When our weblog staff made the swap to an AI-first writing mannequin in June 2025, my response was cut up. There was pleasure on one facet: I may see the inefficiencies in our course of that AI would possibly really repair. On the opposite, nervousness. And whereas loads of that nervousness was in regards to the expertise itself (how nicely these instruments may really write, how a lot we may belief them), my major concern was my staff.
I’ve managed HubSpot’s weblog writing staff for 3 years, and earlier than that was a HubSpot Weblog author myself. I perceive what it means to have possession over your course of. Lots of the writers I handle acquired into this work as a result of they love writing. They benefit from the craft of discovering the correct sentence and incomes a reader’s consideration. Visitors numbers and conversions are secondary. Throughout this AI transition, I felt the burden of what it may imply for these whose whole strategy to their craft was altering quick.
A lot of the general public dialog about AI content material will get the story flawed. There’s an assumption that as a result of AI can write passably nicely, the laborious half is over. Simply apply the identical low-effort polish you’d apply to an AI-drafted e mail or memo to your weblog submit, then ship it.
However I can inform you from expertise: it doesn’t work that manner. A weblog submit is supposed to compete towards dozens (or lots of) of different posts on the identical subject. On this sport, generic, low-effort writing is not going to win, and that’s excellent news in your content material staff. It signifies that regardless that the writing course of has modified, the craft stays essential.
So, how do you steadiness craftsmanship with the effectivity positive aspects AI guarantees? And the way do you construct a course of that takes benefit of what AI is definitely good at with out falling into its traps? We spent the final 12 months figuring that out. Right here, I’ll share what we realized: the place time was saved, the place it acquired added, and what it takes to make AI work with out compromising the standard requirements you’ve spent years constructing.
Desk of Contents
Earlier than AI, writing was private.
Earlier than AI, our writing course of was, nicely, a writing course of. Whereas we had editorial requirements and guardrails to make sure constant high quality, we didn’t implement a selected technique for the way posts ought to be written. We employed writers and editors for his or her capability to craft, and we trusted them to make use of that capability. We understood that writing is greater than only a technical talent. Giving our writers the house to develop their very own particular person workflows yielded content material with character and distinctive insights.
When coaching new writers, we taught a easy, versatile framework to assist of us begin to construction their time:
- Outlining and planning took round half-hour to an hour.
- Analysis may take one to 2 hours, relying on the complexity of the subject and the author’s familiarity with it. This included sourcing quotes, discovering authentic information, and writing from private expertise.
- Drafting, the half the place somebody really places phrases to the web page, took round 5 to seven hours on common for a primary draft.
- Modifying, QA, formatting, and finalizing in our CMS added one other roughly two hours on high of that.
For the standard weblog submit, you’re simply taking a look at a full day’s work, often longer. The majority of that point lived within the drafting part — writing the phrases, discovering the correct construction, and determining the way to clarify one thing clearly was the core of the job.
What We Discovered From Letting Writers Lead
After we formally adopted AI-assisted writing in June 2025, my strategy was deliberate: don’t over-prescribe. Permitting our writers to develop their very own processes had served us nicely for over a decade, and we needed to keep up that sense of management for our writing staff as a lot as doable, at the same time as we added AI to the combo.
We gave writers entry to AI instruments (particularly Claude and ChatGPT, together with NotebookLM) and house to determine the way to work them into their course of. Even with AI, I believed writing is private, and I wasn’t going to inform a staff of skilled writers precisely the way to do their jobs. Our aim was experimentation first, construction later.
What adopted was not the clear effectivity win I anticipated. AI solved some issues and launched new ones. However by working by way of these issues with our writers, we constructed a course of that we all know works.
Quicker drafting doesn’t imply quicker content material.
At first, the indicators had been good. Writers had been placing phrases on the web page quicker than earlier than, and I assumed that might translate straight into quicker posts total.
It didn’t.
A few months in, after reviewing time monitoring information and having conversations with my staff, a extra difficult image emerged. The amount of posts stayed about the identical, however posts had been getting longer, extra detailed, and extra demanding to supply. Writers had been spending extra time testing software program, sourcing professional quotes, reviewing instruments in-depth, and going deeper on subjects. The time AI saved in drafting was being absorbed by every little thing else a aggressive submit requires.
What made it tougher was that some writers felt the strain of each expectations without delay: write quicker and write extra. After I understood that this was taking place, I needed to recalibrate. AI hadn’t decreased the workload. In some ways, it had elevated the workload.
So my first lesson was: When you’re measuring AI’s impression in your staff purely by submit rely, you’re going to be disenchanted. The win is in what these posts turn out to be, not how briskly they get there.
Analysis was our largest shock.
I additionally assumed AI would make analysis quicker. In spite of everything, as an alternative of spending an hour getting up to the mark on a subject, a author may ask Claude and transfer on.
For normal subject data, that’s really true. On well-documented topics with loads of coaching information to attract from, AI can clarify ideas clearly, reply follow-up questions, and get a author up to the mark quicker than navigating a dozen browser tabs.
The shortcomings, nevertheless, had been flagged by writers virtually instantly.
The primary time it actually surfaced was on a listicle protecting competitor merchandise. A author got here again to me flagging that the pricing info AI had surfaced was flawed. Not barely off, however absolutely outdated. AI didn’t know the pricing had modified, and it didn’t flag its personal uncertainty.
I in all probability ought to have seen that one coming. In spite of everything, a instrument educated on information from months in the past clearly can’t know {that a} competitor modified their pricing. However it took a author caring sufficient to flag it earlier than I accounted for it.
From this, we realized that for something requiring accuracy about competitor pricing or options, AI analysis falls aside. This is smart when you consider how these instruments work: An LLM’s coaching information has a cutoff date, which means it’s unlikely to replicate the most recent pricing adjustments, function updates, or product rebranding. And when AI instruments do try a dwell internet search, they’re solely nearly as good because the pages they’ll parse. Product pages are sometimes structured in methods which are tough for an LLM to interpret, which makes even real-time lookups susceptible to inaccuracies. The result’s info that sounds authoritative however could also be months or years outdated.
We produce loads of competitor listicles and product-focused content material, and for these, analysis nonetheless requires vital handbook effort. So whereas AI has sped up general-topic analysis, competitor- and product-focused analysis takes roughly the identical period of time because it at all times has.
The Hallucination Drawback
The analysis drawback ran a lot deeper than product pricing alone. Past outdated competitor information, we had been seeing fabricated statistics, misattributed quotes, and incorrect terminology, all delivered with the identical assured, authoritative tone. AI doesn’t know what it doesn’t know.
We place a excessive premium on accuracy, and these so-called AI hallucinations turned fact-checking from a light-weight ultimate step into some of the time-consuming components of the method. In some circumstances, AI drafting took longer than handbook drafting as a result of writers needed to spend time verifying what the AI acquired flawed.
What struck me was how rapidly my staff caught it. That dedication to publishing solely truthful, verified info is strictly what separates a great author from a content material generator. It bolstered one thing I already believed: the author issues greater than the instruments they use.
To deal with hallucinations, we launched a brand new formal step in our course of: devoted fact-checking. Pre-AI, writers had been chargeable for the accuracy of their very own analysis, and a ultimate editorial go would catch something apparent. With AI within the combine, fact-checking turned its personal distinct part. For a typical submit, I estimate it provides round 30 to 60 minutes to the method. It’s longer for research-heavy items or something involving stats, quotes, or product info.
Positive, you may skip fact-checking and assume AI will get every little thing proper. However is that basically the usual you wish to maintain your content material to? Publishing misinformation, even unintentionally, damages belief in a manner that’s laborious to get well from.
High quality doesn’t police itself.
QA time grew too, for causes past what fact-checking was already catching. Reality-checking is the method of verifying that the data in a submit is right. QA is about every little thing else: Does this submit sound like an individual wrote it? Does it meet our editorial requirements? Is it structured in a manner that engines like google and AI instruments can parse?
With no structured high quality layer, AI-assisted drafts launched issues writers wouldn’t essentially catch on their very own, akin to:
- AI clichés and hedge-word-heavy phrasing (“it’s price noting,” “leverage,” “it’s essential to know,” and so on)
- Redundant sentences.
- Plagiarism from competing content material (not intentional, however from fashions quoting their supply materials straight within the output)
- Damaged or defective hyperlinks
- Lacking picture alt textual content
- Incorrect heading orders
- Sentences, paragraphs, and sections that aren’t optimized for LLM chunkability.
To deal with this, I constructed a customized QA checker straight into Google Docs that flags these issues and extra. It’s turn out to be a required step in our workflow.
What AI Didn’t Contact
By all of the adjustments above, some issues didn’t transfer. The E-E-A-T necessities we had earlier than AI — authentic quotes, firsthand views, strong information sourcing — stayed intact. Editorial judgment stayed intact. The strategic considering that goes into deciding what a submit must say, and who it must say it to, stayed intact.
AI handles a lot of the execution now: drafting, scoping, producing subject angles, and explaining ideas. However the layer of labor that makes a bit price studying (the human perspective, the unique perception, the rigorous sourcing) remains to be on the author. If something, it issues extra now as a result of it’s what separates your content material from everybody else’s AI output.
Evaluating Pre-AI vs. Put up-AI Writing
To grasp what modified, it helps to see it. Right here’s a tough breakdown of how time was distributed throughout a typical weblog submit earlier than AI, and the way that distribution shifted after we adopted it:
Observe: Time estimates are averages based mostly on HubSpot Weblog Staff inner monitoring. Particular person posts fluctuate based mostly on subject complexity, size, and content material kind.
After all, the fact varies greater than these charts recommend. A author would possibly draft for an hour, understand they want extra analysis, return to drafting, catch one thing that wants fact-checking, and return to drafting once more. An actual workflow seems extra like this:
Nonetheless, the time financial savings are evident.
AI content material at scale is straightforward. AI content material price studying is tough.
If AI can generate a weblog submit in minutes, why not simply publish and transfer on? Extra content material means extra possibilities to rank, extra floor space for leads, and extra output for much less effort, proper?
Early within the AI content material increase, all of us observed a sure technique rising within the search engine optimisation house: Publish as a lot AI-generated content material as doable, as quick as doable, and seize market share earlier than rivals caught on. Flood the zone. It operates on the assumption that quantity alone could be sufficient to win.
Besides, it isn’t, and the implications caught up.
Slop at Scale
The content material that comes from such a fast-and-loose technique is recognizable to anybody who’s hung out on this business.
A weblog submit that strings collectively sentences with out saying a lot. A listicle that might have been written about any firm in any business. No authentic information. No actual viewpoint. No particular examples that couldn’t have been fabricated. And should you run it by way of a plagiarism checker, you’ll even discover content material that was lifted from competing sources (not deliberately, however as a byproduct of how LLMs work).
In brief, it’s generic. You’ve in all probability heard the time period “AI slop” to explain this sort of content material as nicely. Skilled readers and, extra importantly, search algorithms can spot slop from a mile away, and it hurts way over it helps.
Entrepreneurs are catching on. In keeping with HubSpot’s 2026 State of Advertising and marketing Report, 52% of entrepreneurs imagine AI has made content material really easy to create that it’s turn out to be much less efficient total.
Want extra proof? In 2026, search engine optimisation professional Lily Ray tracked greater than 220 web sites that recognized themselves as prospects of AI content material creation platforms and located a constant sample: speedy development in natural visitors, adopted by a steep decline that, in lots of circumstances, erased the positive aspects completely. Throughout her dataset, greater than half of the websites misplaced no less than 30% of their peak natural visitors, and almost 1 / 4 misplaced 75% or extra.
Right here’s an instance of what that appears like for one such web site.
I perceive why groups took to this strategy at first. The strain to supply is actual: 83% of entrepreneurs say they’re anticipated to create extra content material than ever due to AI.
However that is precisely what main solely with velocity seems like in apply. If high quality turns into one thing you attempt to retrofit after the very fact, it not often works.
Begin with requirements, then add AI.
The groups doing AI writing nicely begin from the other finish. They outline what “good” seems like — voice, depth, accuracy, originality — after which work backward to find out the place AI may also help them get there quicker with out compromising on these requirements. All writing is anchored in high quality from the start.
On the HubSpot Weblog, which means preserving our E-E-A-T necessities intact. We construct high quality guardrails into our workflow and are sincere about which content material varieties profit from AI involvement and which don’t. For instance, a how-to information and a bit of authentic analysis can have completely different necessities, and treating them the identical manner will lead to generic content material that goes unnoticed.
As former Director of the HubSpot Weblog Karla Hesterberg places it: “The one really easy course of produces slop.” Groups that resist the slop, maintain good writers within the driver’s seat, and use AI as a lever quite than a substitute are those producing work that converts.
For a extra thorough dive into how we preserve high quality requirements in an AI-assisted editorial course of, take a look at this submit from HubSpot Weblog author Amy Rigby on how HubSpot creates high quality content material within the age of AI.
What This Means for Individuals Managers
Virtually in a single day, my function shifted in two instructions without delay. On one facet, I turned extra process-oriented than I’d ever been. I needed to assume extra deeply about workflows, tooling, and the way posts get assembled. On the opposite, individuals administration acquired tougher. Not as a result of my writers had been tough, however as a result of I used to be asking them to vary how they work.
Course of adjustments are comparatively easy to doc, however sustaining motivation and morale by way of a transition that basically modified their jobs is a unique drawback completely. You may construct probably the most considerate AI writing course of on this planet, but when your writers aren’t purchased in, none of it really works.
Writers come to this job for various causes, and AI lands otherwise relying on which cause that’s.
Some writers are wired for outcomes. They get into content material advertising as a result of they’re good at writing they usually like seeing the enterprise impression. For them, AI is a welcome change as a result of it will get them to the outcome extra rapidly.
Different writers got here to this work as a result of they love the craft. The writing course of is one thing they care about deeply. For them, an AI-first mannequin can really feel prefer it’s taking one thing away. I don’t see this as a efficiency concern or a failure to adapt. It’s an inner rigidity that ought to be taken significantly.
As a supervisor, my job is to acknowledge the place every staff member falls on that spectrum and work with them accordingly. I create an area for sincere suggestions, together with unfavourable suggestions about AI. I do know that if writers don’t really feel comfy telling me what isn’t working, I’ll construct processes on unhealthy info. The writers who most truthfully pushed again on our early AI workflows gave me the clearest roadmap for what wanted fixing.
Steps for Managing Your Staff By the AI Transition
Right here’s what I’d inform any supervisor navigating AI writing:
- Don’t over-prescribe early. Give writers entry to instruments and room to experiment earlier than locking in inflexible workflows.
- Mandate experimentation, not technique. The groups that prescribed particular AI utilization from day one created pointless friction.
- Acknowledge that you simply’re asking writers to vary how they work. That takes time and belief.
- Create house for sincere suggestions, together with constructive suggestions. If writers don’t really feel secure telling you what isn’t working, you’ll construct processes on unhealthy info.
- Perceive the place every author falls on the spectrum between outcome-driven and craft-driven, and handle them accordingly.
The aim hasn’t modified: a staff that produces work price studying. The trail to get there simply seems completely different from what it did in 2024.
My Takeaways as a Content material Staff Supervisor
A 12 months into this transition, I’m pleased with the place we landed, regardless that we’re nonetheless figuring some issues out.
What made the distinction wasn’t solely the instruments, however the writers. I knew that moving into, and this previous 12 months confirmed it at each flip. The writers who pushed again truthfully gave me the roadmap, and those who struggled helped me perceive what was really being requested of them.
What sticks with me most from this expertise is one thing writers have began saying lately: that they’re feeling like actual writers once more. The steadiness between AI effectivity and precise craft has began to really feel sustainable. That occurred not as a result of we discovered an ideal immediate or the correct instrument, however as a result of we by no means let go of what made our content material good within the first place.
When you’re an editorial lead navigating the AI shift proper now, know this: What will get you thru is having writers who care sufficient to be sincere with you, and being a supervisor who creates house for that honesty. Don’t underestimate what it means for a author to really feel like a author. It reveals up within the work.
AI is a instrument. Hold your writers on the middle, maintain the standard line, and the remaining follows.
