AI makes custom SEO tools easier, but buy decisions still matter

Custom SEO tools have become easier to build, but easier is not the same as smarter. For agencies and in-house teams, the better question is not whether AI can produce a workflow, but whether that workflow deserves to become a product you own, maintain, secure, and support for clients. Maria Georgieva’s framing is practical: the best decisions come from repeatability, integration complexity, maintenance burden, and client-facing differentiation, not from the lure of a cheaper first draft.

The new build-vs-buy test is really a margin test

The old habit of comparing a SaaS license to a single internal build cost breaks down fast once AI enters the picture. A custom tool may look inexpensive on day one, yet the real bill can show up later in token usage, API calls, infrastructure, engineering time, security reviews, debugging, and ongoing maintenance. If that spend never lands inside the SEO budget, it can create a false sense that the tool is free, when it is actually being paid for somewhere else in the business.

That is why the smartest build-versus-buy decisions now look more like operations planning than software shopping. Gartner has argued that the binary build-or-buy frame is outdated, and a multidimensional build-buy-blend approach makes more sense for enterprise applications. Microsoft has made the same point from a total cost of ownership angle: AI changes the equation across cost, security, scalability, productivity, and management overhead. In SEO, that means an internal workflow is only an advantage if it improves margin without quietly dragging in hidden labor.

Where custom systems earn their keep

The strongest case for building usually comes from narrow, repeatable work that is tightly tied to your own process. Internal reporting, repeatable QA checks, and controlled data pipelines are all examples where custom systems can create real leverage. These are the jobs that benefit from your exact data structure, your preferred review steps, and your own standards for output quality.

That is also where custom tools can become a moat. If a system is deeply connected to proprietary data, has a clear workflow fit, and shortens a high-frequency task that would otherwise soak up team time, it can differentiate the service you deliver. Agencies often win here because they can translate an internal process into a client outcome faster than a generic vendor platform can. The key is to build only when the workflow is stable enough to repeat and specific enough that off-the-shelf software would force too many compromises.

Maria Georgieva’s perspective fits this logic well. She has more than a decade in digital marketing, has specialized in SEO for eight years, and now heads SEO at Payhawk after previously overseeing SEO at Progress Software. That mix matters because it reflects both the agency-style need for efficiency and the in-house reality of owning systems over time.

When buying still makes more sense

Buying remains the better call when the work depends on vendor support, compliance, scale, or predictable updates. Those are not small considerations, especially when the tool sits near client data or touches processes that must keep working even when internal priorities shift. If a platform already handles maintenance, security patching, and product evolution well, outsourcing that burden can protect both margin and attention.

This is also where teams need to think beyond the immediate use case. Forrester has reported that nearly 70% of employees deal with too many applications and context switching at least monthly, which is a reminder that every new custom system can add to tool sprawl. A bespoke workflow that saves five minutes but adds another dashboard, another login, and another support burden can make the team slower, not faster. Buying is often the cleaner answer when the problem is common, the vendor is dependable, and the customization need is modest.

Hybrid setups are often the sweet spot

In practice, many of the best teams will land somewhere between full build and pure buy. Hybrid setups let you keep the parts that matter most, such as logic, data handling, or review steps, while outsourcing the undifferentiated plumbing. That approach can preserve flexibility without forcing the team to act like a software company.

The industry is already moving in that direction. Search Engine Land has recently covered AI agents and AI-powered SEO workflows, including automated audit and reporting processes, and Moz has shown practical setups built from API data and no-code platforms. The pattern is clear: SEO teams are orchestrating systems more often than they are hand-building everything from scratch. That is a healthier model for agencies, because it preserves speed without turning every improvement into a permanent engineering obligation.

Why the search environment makes this decision more urgent

The build-versus-buy question matters even more because search itself is changing. Google says AI Overviews and AI Mode are now part of Search, and its guidance for site owners still centers on foundational SEO, technical structure, and content quality rather than tricks aimed at gaming AI features. Google also warns that using generative AI to create many pages without adding value may run afoul of its spam policy on scaled content abuse. In other words, the algorithmic environment is evolving, but the basics still count.

User behavior is moving too. Pew Research Center found that a majority of Americans say they read AI summaries at the top of search results, and its 2026 AI report says more Americans are using chatbots and AI summaries even as views of AI remain mixed or negative. Search Engine Land has also reported that 37% of consumers begin searches with AI tools rather than traditional search engines, while AI search adoption rises even as trust declines. For agencies, that means the workflows built today need to stay adaptable enough to respond as discovery habits keep shifting.

The practical takeaway is simple: build when the process is repeatable, specialized, and strategically important enough to justify ownership. Buy when the work needs scale, support, and stability that a vendor can provide more efficiently. Use hybrids when you want control without carrying the full engineering load. The agencies that get this right will not just adopt AI faster, they will protect margin while building systems that still make sense six months from now.