Marketing teams are being asked to produce more content than ever. Budgets and headcount haven’t grown with the workload. AI search has added a whole new surface that needs its own content, optimization, and measurement.
It’s easy to see why content creation platforms have become attractive. You pay a monthly fee, plug the platform into your content process, and increase output without adding people. On paper, that can look like an easy win.
We use these tools at Firebrand, and yes, you can outsource a good amount of it. What you can’t outsource is the judgment that decides what to produce, where it fits on your site, and how it connects to everything else you’re doing. This post covers how to run the platform and the expertise together.
What platforms actually do
AirOps is one of the better-known names in a category usually described as AI content engineering or content workflow automation. In practice, it’s a workflow builder for content. You connect it to your keyword data, your brand guidelines, and your CMS, then build repeatable workflows that research a topic, generate a brief, draft the page, and publish it. Teams use it for keyword cluster briefs, competitor comparison pages, programmatic landing pages, blog drafts, and bulk refreshes of existing content.
We’ve used AirOps and know the platform and its feature set well. It’s good at what it’s built for, and the work it takes on is real work. It’s also the most repeatable part of the job. If your team currently spends its week templating briefs and rewriting metadata at volume, a platform like this gives you that week back.
The harder question is what the output does for your brand once it’s live, and whether it was the right output in the first place. Ahrefs found that 74.2% of newly created web pages now contain AI-generated content. Your competitors have the same tools and the same speed you do. Publishing more than the competition stopped being a strategy some time ago, and search engines have gotten noticeably better at telling the difference between more and better.
You bought the race car. Who’s driving it?
Think of a platform like this as the car rather than the driver. It’s a fast machine, and how well it performs comes down almost entirely to who’s behind the wheel.
SE Ranking ran a 16-month experiment, published on Search Engine Land, publishing 2,000 AI-generated articles across 20 new domains with no human editing. Indexing was never the problem. Roughly 71% of the pages were indexed within about five weeks. The problem was maintaining a good position in SERP rankings as presence in the top 100 fell from 28% to 3%.
Those pages didn’t fail because the content was spammy. They failed because there was no real strategy behind the content, and it lacked the optimization nuance that only a seasoned SEO knows how to execute, like building topical hierarchy and internal links.
These platforms amplify whatever strategy (or lack thereof) you build for them. A thin strategy produces bad content faster.
What the driver actually does
Experienced marketers decide the key elements for each content piece, starting with length and format. Does this query warrant a 600-word direct answer, a comparison table, a step-by-step, or a 3,000-word reference page? That call comes from looking at the pages currently winning the query and working out what they have in common.
Internal linking is another strategic call. AI-automated content creation tools typically only guess at what internal links to use in support of your content cluster strategy. Someone who has done the legwork knows which existing pages a new piece should point to, and what keywords to actually hyperlink instead of just “click here,” so crawlers and AI bots get a clearer signal about what the page covers.
Then there’s how new content fits into the site you already have, which is where the expensive mistakes tend to happen. A platform generating 80 cluster pages has no idea what your product pages already rank for. When those cluster pages start competing with your product pages you, have a new cannibalization problem.
Finally, there’s what’s happening off your site, which most content workflows don’t account for at all. Muck Rack’s Generative Pulse study analyzed more than 25 million links cited by ChatGPT, Claude and Gemini across 17 industries. Earned media accounted for 84% of citations. Paid and advertorial content accounted for 0.3%. They’ve run the study three times since July 2025 and the number has stayed between 82% and 89%.
If AI models are mostly citing what other people publish about you, a workflow that only produces pages on your own domain is working on a fraction of the problem. Someone has to connect the content program to the PR program, and both of those to what paid media is doing.
The job the license fee doesn’t cover
The business case for these platforms usually leaves out one line item: somebody has to run it. Configuring the workflows, writing the inputs that feed them, reviewing what comes back, and revising when the output drifts off-brand adds up to a job in itself. It isn’t a one-time setup either. Every month someone has to decide what the platform should produce next, and why.
The 2026 Marketing Leaders Reality Index, a survey of more than 300 marketing leaders published by AirOps, puts some numbers on how often that role goes unfilled. Only 15.5% of teams have expanded their own AI capacity, while nearly half (47.7%) have cut agency or vendor spend. The work didn’t disappear when the spend did. It landed on a senior marketer who was already at capacity, which is how “we’ll bring it in-house” turns into “we brought it in-house and now this is my job instead of strategy.”
Running AI tools and human strategy together
If you’re considering an AI-powered content engineering platform like this, bring it in for what it’s genuinely good at, which is scaling content through better workflows.
For content development, there’s no universal split between what a person should write and what a workflow can handle. What makes sense depends on the maturity of your team, the depth of your category, and who currently owns strategy. The question worth asking of any given piece is whether removing an experienced human from it would noticeably reduce its quality, credibility or strategic value. Where the answer is yes, keep a person on it. Where a well-configured workflow gets you something genuinely good, run the workflow.
In that same survey, teams that increased their budget, headcount and revenue goals together were three times more likely to be expanding their AI capacity than everyone else. They invested in the tool and in the expertise to run it, rather than trading one for the other.
What doesn’t change is that someone has to write the briefs, review what comes back, and run the measurement loop that decides what gets built next. That’s the driver’s seat, and the teams getting real value out of these platforms have someone experienced sitting in it.
FAQs about AI content tools
Can an AI content platform replace an SEO team?
No, an AI content platform can’t replace an SEO/GEO team on its own. The platforms are built to produce content, and producing it is only part of the job. Someone still has to decide what’s worth publishing, how it fits into the existing site content, what links to what, and how any of it connects to the coverage you’re earning elsewhere.
Does Google penalize AI-generated content?
Google doesn’t necessarily penalize content for being AI-generated, because it evaluates the content itself rather than how it was produced. The performance data isn’t flattering, though. Semrush analyzed 42,000 blog posts across 20,000 keywords and found purely AI-generated content took the top spot 9% of the time, against 80% for human-written content. Scaled content abuse, meaning mass-producing pages mainly to rank, is a named spam policy, and Google ran three spam updates in 2026 alone. It confirmed those policies also cover attempts to game AI Overviews and AI Mode.
Is an AI content creation platform cheaper than an agency or an in-house SEO?
When it comes down to costs involved, it depends what you count. The license is the visible part, but underneath it are credits, the hours someone spends configuring workflows and writing inputs, and the QA time. Most of that lands on people already on payroll, so it never shows up as a line item and never gets compared against what it replaced. Be sure to price the whole thing, not the subscription.
What does an experienced SEO/GEO do that a content tool can't?
They help decide what’s worth creating and publishing in the first place and how to amplify that to get the most value for the brand and pipeline. That means knowing whether a query wants a short direct answer or a deep reference page, how a new page fits the site you already have without competing with it, what should link to what, and whether the whole thing connects to the coverage you’re earning elsewhere.
Do AI content tools help with GEO and AI search visibility?
Yes, they can make your own pages easier for models to parse and pull from, which is real and worth having. But Muck Rack found 84% of AI citations come from earned media, not brand sites. Most of what gets cited about you lives somewhere you don’t control, and a publishing tool can’t reach it.
How do I know whether my AI content program is working?
You can take a look at the results after the first month to get a sense of program success. Getting indexed is the easy part. What matters is whether those pages are still holding or increasing position at 60, 90 and 180 days, whether models are citing you, and whether the traffic arriving is engaging and converting.
What content is AI best at producing?
AI is best at producing any type of content that is repeatable and where the format is already settled. This can include: bulk metadata refreshes, first-draft briefs from a keyword cluster, comparison pages built off a template, updates to posts you published two years ago. The common thread is that you already know what good looks like and you just need more of it. Content that has to make an argument, carry a point of view, or land a technical claim with a skeptical reader still needs a real person on it.
We already pay for an AI content platform. Does an agency still make sense?
Yes, and you shouldn’t have to choose. Experienced people can make these tools much more productive without sacrificing quality. Bring in people to decide what it produces, make sure it fits the site, check what comes out, and connect it to whatever PR and paid are doing. Most of the teams getting real value out of these tools are running both, and the tool works better for it.
If you want a read on where your brand currently stands in AI search, or help building the strategy layer around the tools you’ve already bought, contact our team.
About the Author
Shane Jordan is a San Francisco-based digital marketing pro with a passion for driving brand growth. At Firebrand, Shane focuses on client growth strategies including SEO & Generative Engine Optimization (GEO), PPC, organic & paid social media, Influencer marketing and performance analytics. He writes practical guides on digital marketing topics including SEO Best Practices, PPC Landing Pages, Multiplier Marketing, and Measuring AI Web Traffic.
With a seasoned background and a passion for emerging tech, Shane helps brands navigate the future of marketing. Outside of work, he enjoys coastal hikes with his family and piloting small aircraft.
Follow Shane on LinkedIn or explore more on Firebrand’s startup marketing agency blog.
