AI has been moving incredibly fast over the past two years.
We used to think AI was only good for writing filler articles or answering basic trivia. Today, it has evolved to write code, analyze spreadsheets, generate images, summarize live web pages… and frankly, help many users handle over 60% of their actual daily tasks.
Lately, I’ve been stuck on one persistent question: Will the majority of websites be completely replaced by AI in the near future?
Think about tool sites like mortgage calculators, currency converters, unit switchers, robots.txt generators, or llms.txt creators. Historically, users had to open the site, input parameters, click a button, and copy the output. Now, they can just type a prompt to an AI:
“Calculate a 30-year mortgage for me, what’s the monthly payment?”
“Generate a tailored llms.txt file for my website.”
“Write a robots.txt file that allows Google but blocks specific AI scrapers.”
The AI spits the answer straight into their face. If so, why would anyone bother visiting the original website?
Personally, I don’t think this is a simple “yes” or “no” situation. To be more precise: AI will heavily eat into specific use cases, but it won’t kill the underlying value of all websites.
Which Sites Are Most Vulnerable to AI?
In my view, the most replaceable sites are those built entirely around “simple input, simple output.”
- A basic unit converter where you type in meters and get feet.
- A bare-bones mortgage calculator that takes an amount, rate, and term to spit out a monthly fee.
- A text generator where filling out three fields yields a generic, pre-formatted template.
The core utility of these sites is merely wrapping a fixed formula or a stagnant template into a webpage. People used them because they were too lazy to calculate it themselves or didn’t know the exact math. Now that AI instantly understands the intent and shows both the process and the answer, the core reason to visit these standalone pages plummets.
It feels a lot like the early days of smartphones when we all downloaded dedicated flashlight apps. Once the operating system built it natively into the control panel, those apps lost all reason to exist. AI will likely do the same to shallow tool sites.
Why AI Won’t Completely Eradicate Tool Sites
However, the outlook isn’t entirely bleak. AI is powerful, but it suffers from glaring issues: it hallucinates math, misinterprets complex nuances, fabricates non-existent rules, and lacks awareness of hyper-local or real-time policy shifts.
Take the mortgage calculator again. For a quick ballpark figure, AI is fine. But when things get granular—local lending policies, actual tax rates, early repayment penalties, fixed vs. floating comparisons, and true banking criteria—users still prefer a dedicated, transparent, and auditable tool.
Look at an llms.txt generator. Sure, AI can sketch out a text file, but what a user actually needs is answers to an interconnected workflow:
- Which specific AI crawlers should I actually allow or block?
- Are my robots.txt rules properly aligned with my llms.txt file?
- Where exactly do I upload this file?
- How do I configure this on WordPress, Nginx, or Vercel?
- Can I instantly preview, copy, or download the final asset?
- Can I visualize and compare different setups?
This is no longer a simple question-and-answer dynamic; it’s a comprehensive end-to-end workflow. Ultimately, AI will replace “thin tools,” but it will struggle to replace websites offering “human judgment, clear workflows, and tangible validation.”
What the Data Tells Us: Who is in Immediate Danger?
The traffic shift caused by AI is already showing up in the numbers. Recent studies analyzing the impact of Google’s AI Overviews on Wikipedia revealed an approximate 15% drop in daily traffic for affected English pages. Furthermore, separate search tracking indicates that AI Overviews now populate well over half of standard informational search queries.
The writing on the wall is clear: if an AI can fully satisfy a user’s intent directly on the search engine results page, the motivation to click through to the source site vanishes.
The highest-risk categories include:
Put simply: if a user’s query can be fully resolved in a single sentence, the website hosting that answer is in trouble.
Where are the New Opportunities Rising?
It’s not a total wipeout. Many web architectures will actually thrive or find massive new vectors for growth because of the AI landscape.
1. Platforms with Sovereign, Real-Time Data: Live prices, interest rates, evolving regulatory policies, actual inventory, flight schedules, local housing data, or API uptimes. AI systems cannot afford to blindly guess these metrics; they must pull from trusted origins.
2. Complex Multi-Step Workflows: Sites that take a user from validation, safe formatting, downloading, and deployment assistance all the way to post-launch diagnostics. AI can offer tips, but a structured site gets the physical task done.
3. Niche, Authoritative Judgment: Spaces that pivot from explaining “what it is” to clarifying “which option you should execute under specific constraints.” This type of wisdom stems from true operating experience, not just scraping textual data.
4. Communities Built on Human Feedback: AI can compile generalized sentiments, but granular user reviews, project post-mortems, real-world mistakes, and unfiltered change logs hold immense premium value.
This is precisely where independent webmasters still hold a massive competitive advantage.
Shifting Tool Sites from “Single Utilities” to “Workflows”
The old playbook for utility sites was incredibly simple: dedicate one page to one hyper-specific micro-problem. For instance, an “Amount in Words Converter” where you input numbers and get capital text. It was quick, straightforward, and highly effective for classic SEO. Moving forward, however, this model is dangerously exposed. AI can replicate it on the fly with infinite variations.
To survive, modern tool sites must evolve into modular workspaces rather than simple standalone buttons.
Let’s revisit the llms.txt generator concept. If it just formats text, it’s dead on arrival. But what if that tool does the following?
- Structures your site’s absolute fundamentals based on real-time input.
- Helps you map out custom permission rules for explicit AI crawlers.
- Simultaneously produces optimized llms.txt, llms-full.txt, and robots.txt files.
- Generates native deployment copy-paste code snippets for WordPress, Nginx, or Vercel.
- Runs an automated diagnostic on your site’s macro AI-readiness.
- Flags exactly which of your pages require structurally cleaner markup.
- Provides an interface to review, clone, edit, or download the full bundle locally.
Suddenly, you aren’t just running a basic script—you are providing a complete technical workflow. This is exactly the kind of ecosystem I plan to build out and iterate on. These spaces will not diminish as AI grows; their demand will actually skyrocket as the broader web panics over AI scraping, referencing, and semantic search footprinting.
Where is the Next Webmaster Gold Rush?
The modern opportunity isn’t found in inflating your page count. It’s found in aggressively lowering the user’s cognitive load and decision friction. The legacy SEO strategy was: “You search a keyword, I build a page to capture your click.” The new paradigm is: “You bring a tangled problem, I provide the ecosystem to untangle, run, and audit it.”
I see five primary frontiers:
- AI Era Foundational Infrastructure: Standardizers and syntax auditors for llms.txt, robots.txt, deep schema layout, machine-ready sitemaps, customized AI bot policies, and systemic content architecture testing.
- Vertical-Specific Compliance Systems: Moving away from generic AI prompts toward systems that possess deep domain logic—think localized mortgages, specialized tax reporting, insurance comparison, cross-border e-commerce setups, or indie platform technical SEO.
- Verifiable Data Registries: As LLMs answer queries, they depend heavily on provenance and citations. If you maintain highly clean, structurally predictable, and frequently updated reference points, you become a permanent node for AI engine sourcing.
- High-Stakes Decision Support: Areas where AI cannot legally or ethically take responsibility—finances, law, medical procedures, contractual liabilities, or investment strategies. Web spaces can bridge the gap by offering human checklists, structural risk mapping, and direct human expert handoffs.
- AI-Native Optimization Services: Navigating the shift from classic SEO to GEO (Generative Engine Optimization), AEO, and systemic AI-readiness. Site owners desperately want to know: Is my content easily parsable by an LLM? Is my brand equity being accurately synthesized? Are my transactional pages fully clear to machines? This market is exploding.
How We Need to Adapt as Independent Creators
If you want to survive as an independent creator, you can no longer get away with spinning up a basic script alongside a couple of keyword-stuffed articles. We have to recalibrate our standard operations:
First, build complete systems. Don’t just dump a calculated output. Explain the logic behind the number, offer server configuration files, support clean local downloads, and clearly dictate the next sequential step.
Second, champion granular specificity. Ditch generalized theory. Share real use cases, actual project logs, deep performance breakdowns, and transparent mistakes.
Third, prioritize machine readability. Your title layouts, upfront summary boxes, structured semantic data, logical internal links, and files like llms.txt and robots.txt must be flawless.
Fourth, invest in your trust architecture. Pages like About Us, Direct Contacts, Privacy Policies, Terms, and comprehensive FAQs cannot be low-effort generator templates. They prove to both human visitors and programmatic reviewers that your domain is a persistent, legitimate operation.
Fifth, lean into human editorial opinion. Large language models can synthesize answers, but the real premium lies in sharp executive decisions: when to deploy a tool, when to explicitly avoid it, where the hidden pitfalls lie, and exactly how to proceed next.
The Bottom Line
AI isn’t going to smoothly replace the internet across the board. It will ruthlessly kill off websites that are thin, highly repetitive, data-starved, opinionless, and isolated from practical user workflows. Concurrently, it will catalyze a massive wave of new demands: millions of webmasters suddenly need tools to interpret AI, restrict AI, leverage AI, and ensure they are being indexed correctly by AI engines.
The real threat to a creator isn’t that models are getting smarter. The danger is running a site that remains frustratingly shallow—stuck offering a single basic equation, an automated copy-paste template, or a wall of generic text.
The modern web belongs to platforms that control high-integrity content, own verified live data feeds, execute sophisticated operational workflows, or help humans make critical decisions.
If your site only provides basic answers, AI will eventually take your traffic. But if your platform helps people actually get the job done from start to finish, you still have a massive runway ahead.