Everyone seems to have an opinion about AI web development right now. LinkedIn influencers promise it will make custom websites obsolete. Your competitor’s blog says it’s the future of everything. And somewhere in the back of your mind, you’re wondering whether the whole thing is overhyped noise or something you actually need to pay attention to.

If you’re planning a web project in 2024, this confusion is expensive. Misunderstanding what AI can and can’t do leads to unrealistic expectations, poor vendor decisions, and missed opportunities.

We work with AI tools every day. We see what they actually do — and what they don’t. This post cuts through the noise to explain what AI-assisted development looks like today and what it means for your next project.

TL;DR

• AI helps experienced developers work faster and catch more issues — it doesn’t replace them.
• The biggest gains right now are in code generation, automated review, and debugging.
• AI still can’t understand your business goals, design for your users, or make strategic decisions.
• The right question isn’t “should I care about AI?” — it’s “is my development team using it well?”

The gap between AI hype and what’s actually happening

Every agency now claims to be “AI-powered.” Most of the content out there about AI in web development falls into two camps: overly technical articles aimed at developers, or overly hyped marketing with vague promises and no substance.

The data tells a more nuanced story. The Stack Overflow 2023 Developer Survey found that 70% of developers are using or planning to use AI tools in their workflow. But developer trust in AI accuracy is mixed — roughly 43% view it positively, while 31% remain skeptical. This isn’t a settled question, even among the people building with these tools every day.

The honest reality is somewhere in the middle. AI tools are real and genuinely useful. But they aren’t magic, and they aren’t building websites on their own or replacing experienced development teams.

Think of it like the shift from desktop to mobile — it genuinely changed the industry, but the doomsday predictions about it wiping out traditional web development never quite played out the way the headlines suggested.

What AI web development actually looks like in practice

So if AI isn’t building websites autonomously, what is it actually doing?

Think of it like power tools versus hand tools. A carpenter with a nail gun is faster than one with a hammer — but the nail gun doesn’t design the house. AI is the power tool. The developer is still the carpenter, and their experience still determines whether the house stands.

Here’s where AI helps development teams most right now:

• Code generation for repetitive patterns. Boilerplate code, standard components, common configurations — work that used to take hours of copy-paste now takes minutes.
• Automated code review. AI spots bugs, security gaps, and inconsistencies that a tired developer might miss on review number twelve of the day.
• Faster debugging. AI tools analyze error logs and suggest fixes, cutting the time developers spend tracking down problems.
• Testing and documentation support. AI generates test cases and documentation drafts, so the team spends more time building features and less time on paperwork.

This isn’t speculation. A GitHub study found that developers using AI coding assistants completed tasks 55% faster. That’s real, measurable impact — not a marketing claim.

Where AI falls short (and why your team still matters most)

AI is powerful, but it has clear limits. And being honest about those limits is part of being a good partner.

• Understanding your specific business logic. AI doesn’t know your customers, your market, or your competitive advantage. It generates code, not strategy.
• Strategic architecture decisions. Choosing the right technology stack, planning for growth, designing systems that will scale with your business — this takes experience and judgment that AI can’t replicate.
• UX research and user empathy. AI can generate layouts, but it can’t interview your users, observe their behavior, or understand their frustrations. Good design starts with understanding people, not generating pixels.
• Complex security and compliance. Healthcare, finance, and regulated industries require human expertise that AI can’t reliably provide. The stakes are too high for “probably correct.”

The bottom line: the team matters more than the tools. A great development team with AI is powerful. AI without a great team is a liability.

What this means when you’re planning a web project

So what does all of this mean if you’re actually budgeting, scoping, or evaluating agencies for a web project right now? Three things stand out.

Potentially faster timelines — but not free or instant. AI accelerates certain phases of development, which can shorten your overall project timeline. But the discovery, strategy, and design phases still take the same thoughtful time they always have. Those are the phases that determine whether the project actually solves your problem.

Better quality through AI-assisted review. AI-powered code review and automated testing catch more issues earlier in the process. Fewer bugs make it to production. Your users get a better experience, and you spend less time and money on fixes after launch.

The right questions to ask have changed. Instead of asking “does your agency use AI?”, ask “how does your agency use AI to improve my project’s quality and timeline?” The tool matters less than how it’s used.

According to McKinsey’s 2023 research, companies using AI in their development process saw 16-30% improvements in team productivity and time to market. But those gains don’t happen automatically — they come from teams that know how to apply the tools well.

This is the first question in a conversation we think is worth having. Over the coming months, we’ll dig deeper into each of these topics — from the specific tools changing how code gets written to the quality practices that separate good AI-assisted work from reckless shortcuts.

AI isn’t going to build your website for you. But it is changing how the best development teams work, and that change benefits your project in ways that are already measurable. The businesses that will benefit most are the ones asking the right questions now — not “should I care about AI?” but “is my development partner using it well?”

If you’re planning a web project and want a team that uses AI the right way — to build faster, catch more issues, and deliver better results — we’d love to talk about what we can build together. And if you’re working on something more complex, like a custom web application, we do that too.

This is the first post in our series, “AI-Assisted Development: How Modern Agencies Build Better Software.” Next up: a closer look at AI coding assistants and what business owners actually need to know about them.

Frequently asked questions about AI in web development

Will AI replace web developers?

No. AI makes experienced developers more productive — it doesn’t replace the strategic thinking, business understanding, and creative problem-solving they bring. The demand for skilled developers is still growing. What’s changing is the tools they use, not whether they’re needed.

Does using AI in development make my project cheaper?

Not necessarily cheaper, but potentially better value. AI can reduce time spent on repetitive tasks, which may improve timelines. But discovery, strategy, design, and testing still require the same level of expertise. The savings tend to show up in fewer bugs, faster delivery, and less rework — not in a dramatically lower invoice.

How do I know if my development agency is actually using AI well?

Ask specific questions: What AI tools do you use? How do you verify AI-generated code quality? What’s your testing and review process? A good agency will be transparent and able to explain how AI improves their output without hand-waving. We’ll cover this in detail in an upcoming post: “5 Questions to Ask Your Web Agency About AI.”

Is AI-generated code safe and reliable?

It can be — with the right quality controls. AI-generated code needs the same (or stricter) review, testing, and quality assurance as human-written code. The risk isn’t in using AI — it’s in skipping the quality checks because the output “seems right.” We’ll explore why quality assurance matters more now, not less, in a future post in this series.