Google’s New Spam Policy Update Changes the GEO Conversation

The conversation around “how do we get cited in AI answers?” just became more serious.

On May 15, Google updated its search spam policies to clarify that its rules now explicitly apply to generative AI responses within Search, including AI Overviews and AI Mode.

That may sound like a small wording adjustment.

It is not.

Until now, much of the GEO (Generative Engine Optimisation) ecosystem has operated in a relatively undefined space. Agencies, consultants, and growth teams were experimenting with ways to improve visibility inside AI-generated summaries, citations, and recommendations.

Some of those approaches are entirely legitimate.

Others may now carry a clearer enforcement risk.

Google’s updated language suggests that tactics intended to manipulate AI-generated responses, including biased listicles or “recommendation poisoning,” could trigger the same penalties as traditional search spam. These may include lower rankings or removal from search visibility.

For CMOs and boards, this is less about SEO mechanics and more about governance maturity.

GEO Is Entering a Governance Phase

I do not believe this signals the end of GEO.

I do think it signals the end of treating GEO as an ungoverned growth experiment.

There is a meaningful difference between:

• improving discoverability through credible authority signals, and

• attempting to manipulate AI systems to artificially surface content.

That distinction matters far more now.

What Legitimate GEO May Look Like

The sustainable path likely includes:

• clear and structured content

• attributable expertise

• credible third-party citations

• original research and insights

• schema and semantic clarity

• strong editorial standards

• trustworthy first-party data

In practical terms, this is about making content genuinely useful, understandable, and verifiable for both humans and AI systems.

What May Now Be Higher Risk

The tactics that may face greater scrutiny could include:

• AI-generated “Top 10” pages designed mainly for citation capture

• synthetic expert profiles

• low-quality content farms

• citation loops across owned properties

• recommendation manipulation tactics

• scaled AI pages with little evidence of expertise

The important point is not whether every tactic will immediately trigger enforcement.

The important point is that Google has now formally linked AI-generated search experiences to its spam framework.

That changes the risk calculation for enterprises.

Why This Matters Beyond Search Teams

Many organisations still view AI discoverability as a marketing experiment.

It may increasingly need to be treated as part of enterprise reputation management.

If a brand becomes associated with manipulative AI visibility practices, the downstream implications could extend beyond rankings:

• trust erosion

• misinformation amplification

• governance concerns

• legal or compliance review

• reputational scrutiny

This is especially relevant as AI-generated answers become more integrated into customer discovery journeys.

The governance conversation around AI is expanding.

It is no longer limited to internal pilots or model usage policies.

It now includes how organisations attempt to influence external AI systems.

The APAC Context Is Interesting

Across APAC, many organisations have been relatively cautious in their GEO adoption compared with some Western markets.

That slower adoption curve may actually help some brands now.

If AI discovery systems increasingly prioritise authority, trust, and verifiable expertise, then organisations with stronger governance disciplines may have an advantage over those pursuing rapid-volume tactics.

That could favour brands with:

• established regional credibility

• recognised subject matter experts

• consistent customer trust signals

• mature editorial oversight

• stronger governance cultures

In other words, the next phase of AI discoverability may reward operational quality more than aggressive optimisation velocity.

Five Practical Questions CMOs Should Ask Now

1. Do We Fully Understand Our GEO Strategy?

Many leadership teams may not yet know exactly how agencies or internal teams are approaching AI visibility optimisation.

That visibility gap itself creates governance risk.

2. Do Our Content Policies Cover GEO?

Most enterprise AI policies focus on internal AI use.

Few explicitly address:

• AI discoverability tactics

• citation manipulation

• synthetic authority creation

• AI-generated publishing standards

That likely needs updating.

3. Are We Building Real Expertise Signals?

Named experts, attributable authorship, original thinking, and credible citations may become increasingly important in AI-driven discovery environments.

4. Is Brand Trust Being Treated as Infrastructure?

Trust signals are becoming machine-readable inputs.

That changes how organisations should think about reputation building.

5. Are We Optimising for Durable Visibility or Short-Term Exploits?

This may become the defining GEO question over the next 12 to 24 months.

Because AI discovery systems are evolving quickly, policy enforcement frameworks are evolving alongside them.

The Bigger Takeaway

The most important takeaway may not be the policy wording itself.

It may be what the update represents.

Google is effectively acknowledging that AI-generated answers are now important enough to require formal anti-manipulation safeguards.

That signals a broader maturation of the AI discovery ecosystem.

For enterprises, this likely means that AI visibility strategies will increasingly require the same level of governance, accountability, and reputational oversight that is already expected in other parts of digital marketing.

And for many leadership teams, that conversation is only just beginning.