AI has made SEO teams ambitious about what they can automate. Tasks that previously required engineering support can now be solved with the help of Claude or ChatGPT.
That’s exciting, but it also creates a new problem: thinking you can automate everything. In modern language, that often comes down to one question: Should we build or buy this new tool?
This build-versus-buy dilemma has never been simple, and AI has made it even more complicated. The challenge goes beyond cost. It involves security, maintenance, data access, internal capabilities, workflow fit, and whether a custom solution will remain maintainable, reliable, and useful six months from now.
How AI lowers the barrier to building
AI has lowered the barrier to experimentation. Even without technical knowledge, you can now create a custom GPT, build a workflow, connect data sources, or create an internal AI assistant.
But that doesn’t mean the same person can build and maintain a tool that will remain reliable over the next few years.
In most cases, AI can help SEO teams analyze data, identify patterns, summarize information, and recommend actions. It can save a lot of time, and teams that ignore AI are clearly falling behind.
But, at least for now, AI isn’t doing truly creative work in the same way humans do. It works from existing patterns and predicts likely outputs. That may change in the future.
AI also comes with hidden costs. Internally built tools are often treated as free because the invoice usually doesn’t sit with the SEO team. But that doesn’t mean token usage, API calls, infrastructure, engineering time, security reviews, and maintenance don’t cost money.
We are already seeing this effect. Reuters has described it as “corporate AI sticker shock,” with companies struggling to forecast usage-based AI costs. TechCrunch also reported that Uber introduced AI spending caps after blowing through its annual AI budget in four months.
Today, marketing teams aren’t the heaviest AI users, especially compared with engineering teams. But that can change quickly.
And when usage grows, the bills will grow too. That will naturally make companies ask which AI tools and AI-powered workflows create value and which ones only consume budget.
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Start by defining what you need
Before deciding whether to build or buy, SEO teams need to define what they really need.
Different ways to use AI and automation
Many teams group these solutions together, but they vary significantly in cost, complexity, and maintenance requirements.
- A custom tool: A more complex internal system that usually needs engineering support. It is often more about automation, but it can…
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