Earlier this year, I made the case that the core fundamentals of international SEO still matter. I still believe that. Hreflang, localization, technical excellence, and market-specific content remain essential because search engines and LLMs still need to discover, understand, and connect content with the right audiences.
What has changed is the environment those fundamentals now operate in.
For decades, I watched multinational organizations treat markets as mostly separate digital ecosystems. Content created in one market usually stayed there, and governance focused on managing websites, content, and technical implementation across different regions.
Today, those boundaries are much harder to see.
AI systems can translate content, synthesize information from multiple sources, and increasingly sit between organizations and their customers. Information that once lived inside one market can now shape visibility, recommendations, and customer experiences across many regions.
As those boundaries blur, I see the governance challenge expanding. International SEO is no longer only about managing websites across countries. It now requires organizations to manage the knowledge, expertise, and information that search engines and AI systems use to represent them globally.
Why I believe the governance model must change
Historically, many website and localization decisions were built around operational efficiency. Headquarters created content, technology platforms, and standards for global distribution, while local markets adapted those assets for their own audiences.
That model worked because scale often outweighed the limitations of localization. Consistency improved, costs came down, and organizations could deploy content and technology across dozens of markets far more efficiently than local teams could manage independently.
The challenge now is that AI systems are changing what gets rewarded.
Scale and standardization still matter, but search engines and AI systems increasingly look for signals of expertise, relevance, and geographic specificity. Content that reflects local regulations, market conditions, customer expectations, and industry practices often provides context that translation alone cannot reproduce.
At the same time, AI systems can magnify inconsistency. Contradictory product information, conflicting entity definitions, inaccurate regulatory guidance, and fragmented technical implementations can create confusion across search engines, answer engines, and AI-powered experiences.
That is why I do not think organizations can optimize only for efficiency or only for localization anymore. They need governance models that protect global consistency while giving local markets room to contribute the expertise and context that increasingly drive visibility and trust.
Hreflang solved routing, not understanding
In my previous hreflang article, I argued that hreflang still belongs in an international search strategy, even in the age of AI. I stand by that view.
But hreflang does not decide which market perspective should be prioritized when AI systems synthesize information from multiple sources. It also does not determine which content demonstrates the strongest expertise when AI-generated answers are produced.
As search moves from retrieval toward synthesis, I believe organizations need to think beyond routing users to the right page. They also need to govern the knowledge that powers those answers.
What I would centralize
My simplest rule is this: if an activity creates enterprise risk when it is handled inconsistently, it should usually be governed centrally.
Technical SEO standards are a clear example. Search engines and AI systems do not evaluate websites one market at a time. They evaluate the broader ecosystem of signals an organization provides. CMS governance, structured data standards, entity definitions, AI crawler policies, measurement frameworks, and technical infrastructure all benefit from consistency.
Many international organizations have already faced a version of this problem.
Years ago, before hreflang existed, many global companies used IP detection to route users to the market website they believed was most appropriate. The problem was that Google primarily crawled from U.S.-based IP addresses. When Google tried to access French or Japanese content, it was often redirected to the U.S. site instead.
Individual markets could not solve that on their own because the routing rules affected every market at once. The solution required global governance with local input.
I see AI crawler management creating a very similar challenge today.
Organizations now have to decide which AI systems can access their content and whether those systems can reach the market-specific information they are meant to understand. For companies still relying on geographic routing, market gateways, or IP detection, the governance issue should feel familiar even if the technology is new.
The platforms have changed, but the lesson has not. Some decisions are too interconnected to manage market by market.
What I would localize
If technical infrastructure benefits from consistency, content benefits from expertise.
For years, multinational organizations followed a simple model: create content in the primary market, then translate, adapt, and distribute it globally. That approach delivered real efficiencies. It helped organizations scale content production, maintain brand consistency, and support dozens of markets with shared resources and common technology platforms.
Traditional search engines could lean on signals like hreflang and country targeting to understand regional relevance. AI systems increasingly evaluate the content itself. When multiple markets publish nearly identical versions of the same information, language models may treat them as variations of one source rather than distinct expressions of expertise.
To stand on its own, content increasingly needs market-specific signals such as local regulations, terminology, customer expectations, industry practices, and other forms of geographic specificity.
That is why I believe content ownership, audience research, local authority building, regulatory content, and market expertise should usually stay close to the market. The goal is not localization for its own sake. The goal is to make sure expertise comes from the people closest to the customer and that the content reflects the realities of the market it serves.
The strongest multinational organizations will still use global content frameworks, shared resources, and common technology platforms because those efficiencies remain valuable. The hard part is preserving those efficiencies while giving local markets enough space to contribute expertise that is visible, differentiated, and meaningful.
For years, organizations balanced scale against localization. Increasingly, I think they are balancing scale against representation. The markets that remain visible in AI-driven search experiences will often be the ones that contribute enough unique expertise to stand on their own, rather than simply echo the dominant market version.
What I think needs shared ownership
Governance ultimately comes down to accountability. Whether responsibility sits with a Chief Digital Officer, CMO, enterprise search team, or AI governance group matters less than whether ownership is clear. As search becomes more connected to marketing, technology, product, legal, and AI initiatives, organizations need clear decision rights, escalation paths, and accountability.
The companies that succeed will not necessarily be the ones with the largest SEO teams or the most advanced AI tools. I expect the winners to be the organizations that know exactly how knowledge is created, governed, validated, and represented across markets.
My practical rule for determining ownership
For me, the distinction comes down to risk and expertise.
Responsibilities that create enterprise-wide consequences when implemented inconsistently generally belong closer to headquarters. Activities that depend on local customer knowledge, regulations, language, or market conditions are usually best managed in-market.
Many of the most important decisions need both perspectives, which means they are best handled through shared governance.
10 governance decisions I would review with every global SEO team
The exact structure will vary by organization, but I would encourage most multinational companies to evaluate ownership across these areas.
Typically centralized
1. Technical SEO standards
I would centralize these standards to ensure consistency in crawling, indexing, structured data, and technical implementation across markets.
2. CMS and infrastructure governance
I would govern this centrally to prevent fragmentation while maintaining a common technology foundation.
3. Entity definitions and taxonomies
I would keep these consistent so products, services, brands, and organizational relationships are represented clearly across markets.
4. AI crawler and bot governance
I would establish consistent policies for crawler access, monitoring, verification, geographic routing, and exception management. Governance should usually sit with headquarters, while markets should still be able to request business-specific exceptions.
5. Measurement and reporting frameworks
I would centralize reporting definitions so markets are evaluated with comparable success metrics.
Typically localized
6. Market-specific content
I would keep creation and validation close to local teams so content reflects customer needs, regulations, terminology, market conditions, and the geographic signals that help AI systems recognize local relevance. Global content frameworks can still support that work where appropriate.
7. Audience and search behavior research
I would manage this in-market to capture differences in language, intent, customer expectations, and emerging market trends.
8. Local authority building
I would localize this work because market-specific expertise, trust, partnerships, citations, and visibility cannot be fully manufactured from headquarters.
Typically shared
9. Product and knowledge management
I would treat this as shared ownership because it needs global consistency as well as local validation, market expertise, and regulatory accuracy. Headquarters should define the framework, while markets validate that products, services, and policies reflect local realities.
10. AI visibility and representation
I would also make this shared. Headquarters should establish monitoring and escalation processes, while local teams validate market-specific accuracy and identify emerging issues in how products, services, and brands are represented across AI systems.
The new global SEO mandate
I do not think the objective is to centralize everything or localize everything. The real mandate is to place ownership where decisions can be managed most effectively, so the organization can balance consistency with expertise.
Inspired by this post on Search Engine Land.
