AI blog tools: $5.27 an article, 9 stats with no outside source

Search for an AI blog tool and you get a shelf of subscriptions that promise a finished post. The interesting question isn’t whether they write clean sentences, because they do. It’s what an editor takes out afterwards, and how much that costs you. So we did the two things we could actually verify as of 21 August 2026: we priced four of these products from their own pricing pages, and we ran our house style checks over one blog post published by each vendor.

The prose passed. The sourcing didn’t. Across the four posts we counted nine numbered claims, five of which carry a link, and every one of those five points at either the vendor’s own site or another AI writing platform’s blog. Not one leads to the research the number came from. That’s the gap you’re paying an editor to close, and no subscription tier we found closes it for you.

What an editor cuts, and it isn’t the grammar

Our own editorial policy puts sourcing first: a claim rests on a primary document, or it doesn’t run. Every other rule sits below that. The result is a checklist you can run as code, which is what we did here. It counts words, average sentence length, contractions, em and en dashes, a list of house-banned filler words, and outbound links that sit inside body paragraphs rather than in the navigation.

The reason that checklist matters for AI drafts is narrower than the usual complaint about robotic writing. Style is the easy part to fix and the cheap part to automate. What a machine can’t do is tell you whether the 74% it just typed came from a survey of 200 people or from nowhere. Sourcing is the expensive part, which means it’s the part that determines whether a subscription saves you money.

What four AI blog tools cost, and what one post costs inside them

Prices below come from each vendor’s public pricing page, read on 21 August 2026. Only two of the four state an article allowance at all, so only two produce a cost per post. The per-article figures are our arithmetic, not the vendors’.

Tool, entry plan	Price	What the plan states	Cost per article
Copy.ai, Chat	$29/mo billed monthly, $24/mo billed $288/yr	5 seats, unlimited words in chat	not stated
Surfer, Discovery	$49/mo, billed yearly	120 documents, 10 tracked pages	$0.41, if the 120 is monthly
Jasper, Pro	$69/mo per seat	1 seat, 2 brand voices, 5 knowledge assets	not stated
Writesonic, Starter	$79/mo, billed annually	15 AI articles per month, 1 user, 1 project	$5.27

Writesonic is the only one that prices an article outright: $79 a month for 15 AI articles works out at $5.27 each. Surfer’s Discovery plan lists 120 documents next to a monthly price, but the page doesn’t say whether that allowance refreshes monthly or annually, so the $0.41 above carries an assumption we couldn’t confirm. Jasper’s Pro plan states a seat count and a brand-voice count and no word cap at all. Copy.ai’s Chat tier says unlimited words, which sounds generous until you notice the next self-serve step up is $1,000 a month for 75 seats.

That jump is worth sitting with, because it tells you what the product is really selling. Copy.ai’s ladder goes $29, then $1,000, and the thing you buy on the way up is workflow credits, not words. The same shape shows up at Surfer, where Enterprise is $999 a month, and at Writesonic, whose Starter tier bundles brand tracking across ChatGPT, Gemini and Google AI Overviews alongside the article allowance. None of these is a writing tool in the narrow sense any more. They’re marketing platforms with a writer attached, and the pricing reflects that. If you’re comparing free entry points across the wider category, we broke those down in what each free tier really costs you.

We ran our own checks over a post from each vendor

Here’s the method, and its limit. We fetched one blog post from each of the four vendors, pulled the body paragraphs out of the HTML, and ran the same numeric checks we run on our own drafts. We did not run the products themselves, and we can’t prove which sentences on a vendor’s blog came out of its own tool. What we can say is that this is the prose these four companies choose to publish under their own names, on the subject they sell.

Post	Body words	Avg sentence	Contractions per 1k	Em or en dashes	Outside domains linked in body
Jasper, “AI Content Creation”, updated 23 June 2026	1,354	18.1	8.9	0	3
Copy.ai, “AI for Thought Leadership”, 17 July 2025	1,531	15.6	8.5	13	2
Writesonic, “On-Page GEO”, updated 18 Feb 2026	1,212	14.8	33.0	6	1
Surfer, “Why Surfer Should Be in Your SEO Toolkit”, 19 May 2025	1,376	15.5	16.7	3	0

On style, all four clear the bar comfortably. Average sentence length runs from 14.8 to 18.1 words against our ceiling of 23. Contraction density runs from 8.5 to 33.0 per thousand against our floor of 4, so none of them reads as stiff. Writesonic’s 33.0 is the chattiest text in the set by a wide margin.

Three of the four fail our dash rule, and that one is a house rule rather than a universal fault. We ban em and en dashes because they’re the single most reliable tell of an unedited machine draft in our experience, and because a comma or a full stop does the same job. Copy.ai’s post carries 13 of them in 1,531 words. Jasper’s carries none, which is the strongest style result in the table. If you want the wider argument about what tells actually survive, we covered it in why most AI text detectors fail.

Nine numbers, five links, and not one of them leaves the industry

Now the part an editor would actually stop on. We counted every numbered factual claim in the body paragraphs, excluding prices, plan limits, product specs and calls to action. Nine survived that filter. Jasper’s post contributed none of them, because it makes no statistical claims at all, which is a defensible way to write and worth naming.

Copy.ai’s post supplies three. Two of them run naked: “Recent research reveals that 74% of organizations have seen investments in generative AI and automation meet or exceed expectations,” and “Additionally, 78% of businesses now use AI in at least one function.” Neither sentence carries a link, and “recent research” names nobody. The third does carry a link, and this is the one that gives the game away.

Deals influenced by thought leadership content close 41% faster and generate 23% higher value (source).

Copy.ai, “AI for Thought Leadership”. The word “source” is the link text

That anchor points at a blog post on quickcreator.io, which is itself an AI content generator selling AI content. It gets worse when you click. We requested that URL on 21 August 2026 and the server returned 410, the code for a page its owner has intentionally removed. A reader chasing the 41% lands on a second marketing site, then on nothing. That’s a citation chain that never touches ground, and it’s the failure we wrote about in using AI for research without fake citations.

Writesonic contributes one, and it’s an unusual case. The post offers a model sentence to imitate, labelled “Strong”: “Content marketing generates three times more leads than traditional outbound marketing while costing 62% less.” A guide teaching you to make authoritative statements demonstrates the technique with an uncited statistic. Writesonic does better elsewhere, though, because its only outbound domain supports a named human: David Sonn, President and Founder of Arc Intermedia, quoted directly with his company linked. Attribution to a named person you can go and check is worth more than a bare URL.

Surfer supplies the remaining five, all first-party. Its blog traffic grew 358% in a year, 60% of leads and 27% of sales are attributed to that growth, and those three sit under a footnote linking to Surfer Unwrapped 2024, the company’s own report. A claim that 88% of SEOs treat topical authority as important links to Surfer’s own study. One more, that the content score captures 80% of possible on-page gains, carries no link. First-party data with a link beats no link, and it’s still the vendor marking its own homework.

Jasper’s three outbound domains are the best external sourcing in the set, and one of them is a software directory listing on G2 rather than a source. The other two go to Content Marketing Institute research and to Search Engine Journal. The catch is where they sit. One is anchored on the phrase “tracking ROI” in a sentence that states no fact, and the other on a phrase about search changing. Both are decorative rather than evidential, so a sceptical reader gets nothing to verify.

The research says machine prose leaks vocabulary, not errors

The academic literature backs up the shape of what we found, which is that the tell is stylistic and the substance problem sits underneath it. Kobak, González-Márquez, Horvát and Lause studied vocabulary shifts across more than 15 million PubMed abstracts from 2010 to 2024. Their excess vocabulary analysis estimates that at least 13.5% of 2024 abstracts were processed with a language model, rising to 40% in some subcorpora. The markers are ordinary style words used far more often than expected: “underscores” at 13.8 times its expected frequency, “showcasing” at 10.7 times.

A separate group led by Weixin Liang measured the same phenomenon in peer review. Their corpus-level estimate puts between 6.5% and 16.9% of review text submitted to ICLR 2024, NeurIPS 2023, CoRL 2023 and EMNLP 2023 as substantially modified by a language model. Both findings work at corpus scale rather than on a single document, which is the honest limit: neither method tells you that any particular paragraph was machine-written.

What that means for a blog is that word-frequency tells are fixable by anyone who cares to fix them, and these four have largely fixed them. Running the excess words that the PubMed paper names across our four vendor posts turned up one hit in Jasper’s (“potential”), one in Copy.ai’s (“showcases”), and none at all in the other two. The missing citations are not fixable by the same means, because the tool never had the source in the first place.

Google doesn’t care how the words were made

There’s a persistent belief that AI text carries a ranking penalty by itself. Google’s own position, published by Danny Sullivan and Chris Nelson of the Search Quality team, says otherwise.

Our focus on the quality of content, rather than how content is produced, is a useful guide that has helped us deliver reliable, high quality results to users for years.

Danny Sullivan and Chris Nelson, Google Search Quality team, via Google Search Central

The same post draws the line clearly: using automation, including AI, to generate content with the primary purpose of manipulating ranking is a spam policy violation. The spam policies themselves define scaled content abuse as generating many pages primarily to manipulate rankings rather than to help users, and name generative AI tools as one way of doing it. The trigger is intent and scale, not the software.

Which brings the argument back to sourcing rather than style. Google says it rewards content demonstrating experience, expertise, authoritativeness and trustworthiness. Whatever you think of that acronym as a ranking mechanism, nine statistics with no third-party origin between them is a hard case to make for any of the four.

The same draft through an API costs about twenty cents

Here’s the counter-pressure on all of these subscriptions. Anthropic’s published API pricing puts Claude Sonnet 5 at $2 per million input tokens and $10 per million output tokens, and the same page gives a rough conversion of one token to about 0.75 words. A 1,500-word draft is therefore roughly 2,000 output tokens, or two cents. Feed it 50,000 tokens of fetched research and that’s another ten cents. Ten web searches at $10 per 1,000 searches adds ten more. Call it $0.22 a draft, all of it our arithmetic from their published rates.

Against Writesonic’s $5.27 an article that’s a factor of roughly 24. Even a flat consumer subscription undercuts it: Claude Pro is $20 a month billed monthly, or $17 with an annual commitment. The honest counter-case is that none of those figures includes the person driving the thing, and the person is the expensive part. A brand voice you configure once, an SEO score, team seats and a content calendar are real work that somebody would otherwise do by hand.

Surfer provides a powerful starting point for your blog posts and streamlines much of the manual work with its AI content tools, getting you 70-80% of the way there in no time.

Henry Purchase, SEOSpace, quoted on Surfer’s own blog

That’s a customer testimonial on a vendor’s site, so read it as marketing. It’s also the most accurate sentence in the whole set, because it names the number the subscriptions don’t: the remaining 20% to 30%. That fraction is where the citations go in, where the numbers get checked against the study, and where somebody decides that the 74% has no owner and cuts it. Nothing in the four price lists we read covers that work, which is why the per-article price is the wrong number to compare on. For a wider view of how these platforms meter what they sell, we priced the billing models in buy a seat or run a GPU.

What we couldn’t verify, and what would change the conclusion

Four limits, stated plainly. We didn’t run any of the four products, so nothing here measures raw tool output; it measures published prose. One post per vendor is a sample of one, and a different post would move every number in the table. We can’t establish which sentences on those blogs were machine-drafted, only that the companies published them. And Surfer’s document allowance has no stated period, so the $0.41 rests on our assumption rather than their page.

What would change the conclusion is narrow and testable. If one of these tools shipped retrieval that attaches a live, checkable URL to every number it generates, and the URL survived a click, the editing cost we’re describing would mostly disappear. That’s a feature nobody in this set advertises today. Until it exists, the subscription buys you the draft and you still pay for the part that makes it publishable.