On the list of words that would get you most excited about the year ahead, ‘governance’ is not likely to be anywhere near the top. But it is a conversation that everyone involved in content creation needs to have in 2026. AI is allowing businesses to ramp up content production, cutting the time between having an idea and publishing it. But that introduces new risks too.
As someone who has stared at many blank pages wondering where to start, I find the speed of AI content generation mind-blowing. But the thrill of how fast you can fill a page is also the reason why content governance is more important than ever.
As volume and speed increase, so do the risks. Factual inaccuracies, tone of voice drift and contradictory messaging between teams are more likely if you are rushing to get content out the door without proper oversight in place.
Without the right safeguards, publishing content that varies in quality or tone can undermine brand credibility, confuse audiences and create new bottlenecks. Content governance is how to make sure that every piece of content you create is consistent, accurate and reflective of your brand.
Understanding the risks of AI-generated content
We hosted a webinar in 2025 on how to put the right processes in place to get the best out of AI without impacting brand image or engagement. During the session, we polled attendees on the risks they were most concerned about when scaling content with AI.
The results reflected three interconnected challenges:
1. Inconsistency
60% of attendees said their top concern about increasing their AI use was generic results and off-brand tone. We have all seen how AI can continually provide different responses to the same prompt. This is the result of the probabilistic nature of AI generation, but can also be impacted by subtle differences in prompting across teams or changes to model performance made by providers. Content governance helps you account for this and avoid one output feeling polished and professional, while the next feels overly casual.
Let’s take the example of a global SaaS provider that is generating different, sector-specific landing pages. The process begins with a prompt designed by the brand team that specifies the tone should be confident, pragmatic and with no unnecessary hype or inflated claims. At first, the pages sound consistent and match the brand’s style. But over time, different teams tweak the prompts to make the content ‘punchier’ or ‘more persuasive’. These pages are stored as good examples by these teams and AI starts copying their tone when used to update the pages or add other content to the website. After a few months, the same products are described in noticeably different tones across sectors and regions, creating brand inconsistency.
2. Accuracy
We all know that AI can produce compelling but incorrect claims – and 37% of our webinar attendees reported that accuracy of outputs was their main AI-related concern. When content volume increases without proper governance, so does the likelihood of factual errors, outdated information or fabricated details.
This is potentially a huge issue for brands that rely on authority and expertise. For example, a cybersecurity firm decides to use AI to accelerate blog production. A post is published with incorrect information about when a major new compliance regulation is coming into effect. The mistake seriously undermines the brands credibility and is live on the site for a week before being corrected after a potential client mentions it to a member of the sales team.
3. Contradictory messaging
If different teams are using AI independently without any central oversight or guidelines, it is likely that shifts in narrative and messaging will creep in. Sales, marketing and product teams all have different priorities, levels of technical expertise and ways of interacting with customers. As a result, they often think and talk about products and services in distinct ways. With AI reflecting different teams’ priorities right back at them, key messaging risks becoming diluted across channels
This can have real impacts on the customer journey. Put yourself in the shoes of a customer looking at a B2B payments platform. The marketing content says the platform automates 100% of reconciliation – which sounds like exactly what you need. But when you get sent a sales deck ahead of your first meeting, it says that automation covers up to 70% of reconciliation tasks. Meanwhile, the product documentation states that automation applies only to specific transaction types. Using AI to generate these materials may have saved time. But it just lost you a potential customer.
Building strong foundations for AI-assisted content generation
Whether you are a fan or not, AI has muscled its way into the content creation process in a really short amount of time. It’s no wonder then that we are collectively still figuring out how to adapt. Good content governance is not about slowing down or suppressing AI adoption. When done right, it gives your teams a solid framework and set of guardrails that make sure that every piece of content, whether human-written, AI-assisted or machine-generated, meets your standards.
If you haven’t thought about content governance in 2026, you definitely need to. Here are some key things to consider.
1. People need to feel confident about using AI
AI is only as effective as the people prompting it. Training your teams on how to use generative tools effectively, safely and strategically is the best way to improve output quality and reduce risk. Our recent blog on quality assurance in the world of AI outlines how to ensure quality – from brand-aligned prompts and meticulous fact-checking to screening rigorously for unconscious bias and adding the human touch back in.
2. You need to clearly set out what good and bad look like
Scaling content effectively means having the fundamentals in place from the start. At a bare minimum you need a content strategy that clearly sets out your objectives, key messaging and target audiences. Not only does this get everyone on the same page – it also serves as an important base layer of context for AI use across the business.
There are other core resources that help keep content consistent and on-brand. Content pillars establish the themes and topics you want to own while a tone of voice document guides how your brand should sound across every format. With the foundations set, you can use brand and messaging frameworks to set non-negotiable guardrails. Depending on your sector, you may also want to add any compliance-related specifics to the list too.
3. Your review and approval process needs to be rock solid
Everyone needs to know exactly who is responsible for what. A strong governance process defines clear review stages, approval roles, quality standards and fact-checking requirements. This means that every piece of content, no matter how big or small, gets the scrutiny it needs.
Less slop and more value
AI gives you the power to scale content faster than ever. But you need content governance to turn that speed into a competitive advantage. Without the right guardrails, AI amplifies risks. With the right processes and oversight in place, it can amplify innovation and impact. Content winners in 2026 won’t be those producing the most content, but those producing the right content, consistently, at scale.
If you need support building the right content governance model for you, we can help.
