Marketers Invest More in GEO

TL;DR

• Generative Engine Optimization (GEO) is now a strategic priority for enterprises.

• AI visibility is the number one goal, but scaling AI-optimized content remains the top challenge.

• Marketing leaders are increasing investments in GEO, focusing on frequent content updates, AI-readable metadata, and brand-owned content.

• Tracking LLM citations, defining AI-focused KPIs, and integrating GEO into existing workflows are essential for capturing AI-driven influence.

Executive Summary

Generative Engine Optimization (GEO) has emerged as a top priority for enterprises, yet many struggle to implement AI-optimized content strategies at scale.

• In 2025, US enterprises allocated 12% of their digital marketing budgets to GEO.(Conductor, The State of AEO/GEO report).
• 56% of marketing leaders reported significant GEO investments, and 94% plan to increase spending in 2026.
• Despite growing investments, AI visibility remains the number one goal, with scaling AI-optimized content cited as the primary challenge.

This report outlines current trends, operational gaps, and actionable recommendations for marketing teams seeking to capture influence in AI-driven discovery channels.

GEO Adoption Trends

Budget Allocation

• Average enterprise spend on GEO in 2025: 12% of digital marketing budgets (Conductor, The State of AEO/GEO report).

• Leadership survey results:

  • 56% report high or significant GEO investments
  • 94% plan to increase spending in 2026

Strategic Importance

• GEO now competes directly with traditional channels such as paid search and SEO.
• Marketers are under pressure to demonstrate ROI and integrate GEO efforts with existing content strategies.

Key Components of GEO

Recent research highlights three critical areas for GEO success:

1. Frequent Content Updates

   • Over 70% of pages cited by ChatGPT were updated within the past 12 months (AirOps).
   • Fresh content improves AI engines’ ability to reference your brand.

2. Clear, AI-Readable Metadata & Descriptions

   • Full-sentence descriptions are more likely to be understood by AI systems.
   • Fragmented sentences or isolated keywords reduce discoverability.

3. Maintaining Brand-Owned Content

   • 86% of generative AI citations originate from content directly controlled or influenced by brands (Yext).
   • Control over content enhances credibility and citation frequency in LLMs.

Operational Challenges

Despite recognition of GEO’s importance, teams face execution and measurement gaps:

• Scaling AI-optimized content: Lack of tools and workflows to efficiently produce AI-readable content at scale.
• Tracking visibility: Difficulty monitoring where and how LLMs or bots crawl and reference brand content.
• Measuring ROI: Uncertainty over the impact of AI-driven discovery versus traditional search metrics.

Recommendations for Marketers

To close the execution gap, organizations should adopt a structured approach:

1. Establish Baseline Visibility

   • Track brand mentions in AI-generated responses using tools like Dageno.
   • Measure frequency, context, and platform of citations across ChatGPT, Google AI Mode, Perplexity, and other LLMs.

2. Pilot AI-Optimized Content Strategies

   • Implement automatic content refreshing for key pages.

   • Structure content for AI readability with:

     • Clear, full-sentence descriptions
     • Concise, answer-first paragraphs
     • Explicit contextual cues

3. Define KPIs for AI Influence

   • Frequency of brand mentions in LLM responses
   • Referral traffic from AI-driven discovery
   • Share of voice in AI-generated answers
   • Compare results against competitors to identify gaps and opportunities

4. Integrate GEO Into Existing Marketing Workflows

   • Coordinate content, PR, and SEO teams to ensure message consistency.
   • Use AI visibility data to inform product marketing, social content, and PR campaigns.

Conclusion

GEO has transitioned from experimental to strategic priority for enterprises.

• Marketing leaders must invest in tools, workflows, and content practices to scale AI visibility effectively.
• By tracking LLM citations and optimizing content for AI systems, brands can capture influence early, ahead of competitors who remain focused solely on traditional search channels.