What Does an AI Writer Do in 2025?

Only a few years ago, businesses would specifically search for a “financial writer” or a “technical writer” to ensure their future writing assistant could combine jargon and human creativity while staying on top of the latest industry trends. Today, there’s a new applicant in town, the AI writer, who seems to do it all. Countless organizations flock toward artificial intelligence, often with good reason. It can save time and money, and a lot of the time, do a decent job. The problem with AI writing software is not that it’s inaccurate. At this point, we already know it can hallucinate, so your workflow has to account for fact checking and human oversight. The problem is that the mere term “AI” applies to so many different types of applications that it can be tough to tell the bare-bones grammar checker from the technical writing tool. So today, we’ll break down common categories of AI systems and see which one’s better suited for different types of written content. The AI Content Writer Landscape in 2025: Beyond the Marketing Jargon Whether you wish for the day when general AI is finally here or fear it, chances are we all have to wait a little longer. That means, if you’re using one tool to rule them all, you’re pulling back a slingshot from the safety of Rivendell, hoping it’ll land the ring in Mount Doom. In other words, you’re scaling effort instead of precision and banking on luck over fit. Now, staying on top of all the SEO content writers and other generative AI tools could give even an LLM a migraine, but most of them fall into four distinct categories. Subscribe toThe Content Marketer Get weekly insights, advice and opinions about all things digital marketing. Thanks for subscribing! Keep an eye out for a Welcome email from us shortly. If you don’t see it come through, check your spam folder and mark the email as “not spam.” The ‘Hold My Beer’ Generalists You’ve likely seen their names all over the press or on TV, but really, you should think of these as your brainstorming buddies. Incredibly flexible, generalist AI algorithms behind ChatGPT, Claude and Grok can help with a wide range of projects, including data analysis and writing tasks, but they can’t guide your content creation process unless you already know what you’re doing. While they’re not content writing specialists, their versatility can make them useful for creative exploration, whether your team is brainstorming a new product name or a single team member is trying to overcome writer’s block. Before filing any patents, make sure you double check that name, though. After all, all these tools can give you is a gobbled-up version of what’s already out there. The SERP-Climbing Sherpas These platforms build on top of broad, generalist models, providing dedicated workflows for AI-generated content that needs to perform in search engine results pages (SERPs). Some may also cover copy for press releases or social media. Think of tools like Brafton’s own contentmarketing.ai, Koala Writer, Anyword and SurferSEO. Keep in mind that your goal is not to check off “SEO.” Most of the time, you’re looking to automate very specific SEO-related tasks, be it outline drafting, keyword research or content repurposing. Each AI assistant leans into different parts of that process, so you’ll want to understand the feature palette and philosophy behind your subscription. SurferSEO, for instance, is aimed especially at agencies looking to prospect clients, audit existing content and scale article production with one-click workflows, whereas contentmarketing.ai focuses on supporting in-house content teams with specialized E-E-A-T-oriented workflows across formats. From generating on-brand blog posts and landing pages to press releases, social media copy and subject matter expert (SME) interviews, it helps writers move fast without losing sight of SEO or editorial quality. The Librarians of Logic Think of your customer trying to set up your product for the first time. They open your app’s installation guide and read instructions telling them to “enable legacy Bluetooth 5.3 compatibility mode” — a feature that doesn’t exist. That mode could be your competitor’s solution from last year, a made-up number or a mix of your app and software applying to a different industry, who knows? The point is, this kind of hallucination isn’t just confusing, it actively damages the user experience and trust in your brand (at scale!). Meanwhile, your marketing team is stuck using a generalist AI chatbot or landing page builders that aren’t designed to manage complex, evolving technical documentation. That’s why specialized platforms like Document360’s Eddy AI and ClickHelp matter. They help enforce style consistency, maintain accuracy and manage data efficiently across formats or multiple languages, making them essential for clear, reliable product documentation. Your Friendly Neighborhood Storytellers Narrative-driven content marketing may be a small niche, but for some brands, an AI model that’s actually meant for creative writing can act as a thinking partner. Co-pilots such as Squibler and Sudowrite can help with plot development, character creation and even generate descriptive prose to get your story off the ground. Not the first choice for brand stories, but if you already have an AI strategy and trained staff in place, it might be worth an experiment. Reading Between the Lines of AI Marketing Every content marketer started drafting some flashy, keyword-stuffed blog or landing page with allegedly hilarious puns. I’m no exception. I can’t look back on my early work without at least a bit of shame or amusement, but it’s how even the best human writer perceives engaging content when starting out. Some AI platforms, however, haven’t grown out of that phase. So if you’re trying to assess which subscription isn’t more than a fancy cash shredder, you need to read product descriptions with a strategic eye. Here’s what to look for. Long-term support vs. feature-heavy solutions: Does the platform seem focused on a core set of features and continuous improvement, or is it a grab-bag of every AI trend? Look for a tool that aligns with your long-term content strategy and business philosophy, not just one that has the longest list of jargon-stuffed features. Technical setup requirements: Be realistic about your team’s technical expertise. Ask or poll them, anonymously if necessary. If a platform requires a complex setup or deep understanding of APIs, your team should feel comfortable using it, not freaked out by the very thought of touching their laptop’s power button. A powerful tool is useless if nobody knows how to use it. Red flags: Be wary of promises that sound too good to be true. Vague claims about “unprecedented results” or “fully automated content creation” can often tell you that a platform will require more manual intervention than advertised. What AI Writing Tools Actually Do: Function vs. Promise Now, as the one choosing the platform, you may not necessarily care what the tool actually does. That’s for your team to figure out, right? (Could we get the buzzer noise, please?) Consider that client reading your manual, the type of confidential company information you’ll feed into the platform, the scope at which your team will scale your (possibly wrong) messaging across marketing channels. Not a decision you want to leave to chance, is it? So, here’s a breakdown of what you can realistically expect from an AI writer across different content formats. Blog Posts and Articles Yes, an AI writer can be a massive help here, from integrating research and structuring outlines to maintaining a consistent tone (assuming its setup allows for that). However, these tools are not a replacement for subject matter expertise. The best results still come from a workflow where the human experts inform and/or review the content for accuracy and insight. That’s why we have built an interview workflow straight into contentmarketing.ai. Other tools may plan for a review process toward the end of the production cycle while others ignore E-E-A-T entirely. Social Media Content Most of us are social creatures, so the fact that most social media platforms are now focusing on true engagement shouldn’t freak us out. But it usually means you need to engage with peers or prospects while running a full-blown content production process, and AI can certainly be a game-changer for that. It can generate multiple variations of a post for A/B testing or repurpose and tweak content across platforms, saving your team hours of work. Email Marketing The oldie-but-goodie is still around, and just like in personalized ads for different social media audiences, you can draft targeted messages and subject lines that are more likely to get opened by your brand’s advocates, prospects and customers. Just remember that email marketing is one of the rare instances requiring actual placeholders for your reader’s name. Automation is only exciting until your first client responds to “Dear .” Ad Copy Product packaging. Highway ad signs. Witty 404 pages or voicemail messages. Whether you realize it or not, ad copy is all around you, and while most models won’t give you the equivalent of Apple’s 1984 clip after one click, you can rely on different models as creative sparring partners to generate countless variations, allowing you to test different hooks, calls to action and audience references to find a winning combination. Technical Documentation As we already covered, you don’t want to hand over documentation tasks for your most recent innovation to any old model, but under the right circumstances, AI can be a stickler for rules. It can enforce style guides with ruthless efficiency, ensuring all your documentation is consistent and easy to understand. And the repurposing functionality that makes it a great match for social media can also be handy when you’re creating different versions of a document for different audiences. When To Put the Brakes on AI As powerful as they are, AI tools can’t handle every job. Here are a few situations where you should think twice before handing over the reins. Content requiring deep SME insight without human oversight: If you’re producing content about a highly specialized topic or even one that happens to evolve rapidly (like AI), chances are an AI writer can’t replace the knowledge and experience of a true expert. Use AI to assist, not to create from whole cloth. Highly regulated industries: Whether due to privacy and compliance or recent changes in applicable research, in fields like finance or health care, you’ll want to double-check everything, and for good reason. While AI can help with initial drafts or rough outlines, all content must be thoroughly vetted by experts. Crisis communication: When your brand is in the hot seat, you need a human touch. And as believable as the output may be getting, AI often still lacks the emotional intelligence and nuance required for sensitive messaging. Original research and data analysis: While AI can support certain research tasks — like scanning academic papers, parsing large datasets or even assisting with technical domains like genome sequencing — it can’t independently design studies, interpret results in context or draw novel conclusions. Human researchers are still essential for shaping hypotheses, validating findings and ensuring methodological integrity. Personal brand storytelling: No matter what any landing page tells you, there’s nothing more unique and non-reproducible than yourself. Your voice is your most valuable asset. While AI can help you brainstorm ideas and finetune output based on what you like and who you are, you should spend a significant amount of time on defining those parameters before scaling. Strategic Implementation: Building Frameworks for ROI I’m guessing you already knew this, but the click on a “Buy now” button won’t magically transform your content strategy, no matter which tool you choose. To see a real return on investment, you need to integrate that tool thoughtfully into your team’s workflow, and you have a few options of doing it. The AI-powered team: Think of this as a specialized relay race. Let’s say your SEO strategist uses a tool like contentmarketing.ai to ensure all your blog posts and white papers follow the same brand and content briefs, and a content editor, who focuses on refining generated drafts, ensures your copy doesn’t contain competitors’ branded keywords and refines it for brand voice and accuracy. Each person has a distinct, AI-augmented role in the content production line. The human-AI collaboration framework: This approach might be less of a handoff and more of a continuous rally between one human and their AI partner. A content creator might start by brainstorming titles with a model. Then, they write the intro themselves before asking the AI to draft the next section based on an outline. The creator then edits the output, adds their own expertise and then prompts the model for another section, on and on until the piece is done. It’s a partnership with clear checkpoints, but if all checkpoints depend on the creator, it’s difficult to scale beyond that one person. The compliance-aware AI assist model: Every word matters, but that’s even more true in industries like finance or health care. Here, AI can still play a role, but within carefully controlled guardrails. An SME might use a model to surface recent guidance, summarize dense research papers or draft internal content outlines. Then, compliance specialists and legal reviewers step in to vet every piece before publication. In this framework, AI is treated as a tool for speed and scale, not as the final author. Prompting Is a Matter of Your Platform’s Design and Philosophy How you talk to your AI matters, but how you need to talk to it depends heavily on the tool you’re using. A generalist platform like ChatGPT is a blank slate; it needs a ton of context to produce on-brand, accurate content. In contrast, specialized platforms often have built-in guardrails and workflows that require less detailed prompting because the strategic framework is already part of the system. Your prompting strategy should adapt to the platform’s design — less hand-holding for specialized tools, more detailed instructions for the generalists. Regardless of the platform, be mindful of your company’s data handling policies. Avoid including sensitive customer or business information in your prompts, especially when using public AI models. Legal and Compliance Considerations To Guide Your AI Writing Process Just like I as a writer don’t need to explain the acronym “AI” anymore, legal and compliance experts are also adapting to our new shared reality. For optimal results, it’s still best to stay ahead of recent decisions, just in case. AI Disclosure Requirements Industry-specific regulations: Some industries will have strict rules about how AI can be used. Make sure you’re up to date on the regulations that apply to your business. Regional compliance: Laws like the EU AI Act and various state-level regulations are setting new standards for transparency. Be prepared to disclose when and how you’re using AI. Best practices: Even if it’s not legally required, it’s often a good idea to be transparent with your audience about your use of AI. This can help build trust and manage expectations. Risk Management Frameworks Intellectual property: Be careful to avoid copyright infringement. Ensure your AI writer is trained on ethically sourced data and that you have the rights to use the content it generates. Accuracy verification: Establish a fact-checking protocol for all AI-assisted content. Don’t take the AI’s word for it, especially when it comes to stats, dates or other factual information. Data privacy: If your business handles sensitive customer data, be extra cautious about how you use AI. Ensure your chosen platform has robust security measures in place and that your prompting strategies don’t expose private information. Measuring Success Beyond Content Volume Take my word for it: The fact that AI can keep churning out more words will get old fast (at least after the third draft opening with “this ever-changing landscape”). The true measure of an AI writer’s success lies in driving tangible business results. Instead of focusing on volume, track the ROI metrics that actually move the needle: Content quality and performance: Are engagement rates and conversions improving? Is your brand voice more consistent across all channels? Team productivity: How much faster is your time-to-publish? Are your content creators able to shift their focus from drafting to more strategic, high-value tasks? What are those? Long-term sustainability: Look at the bigger picture. Are you seeing reduced content creation costs and improved content performance over time? Your customers won’t care who wrote it — as long as it helps them. Writers will argue, adapt and sometimes resist, but if the work gets sharper, more strategic and less soul-crushing, they’ll embrace the change. The real win isn’t word count — it’s impact. Note: This article was originally published on contentmarketing.ai.

About the Author: PPCRAO

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