Every B2B business is making choices about AI right now. Some are making smart choices. Some are not.
Anyone with a ChatGPT account can pump out 10 blog posts before lunch. But that convenience has created a flood of content that looks polished and says nothing, exactly like stock photos with no individuality. As a result, prospects are tuning out.
The problem isn’t AI itself. It’s how teams use AI.
The smart ones know that AI is neither a magic solution nor something to avoid. They understand which parts of content creation benefit from AI speed and which parts require human judgment that cannot be automated. They can spot the difference between how AI adds value and how it adds risk.
With 88% of organizations now regularly using AI[1] in atleast one business function, according to McKinsey, the competitive advantage goes to those who know how to navigate the middle ground.
If your team is using AI to create content, they need to be aware of the hazards and promises of AI. This article decodes a few key terms that have come to characterize the writer’s world.
AI Slop: The Fast Food of Content
You might have scrolled through LinkedIn posts that say everything and yet, nothing. That is AI slop–the fast food of content. AI slop refers to content that is generic, shallow, and often riddled with inaccuracies or simply made-up information.
What makes content “sloppy” is that it is generated without adequate human oversight or quality control. Being generic, it could be used for different scenarios by simply interchanging the facts.
AI slop happens when organizations prioritize volume over value and skip the human verification layer that catches errors and adds differentiation.
In November 2023, Sports Illustrated was accused of publishing product reviews under fake author names with AI-generated profile photos [2]. When reports of it came out, the company removed the content, launched an internal investigation, and ended its partnership with the third-party that had created the reviews.
What You Can Do Differently
- Define AI use clearly. Have open conversations with your team about what to use AI for and what not to. For example, encourage your team to create AI workspaces for collaborative research and knowledge sharing. But put boundaries on how much of the final output can be AI-generated.
- Audit your last 10 published pieces. If you’re using AI to generate content, read your published work with fresh eyes. Is there anything distinctive about your content besides your logo? Any insights or perspectives that are uniquely yours? If there isn’t, you are producing slop.
- Implement the experience test. Before publishing, ask: what part of this could only have been written by someone who has worked in this space? If nothing passes that test, rewrite.
AI Hallucination: When AI Confidently Makes Stuff Up
Hallucination takes place when AI models confidently generate false information. This happens because large language models predict patterns in language based on their training data, not by verifying facts. When models encounter gaps in their knowledge or receive inadequate prompts, they fill in missing details with what seems statistically plausible based on patterns they have learned.
Responses that contain AI hallucination can easily pass off as genuine until someone verifies them. The now-infamous case involving Deloitte Australia is a classic example of hallucination.
In 2024, the Australian government commissioned Deloitte to conduct an independent review of its welfare compliance system. Deloitte submitted a 237-page report and was paid $290,000.
A University of Sydney researcher, Chris Rudge, spotted big problems in the paper–a fabricated quote from a court judgment and nonexistent academic papers. Deloitte admitted the report was generated using Azure OpenAI’s GPT-4o, which invented citations[3]. The firm refunded the final payment installment and issued a revised report, but the damage to their credibility was already done.
What You Can Do Differently
- Never publish a stat without clicking through to the source. If AI provides a number, verify it exists in the cited document.
- Build an exhaustive checklist. Ensure nothing gets left out of your verification–data and interpretation of data, quote attribution, details of cited studies, and accuracy of company names and technical terms.
- Implement dual review. Have someone who did not write the piece go over the details before you hit publish.
Vibe Writing: The Strategic Middle Ground
In software engineering, vibe coding[4] is a practice of letting AI handle the scaffolding, such as basic structure, boilerplate, and pattern matching, while humans supply the creativity and judgment. With a “code first, refine later” principle, the developer decides what to create, how to position it, where the risks are, and when to intervene.
That same principle applies beautifully to content, a process some are calling vibe writing.
AI aggregates research, pulls benchmarks, and helps spot common frameworks, which takes some of the cognitive load off writers. Then we step in with the human layer by bringing domain insight, strategic positioning, and creativity that reflects a brand’s personality.
Vibe writing gives us the best of both worlds with content creation that moves at AI speed but carries the depth, clarity, and strategic intent only humans can offer.
What You Can Do Differently
- Define your human value layer first. Before using AI, articulate what makes your perspective unique. What do you know from experience that AI cannot learn from training data? That becomes your quality bar.
- Start with the emotional arc, not the outline. Ask yourself: what is the emotional journey? Where should the highs and lows land? AI can structure information, but you decide how it should make someone feel.
- Write as you speak. A crafted version of natural speech creates an immediate connection. AI gives you bland corporate; your job is to inject conversational humanity into it.
Other Terms Worth Understanding
As you navigate conversations with agencies, vendors, or internal teams, a few other buzzwords will inevitably show up. Here’s what they mean and why they matter to anyone who writes with or alongside AI:
Stochastic Parroting: A technical term for what AI does, remixing patterns from training data without truly understanding it. It predicts what comes next based on probability, not comprehension.
Mode Collapse: It refers to AI text becoming increasingly repetitive or formulaic over time. It is common in free models or when systems are heavily fine-tuned on limited datasets.
Template Bias: It is about AI’s tendency to fall into predictable structures. If your content starts with “In today’s fast-paced world” or “In an era of digital transformation,” you are seeing template bias in action.
Prompt Drift: When AI gradually moves away from your original instruction or tone as the conversation continues, it’s called prompt drift. The longer the thread, the more likely AI is to lose the plot.
Synthetic Prose: It includes output that feels machine-generated even when factually correct. Too balanced, too neat, too careful. It reads like a committee wrote it, because in a way, the entire internet did.
De-slopping: It is the process of editing AI output to remove generic patterns and inject authenticity. This is exactly what your content team should be doing before anything goes live.
The Takeaway for Writers
The real advantage in the age of AI is judgment, and not speed. Writers who understand the risks around slop and hallucinations can use AI tools without falling into the traps that have impacted big brands. Writers and reviewers need to stay alert to quality, be honest about what’s automated, and keep the human layer at the center of the output.
When AI becomes a complement instead of a crutch, you get efficiency without losing credibility or craft. That’s the balance the best teams are learning to strike.
If you want partners who know when to lean on AI and when to lean on expertise, let us talk.
References:
- https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai
- https://www.bbc.com/news/world-us-canada-67560354
- https://www.business-standard.com/technology/tech-news/deloitte-ai-hallucination-report-australia-gpt4o-fabricated-references-125100800915_1.html
- https://www.ibm.com/think/topics/vibe-coding
