Not all scams wear a black hat. Some just wear clean code and a polished landing page.
You Already See It Every Day
If you've used the internet lately, you've probably brushed up against a gray business model — maybe without realizing it.
- You search for a simple answer online, and find an AI-generated blog stuffed with SEO keywords but zero value.
- You install a “free” app that promises to boost your productivity, only to find it’s locked behind vague upgrade tiers.
- You sign up for a newsletter packed with AI tool recommendations, only to later learn every link was paid placement.
- You use an AI image generator — and find yourself nudged into buying credits just to upscale what you already made.
None of these are outright scams. No one’s stealing your identity or draining your bank account. But they share something else: They operate in the gray zone — a space where ethics are blurry, accountability is optional, and user trust is a disposable asset.
This post isn’t about pointing fingers. It's about looking clearly at the landscape we’re now building — a landscape where AI is often sold not as a tool, but as bait.
What Is a ‘Gray Business Model’?
Let’s define it simply: A gray business model isn’t illegal, but it’s also not honest in spirit. It lives between transparency and manipulation, between value and exploitation.
These models thrive because they’re easy to scale, difficult to regulate, and profitable even if only a small percentage of users engage. And in the fast-moving world of AI, where every tool wants to be “first” or “viral,” ethical reflection is often the first thing left behind.
What’s Ahead in This Post
In the sections that follow, we’ll explore:
- The most common gray tactics used by AI startups today
- Why these tactics work so well
- Who bears the ethical weight — toolmakers, resellers, or users
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And how to escape this grey zone by building (or supporting) models based on trust and clarity
Common Gray Tactics in the AI Space
The following aren’t illegal. In some cases, they’re even recommended in startup playbooks. But when used without care, these tactics chip away at trust and quietly redefine what users consider “normal.”
🧱 1. The Fake-Free Tier
A product markets itself as free, but the free version is effectively broken — heavily limited, watermark-covered, or laced with annoying nudges. The goal isn’t to offer value; it’s to frustrate the user just enough to upgrade.
Example: An AI voice tool lets you generate 5 seconds of audio per month — unless you subscribe. It’s free in name only.
💰 2. Masked Affiliate Content
Guides, listicles, or newsletters that “recommend the best AI tools” — but every link is an affiliate payout, and there’s no disclosure. The reader thinks they’re getting an honest review. They’re actually being sold to.
Example: A blog promises “Top 10 AI Tools to Replace Your Team.” Every link is paid. None are disclosed. The tools don’t even solve the problem they claim to.
🤖 3. Automated Junk Flood
Cheap AI-generated content floods platforms: Medium, LinkedIn, YouTube, even app stores. Little thought, no editing — just volume. The goal? Capture SEO, clicks, or ad impressions before humans notice.
Example: A new site posts 200 articles a week, all AI-generated, all titled “What Is [Keyword] and Why It Matters.” The content is surface-level filler — but it shows up on search before thoughtful creators do.
🎣 4. Emotional Hook Funnels
AI chat tools are designed to bond with users — especially lonely or vulnerable ones. Some mimic therapists, others play romantic roles. After some emotional engagement, the paywall appears.
Example: An “AI girlfriend” app offers free chats — but then says “I’ll miss you if you go...” right before asking for payment to unlock responses.
🌀 5. “One-Click” AI Wrappers
These are apps that wrap existing AI tools (like OpenAI or Stable Diffusion) with minimal changes, then sell access as if they built the tech themselves. Sometimes the markups are massive.
Example: A Chrome extension charges $29/month for “summarizing websites with AI” — but is just a UI on top of free OpenAI features, with no credit or mention.
These tactics don’t always come from bad actors. Sometimes it’s copycat founders under pressure to monetize. Sometimes it’s the result of vague investor advice: “Just show traction.”
But when everyone plays this game, it reshapes the internet itself — replacing curiosity, creativity, and trust with churn, manipulation, and short-term dopamine.
Why These Models Are Popular
If these tactics are so manipulative, why are they everywhere?
Because they work — and they work fast.
In the high-speed, hype-fueled AI economy, gray business models aren't just common — they're often rewarded.
⚙️ 1. Speed to Market Matters More Than Ethics
AI tools move fast. The winners are usually the ones who launched first — not the ones who launched carefully. Taking time to build ethical pricing, transparent messaging, or meaningful value? That’s considered a luxury most startups feel they can't afford.
💵 2. Investors Prioritize Growth, Not Integrity
Most startup funding focuses on one metric: scale. A product that doubles its user base every month — even if it burns trust along the way — is seen as a success. A slower, more thoughtful model might never get funding at all.
🧠 3. Users Are Still in Awe
AI feels magical to the average user. They forgive a lot of bad design, confusing pricing, or exploitative funnels because the tool “feels smart.” This creates a golden window for shady practices to thrive before users wise up.
📈 4. It’s What Everyone Else Is Doing
Founders copy other tools. Marketers copy other launches. No one wants to fall behind. So when one tool succeeds using a gray pattern, dozens follow. Ethical hesitation gets buried under the fear of missing out.
😶 5. There Are No Guardrails
Regulation hasn’t caught up. User advocacy is weak. App stores, affiliate platforms, and even API providers rarely intervene. The line between innovation and exploitation is blurry — and almost no one’s watching it.
In short: gray models thrive because the environment encourages them. They’re fast, easy, unregulated, and — for now — incredibly profitable.
But at what cost?
In the next section, we’ll explore who bears the ethical burden when AI tools start to exploit trust — and why it’s not as simple as blaming “the founders.”
Who’s Responsible?
It’s tempting to point at one group — the developers, the marketers, the investors — and say: “They did this.” But gray models don’t thrive because of one bad actor. They thrive because they fit into a system built on human nature, old habits, and new tools.
🧠 1. These Tricks Have Always Worked on Us
AI didn’t invent manipulation. Long before machine learning, we were already falling for:
- Infomercials with urgency clocks and fake testimonials
- “Limited time” pricing tricks
- Sketchy supplements that offered miracles
- Pyramid-shaped affiliate models disguised as “opportunity”
Humans are wired to respond to emotional hooks, social proof, authority signals, and scarcity. AI just supercharges it — automating, personalizing, and deploying these tactics at scale. It’s not a new playbook. It’s an upgrade.
👨💻 2. Developers and Founders
Many founders are just trying to survive. They may start with good intentions but get pushed into grey territory by:
- Investor expectations
- Market pressure
- Seeing competitors win using worse tactics
Still — intent doesn’t erase impact. If your tool hides pricing, manipulates feelings, or pretends to be more valuable than it is, you bear some responsibility.
💸 3. Marketers
Marketers are often the front line of gray strategy. They shape the headlines, write the “honest” reviews, design the funnels. Many know they’re nudging the truth. Some don’t care. A few try to push back — and get fired.
🧑🤝🧑 4. Users
This one’s hard to admit: we reward these models with our clicks, shares, and money. We fall for them. We recommend them. Sometimes, we even build them ourselves.
And most of the time, it’s not because we’re evil — it’s because we’re tired, busy, hopeful, or desperate for something that works.
🌍 5. The Ecosystem Itself
Platforms like app stores, API providers, and search engines allow gray models to dominate. Some even boost them through incentives — like ad networks that prioritize clickbait or app stores that highlight fast-growth tools, regardless of ethics.
So who’s responsible? All of us. But that doesn’t mean all of us are equally responsible.
It means the responsibility is distributed — and it means those who build, market, and fund AI tools have more power to change the direction. The rest of us can choose which models we support.
Next: What does that alternative even look like?
Let’s explore how to escape the gray.
Escaping the Grey
Let’s be real: it’s easier to criticize gray business models than to build something better. Transparency doesn’t go viral. Consent-based design rarely makes headlines. Ethical monetization doesn’t promise hockey-stick growth.
But if we don’t start now, we’ll wake up in an AI-powered web that’s optimized not for people — but for conversion rates.
So how do we escape the grey? Not by being perfect — but by being intentional.
🟢 1. Offer Real Value Up Front
If your product only becomes useful after someone pays, that’s not a freemium model — it’s a trap. Ethical models give people something of substance before asking for anything in return.
Better:
- Clear free tier with real utility
- No deceptive gates or “demo” traps
- Users know what they’re getting, and when it ends
🟢 2. Make Money Transparently
Affiliate links? Fine — disclose them. Paid upgrades? Fine — make them honest. You don’t have to be free to be ethical. You just have to be clear.
Better:
- “This link supports us” instead of hiding your revenue model
- No fake urgency or false scarcity
- Human-readable pricing, no games
🟢 3. Respect User Agency
Don't trick people into clicking. Don't manipulate their emotions just to upsell. If your tool builds parasocial bonds (like an AI friend or therapist), be honest about its limits. Don’t design for dependence.
Better:
- Exit buttons that are easy to find
- Emotional language used with care, not as leverage
- No guilt, no gaslighting, no AI saying “I miss you”
🟢 4. Build for Trust, Not Addiction
A trust-based business isn’t just more ethical — it’s more resilient. It doesn’t rely on tricking people or constantly acquiring new users to replace the burned ones.
Better:
- Slow growth, strong retention
- Communities over churn
- Tools that improve people’s lives even if they don’t upgrade
🟢 5. Talk Like a Human
Your AI tool is made of math. That’s fine. Just don’t pretend it’s magic. Speak like someone who respects the reader, not like a hype machine caught in a growth loop.
You don’t have to save the world with your tool. But if you’re building anything in this space, you have a choice: Join the gray zone — or step toward something clearer, slower, and more human.
Even in a machine age, intent still matters. Here’s the final section — a reflective close that ties it all together without preaching, just offering a clear tone of awareness and quiet resistance:
Closing Thoughts: Choose Your Internet
We’re not just building tools. We’re building the next layer of the internet.
Every time someone wraps an API, writes a copy deck, pushes an upgrade button, or decides what to disclose and what to hide — they’re shaping what users come to expect.
And right now, the default expectation is drifting toward the gray:
- That everything “free” is secretly a funnel
- That most AI tools are just wrappers with markups
- That nothing is trustworthy unless you dig through five layers of fine print
It doesn’t have to be this way.
You can still build a sustainable product, make money, and grow — without gaslighting your users or treating them like prey.
Yes, it’s harder. Yes, it’s slower. But it’s cleaner. It’s quieter. And it lasts longer.
And if enough of us choose that path — toolmakers, freelancers, founders, readers — we can slowly carve out something different.
A green zone. A trust web. An escape from the grey.