If you asked most digital teams to describe how they build and maintain their website or DXP, the answer would involve a development sprint, a design review, a content migration, a UAT phase, and a go-live. That process is fundamentally the same as it was in 2019 — and in a world where AI has changed nearly every other knowledge work process, that's a striking omission.
The Legacy Process Problem
The reason most web development processes haven't changed is partly inertia and partly risk aversion. Digital teams know the current process works — slowly, expensively, but reliably. Changing it requires investment, retraining, and a tolerance for a learning curve that many teams feel they can't afford given existing delivery commitments.
The problem is that this reasoning is circular. The process is slow and expensive precisely because it hasn't been modernised. Teams are too busy delivering with the old process to invest in the process that would give them time back.
What AI-First Web Development Actually Looks Like
Modern, AI-assisted web development doesn't look like science fiction. It looks like:
- Developers using AI coding assistants to generate boilerplate, write tests, and refactor code in real-time, not at the end of a sprint
- Design-to-code pipelines that dramatically reduce the fidelity gap between design intent and built output
- AI-generated test suites that provide coverage that would take weeks to write manually
- Automated accessibility audits that run on every commit, not just before launch
None of these require a wholesale technology replacement. Most can be introduced incrementally, alongside existing tools and processes. The investment required is smaller than most teams expect. The return — in velocity, in quality, and in the capacity it creates for higher-value work — is larger than most leaders realise.
If your web process still looks like 2019, the gap to modern practice is narrower than you think — and the cost of staying where you are is growing.