expectations, and provides much needed transparency, which is useful externally, and it is useful internally too.

For larger organisations, it’s especially useful because it shows that AI use is considered rather than hidden.

What a good AI content policy should cover

A useful policy doesn’t need to be long, but it should be clear.

Where AI can be used Be specific. Research, ideation, summarising, repurposing, translation, workflow support and editing are not the same thing as creating AI-generated final copy.

What stays human-led This should include strategy, subject-matter judgement, fact-checking, editing, sign-off and accountability.

When AI use should be disclosed If AI forms a substantial part of the process or output, disclose it.

What standard the final content must still meet AI support should not lower the bar for accuracy, originality, clarity or usefulness.

Who is responsible Someone still has to own the final output – that should be clear.

To wrap up, it all comes down to trust. AI can absolutely support content creation, and for many teams it already does. But if it is playing a meaningful role in the process, organisations should be clear about that. Not because they have to, but because transparency is a huge part of what makes content feel credible in the first place. And transparency is only becoming more important as AI shapes how content is found, interpreted and surfaced.

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