Quick answer: Yes — AI can generate a working website in minutes. What it can’t do on its own is make that website secure, fast, accessible, SEO-ready, and connected to how your business actually runs. AI writes code; it doesn’t supply judgment. That’s the difference between a website that’s written and one that’s done.
Last week, WordCamp US came to my hometown. WordPress professionals from all over the world filled the Phoenix Convention Center for three days, and almost every conversation circled back to the same topic: AI. Not whether to use it — many professionals use it — but what it changes about building websites for a living.
I talk to business owners every month who are asking a fair question: “Why would I hire a web developer when AI can build my website?” After three days of listening to the people who build the web debate their own future, I want to give you the honest answer.
Yes, AI can build a website. And no, that doesn’t mean what you think it means.
AI Can Write the Code. That Was Never the Hard Part.
One session at WordCamp was titled “Staying Relevant as a WordPress Developer in 2026,” and its core message was blunt: the job of web developer is becoming the job of web engineer. Developers don’t get paid to type code anymore. AI can produce routine code faster than a developer can type it manually. The job now is to define the problem and design the solution, then use AI to execute it.
The rule of thumb the speaker gave the room: 80% planning, 20% execution. Nothing goes to AI without thinking first (a lot of thinking, researching, strategizing, and then thinking some more).
That’s the part the AI website demos skip. When you type “build me a website for my plumbing company” into a chatbot, you get the 20% — execution. Nobody did the 80%: who your customers are, what they search for, which pages need to convert, how the site connects to your booking system, what happens to the 800 URLs on your old site that Google already knows about.
The result usually looks finished. Whether it is finished is a different question.
Three Things AI Doesn't Have
The same session laid out what AI still can’t bring to your project. Three things stuck with me.
1. Judgment
AI will always have an answer. The value is in judging the answer — knowing what to ask, what to accept, and what to push back on. That judgment comes from experience AI wasn’t trained on: your legacy database that has to migrate without losing ten years of customer records, your broken redirects quietly bleeding rankings after the last redesign. Those one-of-a-kind problems are where AI lacks the business context, history, and accountability needed to make the decision safely.
2. Specialization
A generated site can look great and still fail everywhere it counts. Performance (does it load fast on a phone?) accessibility (can people using keyboards, screen readers, or other assistive technology use it—and has it been tested against recognized accessibility standards?), legal compliance (privacy policies, cookie consent), and conversion (does the page actually turn visitors into calls?). These are specializations. AI doesn’t volunteer them, because the person prompting doesn’t know to ask. And even if you do ask – all that information has to be reviewed and confirmed by a real person. AI just can’t do that for you.
3. Fundamentals
Good engineering principles didn’t retire when AI arrived. Developers at WordCamp still talked about SOLID and KISS (“Keep it simple, stupid”), because AI-generated code tends toward the opposite: sprawling, overcomplicated, duplicated.
My favorite line of the conference was a review policy: “Two sentences or it is not done.” If your developer can’t explain what was built and why in two sentences, it isn’t done — it’s just written. That’s the standard you’re paying a professional for: not code that exists, but code that’s understood.
Is AI-Generated Code Safe?
Here’s the section I’d ask you to remember, because it’s the one with real money attached.
In its 2025 GenAI Code Security Report, Veracode evaluated more than 100 AI models using security-sensitive coding tasks. Across the tested models, languages, and tasks, only 55% of the generated solutions were secure. In other words, 45% introduced a detectable vulnerability. For cross-site scripting tasks, the average security pass rate was only about 14%. And newer, smarter models did no better than older ones.
Developers have a name for building software by prompting without reading the output: vibe coding. It’s fun for prototypes. For a business website that stores customer information, it’s how you end up with exposed API keys, forms that accept malicious input, and a database anyone can query. The AI won’t warn you, because a security-aware prompt — and a security review of the answer — were never part of the conversation. It may warn you about obvious risks, but it cannot be trusted to identify every vulnerability—or to understand how a seemingly harmless code change affects the rest of your website.
This is the crucial point about developers using AI: the tool is only as safe as the person checking it. Knowing how to prompt for secure code, and how to read the code that comes back, is the skill. Small businesses are already a favorite target for attacks — I’ve written before about what hackers actually want from your website — and an unreviewed AI build leaves the door open.
Here are some additional security risks beyond visibly bad code:
- Exposed passwords, API keys, or database credentials
- Missing authentication and access controls
- Forms that do not safely validate user input
- Outdated or malicious third-party packages
- Plugins or integrations given excessive permissions
- Customer information sent to an AI service without proper handling
- No backups, monitoring, logging, or recovery plan
- Code that works initially but becomes unsafe after an update
Are AI-Built Websites SEO-Friendly?
Mostly out of the box: no. AI builders optimize for “looks done in five minutes,” not for how search engines read a site. AI does not automatically know your audience. It can help analyze customer and search data, but someone still has to supply reliable information, interpret it, and turn it into a strategy. This is what falls into the 80% planning.
The common problems we see when one lands on our desk: bloated code that drags down Core Web Vitals, weak heading structure, missing or generic schema markup, and template text that reads like every other AI-built site in your industry — a real problem now that Google’s own AI Overviews are rewriting how people click.
Can those problems be fixed? Absolutely — that’s search engine optimization work. But “generate it with AI, then pay to rebuild it for Google” is usually the expensive route to the same destination. It’s just better to start the project correctly and avoid problems from the beginning.
How Professional Developers Actually Use AI (We Do, Daily)
I want to be clear: this article isn’t AI skepticism. I came back from WordCamp more convinced than ever that AI is the biggest leverage our industry has been handed. But like anything else – it’s just a tool.
The difference is how it’s used. At OlivSEO we write reusable skills, prompts, agents, and workflows — checklists and automations that encode how we do website design, migrations, and audits — and we reuse them on client work every day. AI executes; an engineer plans, reviews, and signs off. You get the speed of AI and someone accountable for the result.
One speaker put it in a way that stuck with every developer in the room: “If you don’t become a WordPress engineer, that is who will replace you.” And I couldn’t agree more. The bar moved for my profession. It should move for who you hire, too — the question to ask isn’t “do you use AI?” but “show me how.”
So — Hire a Developer or Use AI?
An honest decision:
An AI builder is probably fine if you need a hobby site, a one-page placeholder, or a quick way to test whether an idea deserves a real investment. You may not need to pay an agency for that.
You need an engineer when the website is part of how your business makes money: it must rank, load fast, convert, integrate with your tools, meet accessibility and privacy requirements, survive updates, and not get hacked. That’s not one skill; it’s judgment plus specialization plus maintenance over time. Hiring a developer does not automatically guarantee a secure or successful website. The difference is that a qualified professional should have a repeatable process for identifying risks, testing the work, and taking responsibility for the result.
And a word about money, because that’s usually the real hesitation. An AI-built site isn’t free — it defers its costs. You pay first in your own hours prompting and fixing, then in the rebuild when the site can’t rank, convert, or integrate with your tools, and sometimes in the cleanup after a security incident. When one of those sites lands on a developer’s desk, the fix usually costs more than building it right the first time would have. The honest math isn’t “AI: $0 versus developer: $X.” It’s pay for engineering now, or pay for it later — plus the months the site underperformed in between.
If you’re weighing the two, look at the work itself — the value isn’t the code, it’s everything decided before and after the code.
FAQs
Yes — ChatGPT and tools like it can generate working pages and even full sites. What they produce is a starting point: unreviewed code and structure with no strategy, security review, or SEO behind it. Treat it like a sketch, not a building.
It’s replacing one part of the job: typing code. The judgment, planning, specialization, and accountability parts are becoming more valuable, not less. WordCamp’s phrase for it: web developers are becoming web engineers.
Not without review. Independent testing by Veracode found 45% of the AI code-generation tasks in Veracode’s study produced code with a detectable security vulnerability, and models fail to prevent cross-site scripting in 86% of relevant cases. Security-aware prompting is only the beginning. AI-generated code still needs human review, automated security scanning, functional testing, dependency checks, and controlled deployment by someone who understands how the system works. A responsible AI-assisted workflow includes documenting requirements, reviewing every change, testing on a staging site, scanning for vulnerabilities, checking dependencies, testing accessibility and performance, backing up the existing site, and monitoring the website after launch.
The good ones do, daily — for execution, not for decisions. Ask any developer you’re considering to show you how AI fits their workflow and how they review its output. A confident answer to both is a green flag.
When the site doesn’t carry business risk: hobby projects, placeholders, idea tests. The moment the site handles customer data, revenue, or your reputation, “good enough” needs a human engineer behind it.
To Summarize
AI has changed how good websites are built. It has not eliminated the need for planning, testing, security, accessibility, SEO, or accountability. Used by someone who understands the code and the business behind it, AI can make development faster and more efficient. Used without that judgment, it can make an unfinished website look finished.
If you are comparing an AI builder with professional development, ask what is included beyond generating the pages. That answer will tell you what you are actually buying.
Let's talk about your project
Planning a new website — or holding an AI-built one that isn’t performing? I’ll give you the same honest answer I gave here, applied to your situation.
