AI Content: Authenticity Wins in 2026 Contentful

Using AI in our content workflows changes how we talk to our audience which means we have to rethink our approach to AI creative content. Yes, automation gives us speed we’ve never had before, but if the content doesn’t feel like it’s coming from you, it’s just noise. For any real content strategy to work, you have to protect your brand authenticity. The real challenge is making sure that what the machine generates actually connects with people. So, how do we get that balance right between fast AI output and the human touch that actually builds a brand?

Step 1: Setting Up Your AI Content Assistant in Contentful

By 2026, Contentful’s AI Content Assistant is pretty much standard for any team trying to produce more content without it turning into junk. Getting the initial setup right is everything. This is how the AI learns your brand’s personality. Just turning the feature on won’t cut it. The quality of what you get out is a direct result of the precision you put in at the start.

1.1 Accessing the AI Content Assistant Module

Inside your Contentful dashboard, head to the left sidebar. Go to “Settings,” then find and click “AI Integrations.” You should see a list of AI modules. Find the “AI Content Assistant” and click it to open the configuration panel. If it’s your first time, a prompt will ask you to enable the service. Click “Activate Assistant” to get started.

1.2 Defining Brand Voice and Tone Profiles

Now, in the AI Content Assistant settings, look for the “Brand Voice Profiles” section and click “Add New Profile.” You’ll have to name it (something like “Corporate Tone,” “Casual Blog,” or “Product Launch”). This is where you bake your brand’s personality into the tool. I tell clients to be painfully specific here. Don’t just write “friendly.” Write “Friendly, but authoritative, using second-person address (`you`, `your`) and avoiding internal jargon.”

1. Tone Sliders: You’ll see sliders for things like “Formality,” “Enthusiasm,” “Urgency,” and “Empathy.” For a B2B SaaS client, I might push Formality to 75% but keep Enthusiasm at 50% and Empathy at 60%. These numbers aren’t random. They directly change the AI’s word choices and how it builds sentences.
2. Keyword Inclusion: Use the “Key Phrases and Exclusions” box to list your core brand phrases that should show up often (e.g., “innovative solutions,” “customer-centric approach”) and, just as important, words to ban (e.g., “cheap,” “run-of-the-mill”). This keeps your vocabulary consistent.
3. Grammar and Style Guide Upload: Contentful now lets you upload your brand’s style guide as a PDF or link to it on a Confluence page. Find the “Style Guide Reference” section and click “Upload Document”. This feature is a huge deal because the AI can finally learn your specific house rules, like whether you use the Oxford comma or how to capitalize your product names correctly every time.

Pro Tip: Create different voice profiles for different jobs. A social media update needs a completely different feel than a whitepaper. Trying to use one profile for everything is a recipe for bland, generic copy that nobody wants to read. Test each profile with a couple of quick prompts to make sure it’s doing what you expect.

Step 2: Generating Content Drafts with AI

With the AI Content Assistant properly set up, you can start making drafts. The trick is giving the AI clear, tight prompts that point it in the right direction. You can’t expect it to read your mind. I think of the AI as a very fast junior writer who needs crystal-clear instructions to do anything useful.

2.1 Initiating Content Generation within an Entry

Open up a content entry in Contentful, a blog post, a product page, whatever. Find the rich text editor field where you need the new content. You’ll see a little AI icon (it’s usually a brain or a star) in the toolbar. Click it and the AI Content Assistant box will pop up.

1. Content Type Selection: First, the assistant asks what you’re trying to generate. You’ll see options like “Blog Post Section,” “Product Feature,” “Meta Description,” “Social Media Caption,” or “Email Body.” Pick the one that fits. This helps the AI stick to the format you actually need.
2. Prompt Input: Now for the “Describe Your Content” box. Get specific. A prompt like “Write about our new product” is useless. Instead, try this: “Generate a 300-word blog section introducing our ‘Quantum Leap CRM.’ Focus on its real-time analytics dashboard and its smooth integration capabilities. The target audience is small business owners who are struggling with data silos. Make sure to emphasize how it improves their decision-making.”
3. Voice Profile Selection: Don’t forget to pick the “Brand Voice Profile” you just set up in Step 1 from the dropdown menu. If you skip this, you’ll get the AI’s default neutral voice, which is almost always bland.
4. Draft Generation: Hit “Generate Draft.” The AI will take about 10-30 seconds, depending on how complex your prompt was, and the draft will pop up in a preview window for you to see.

Common Mistake: Writing vague prompts. “Write about marketing” will get you a generic, useless article. A much better prompt is, “Write a 500-word article for marketing managers about how first-party data strategies are changing after cookie deprecation, and cite some recent IAB reports.” Given that an IAB 2023 Data Privacy & Measurement Report found 75% of marketers are rethinking their data strategies, that’s a topic that will actually produce a focused and valuable draft.

Step 3: Refining AI-Generated Content for Authenticity

Getting a draft from the AI is just the start. The real work, and the art, is in the human editing. This is the stage where a writer adds genuine empathy and the specific insights that an algorithm can’t invent, which is how you protect your brand authenticity.

3.1 Using AI for Sentiment and Tone Adjustment

After you generate a draft in Contentful’s AI Content Assistant, you’ll see a “Refine Options” panel, usually over on the right.

1. Sentiment Analysis: Click “Analyze Sentiment.” The tool will highlight text and give you a score (like “Positive: 85%, Neutral: 10%, Negative: 5%”). It might even suggest different words for spots where the tone is off. For example, if a product description sounds too timid, it might suggest changing “could potentially improve” to “will significantly enhance.”
2. Tone Rephrasing: The “Tone Adjustment” dropdown is your friend here. You can pick options like “Make more enthusiastic,” “Soften the language,” “Increase formality,” or “Simplify for broader audience.” Applying these will rewrite parts of the text, letting you make small fixes without having to start over. I find this incredibly useful when I need to adapt one core idea for several different audiences.
3. Conciseness and Clarity: The “Conciseness” tool can be a lifesaver. Clicking “Shorten Sentences” or “Remove Redundancy” helps you kill the wordy, roundabout sentences that AIs often spit out, which tightens up the copy immediately.

Pro Tip: Never just accept what the AI suggests. The suggestions are starting points, not finished products. For example, if the AI suggests a more enthusiastic tone and offers the word “bold,” you have to ask yourself if “innovative” fits your brand better. That human judgment is what keeps your brand voice from going completely generic.

3.2 Human Editing and Value Addition

Here’s where an experienced editor or writer earns their keep. The AI gives you the raw material, but it’s a human’s job to shape it into something worth reading. After using the AI’s refinement tools, paste the text into your main editor and get to work.

1. Fact-Checking and Accuracy: You have to verify every single statistic, claim, or technical detail the AI comes up with. They are getting better, but these models can still “hallucinate” facts out of thin air. If the AI gives you a market growth percentage, you better go check it against a reliable source like Statista’s marketing and advertising outlook.
2. Injecting Unique Insights: Add your own point of view, a relevant case study, or a personal anecdote. An AI can summarize what’s already out there, but it can’t create a new idea from your own professional experience. That’s what makes your content different from everyone else’s.
3. Emotional Resonance: Read the whole thing out loud. Does it sound like it’s coming from a person at your company? Does it create the feeling you want it to? I often find myself adding a personal metaphor or a sharp rhetorical question that makes the text feel human, not algorithmic.
4. Call to Action Optimization: AI can write a basic CTA, but a good marketer knows how to write one that actually convinces someone to click. Make sure your final CTA is clear, direct, and lines up with where the user is in their journey.

Editorial Aside: The biggest mistake I see is companies treating the AI as a magic bullet and publishing its first draft. It’s an accelerant, not a replacement for a writer. If you push AI content live without heavy human polish, you’ll start sounding generic, you’ll lose reader trust, and your brand will get diluted. I’ve watched engagement metrics crater for brands that made this mistake because their content suddenly sounded like everyone else’s.

Step 4: A/B Testing and Performance Monitoring

You can’t know the real impact of an AI-assisted content strategy without measuring performance. Never assume that just because content is faster to produce, it’s actually getting better results. The data is what tells you the truth.

4.1 Setting Up A/B Tests for AI-Generated Content

Most modern CMSs, Contentful included, can connect to A/B testing tools. Let’s say for this example that you’re hooked up to Optimizely Web Experimentation.

1. Create Variations: In Contentful, make two versions of something. Maybe one is a lightly edited AI draft and the other is heavily rewritten by a human. Or you could test two AI drafts against each other, each with a different tone. For example, test an AI headline like “Boost Your Productivity with Quantum Leap CRM” against a human-edited version like “Unlock Peak Performance: Introducing Quantum Leap CRM.”
2. Optimizely Setup: Go into your Optimizely Web Experimentation dashboard and start a new A/B test.
3. Targeting: Decide who sees the test. It could be all visitors, or maybe just a segment like first-time users.
4. Goals: This is the most important part. Define what success looks like. For a blog post, maybe it’s “Time on Page” or “Scroll Depth.” For a product page, it’s probably “Add to Cart” clicks or the final “Conversion Rate.” Set these up as your primary goals in Optimizely.
5. Traffic Allocation: Split your traffic between the versions, usually 50/50.
6. Launch Experiment: Once it’s all set, launch the test.

4.2 Analyzing Results and Iterating

You’ll need to let the A/B test run until it reaches statistical significance, which might take a few weeks depending on how much traffic you get. Then it’s time to dig into the results.

1. Review Performance Metrics: Check in Optimizely to see which version won based on the goals you set. Did the AI headline get more clicks? Did the human-edited description lead to more sales?
2. Identify Patterns: Start looking for trends across your tests. If your AI-generated content always seems to have a lower time on page, that’s a signal that your editors need to spend more time improving the story and flow. If the AI is great at writing short, high-CTR meta descriptions, then let it do more of that.
3. Feedback Loop: Take what you’ve learned and use it to make your AI Content Assistant setup even better. If the “Direct and Factual” voice profile is killing engagement, maybe you need to adjust its settings to be a bit more “Empathetic.” Go back into your Brand Voice Profiles in Contentful and make those tweaks.
4. Iterate: Good marketing is never done. You take the A/B test results, adjust your workflow, and run another test. This kind of feedback loop is the only way to make sure your use of AI is actually getting better and helping you hit your goals.

By testing and tracking the performance of your AI creative content, you get hard data on what your audience actually responds to. This ensures that the automation is making your brand authenticity stronger, not weaker.

Finding the right mix of AI speed and human touch isn’t something you figure out once. It’s a constant process of adjustment. If you’re disciplined about configuring your tools, writing good prompts, demanding a high-quality human review, and actually testing the results, you can produce more content without losing what makes your brand unique. This smart collaboration between people and machines is exactly what a modern CMO CX strategy requires to be effective.