How Taste Enhances AI Content Quality In Enterprise Marketing

Judging AI content quality is really just a matter of exercising the same great taste that manifests itself everywhere else in life:

• In high school, there’s always someone who’s already listening to the next great musical artist before they top the charts.
• We’ve all walked into a living room (or seen one in a magazine spread) where every aspect of the décor is both beautiful and cohesive. Even the loudest and busiest patterns match perfectly.
• There are dinner parties where a guest manages to show up carrying the perfect wine to pair with the meal the hosts are serving.

You know great taste when you see it, hear it, feel it, or taste it. In enterprise marketing, taste is about knowing if content works when you review it.

Generative AI has made it much easier to produce content at scale, but more isn’t necessarily better. Teams can now generate dozens of drafts, variations, and summaries in the time it once took to polish a single headline. The hard part now is deciding what’s worth publishing.

That’s where taste comes in. And it’s something AI cannot replicate. Enterprise marketers not only need to cultivate it, but also know when to bring it into their AI-assisted workflows.

What ‘taste’ actually means in enterprise content

As AI adoption becomes pervasive, taste has become one of the tech sector’s favorite buzzwords. In a now-viral post on X, OpenAI president Greg Brockman said, “Taste is a new core skill.”

Paul Graham, the co-founder of legendary accelerator Y Combinator, shared similar sentiments, noting that “when anyone can make anything, the big differentiator is what you choose to make.”

Having great taste is not only relevant to making code for new software applications. It’s vital for B2B marketing teams trying to generate demand and brand affinity. According to a 2026 research study published by the Content Marketing Institute, 64% of enterprise marketers cite “content relevance and quality” as the top factor in driving greater effectiveness.

In enterprise content operations, AI requires taste — or editorial judgement — that understands your target audience’s needs and aspirations, and how they correlate with your brand’s value proposition, mission, and values. Exercising taste in this context is about articulating ideas so that they are both on-brand and on point for the people who discover them on your web site.

Think of this as a deliberate, structured filter that sits between AI-generated output and publication. This “taste layer” is where human expertise evaluates nuance, emotional resonance, cultural context, and brand fit. These are all dimensions that AI can mimic but not originate.

Taste is the difference between content that feels generic (otherwise known as slop) and content that feels like it came from your organization’s experts. It’s the reason one brand’s AI-assisted blog reads like a thought leadership piece while another’s reads like a summary of search results.

Where human judgement is irreplaceable

AI excels at pattern recognition, synthesis, and scale. But quality covers a different set of variables:

• Judging emotional resonance: AI can’t reliably predict what will move, surprise, or inspire a specific audience. It doesn’t feel. If you’re marketing to CIOs, for instance, you need content that helps them build greater alignment with other lines of business and treats them as innovators rather than the “‘no’ people” who stand in its way.
• Navigating cultural nuance: Subtext, tone, and timing require contextual awareness that AI often misses, especially in global or sensitive topics. Content aimed at a health care organization should comply with local laws governing patient privacy. Content aimed at small business owners should avoid excessive jargon or require deep technical knowledge.
• Making strategic trade-offs: Should AI-assisted content prioritize SEO, AI visibility, brand positioning, or product education? AI can optimize for various metrics, but humans need to choose which competing goals to balance. These differences play out in content that’s part of a short-term product launch campaign and evergreen assets intended to nurture qualified leads.
• Recognizing originality: AI remixes existing patterns. Humans spot genuinely new ideas worth amplifying. Great taste stems in part from the lived experience of salespeople who have learned from customers, marketers who run live events, and software engineers developing the next industry breakthrough.
• Knowing when to break the rules: Sometimes the best content defies conventions. AI is trained to follow them. There are occasions where it makes sense to directly mention a competitor, or to cite a high-profile story from the media. Sometimes putting content in the first person will prove far more effectively than the neutral voice representing your entire company.

Involving your top talent, whether they work on the marketing team or in another function, is a way to keep marketing content human, more distinctive, persuasive, and high-converting.

Building workflows that preserve taste (without becoming a bottleneck)

Talking about “taste” could be construed as an extra step that will prolong publishing cycles, which nobody wants.

When you balance your CMS’s AI’s capabilities and human judgement, however, the opposite happens. More quality content gets out the door, and you minimize the work that will come later when it’s time to refresh and repurpose your top assets. Achieve this by:

• Distinguishing between taste and governance checkpoints: You probably already have reviews and approvals in place to ensure brand safety or compliance. An AI content quality assessment is looking for opportunities to elevate an asset beyond what’s already available online.
• Establishing the appropriate cross-functional inputs: If you’re launching a new product or providing an update on strategic direction, you may need to bring in tastemakers, ranging from corporate communications and PR to R&D and customer success. Do this before draft content is developed to keep your publishing schedule on track.
• Tapping into your brand ecosystem: Great taste isn’t limited to those on the payroll. Look to your partner network if you have one, as well as industry influencers that may be participating in a campaign or speakers at an event you’re hosting. Don’t forget to look at customer insights gathered via sales and support calls, advisory boards, and those surveyed in yet-to-be-published case studies or research.
• Clearly communicating the ask: Your tastemakers should understand their role is not catching typos but looking at the content through your audience’s eyes and suggesting anything that will help the message land with greater impact.

Use this table to guide which subject-matter experts to lean on depending on what kind of content you’re developing:

Product & engineering

What they bring

Technical accuracy, feasibility, detection of overclaiming, identification of truly novel features

How to involve them

Scheduled technical review(s) during draft stage, checklist of capabilities to verify, short Q&A session for complex features

Example review focus

Confirm feature claims, validate timelines, suggest accurate wording for limitations and caveats

Sales & customer success

What they bring

Real-world objections, buyer language, resonance with prospects, common misunderstandings

How to involve them

Bring recent call transcripts or FAQs to reviewers, run a sprint review with reps, incorporate flagged phrasing into edits

Example review focus

Flag claims that sound like marketing, suggest language that answers common buyer concerns, ensure use cases match customer realities

Customers & Users

What they bring

Validation of clarity, usefulness, tone, and perceived value; detects gaps between intent and reception

How to involve them

Beta reader panels, advisory councils, targeted user interviews before publication, quick surveys on draft excerpts

Example review focus

Assess whether message lands, suggest real-world examples, point out confusing or overcomplicated sections

External experts & partners

What they bring

Credibility checks, industry context, unbiased reality check, media-ready framing

How to involve them

Share drafts with analysts, partner agencies, or journalists under NDA or embargo; request short annotated feedback

Example review focus

Verify market positioning, identify weak claims, suggest data or sources to strengthen credibility

Taste as a competitive moat

An article on Search Engine Journal suggested that the rise of AI answer engines could be the death knell for evergreen content, or assets that touch broadly on a topic that can be used to drive inbound traffic for an extended period of time. Instead, the author argues that first-person knowledge will become more important, with hands-on lessons from the frontlines defining great marketing content.

Even if evergreen content doesn’t completely go away, the more you can infuse it with the editorial judgement or taste from a living expert, the higher your AI content quality will be.

Taste is a powerful element in AI content strategy because it’s always evolving. As humans we constantly learn, are exposed to new ideas and refine what we decide is worthy of an audience’s attention. AI tools get trained on data, but human judgement brings in a lot of offline and private experiences that can’t be found through a search engine.

Brands can cultivate taste as a skill in part by empowering people inside and well beyond marketing teams to exercise their judgement in assessing AI-assisted content as an everyday process.

You can still invest in better models, platforms, and prompts. Just make sure you treat the expertise around you as another source of data and insight to enhance what AI helps you create.

For more on how people perceive content online and the human element they’re looking for, check out WordPress VIP’s 2026 Future of the Web report.

Read the report