For nearly two decades, search engine optimization (SEO) dictated how brands achieved visibility online.
Ranking high on Google or Bing meant being found, considered, and chosen based on certain criteria. Marketers built entire playbooks around understanding algorithms, shaping content, and winning the top position on the results page.
That world is changing. The rise of generative AI (GenAI) has introduced a new discovery experience. It is one that doesn’t list websites, but delivers answers and tailored recommendations directly to the consumer.
Where SEO once determined rankings, large language models (LLMs) are now shaping which brands appear in conversations and product suggestions. Some models, like Perplexity.ai, make the buyer journey completely seamless from discovery to purchase.
This isn’t a technical adjustment. It’s a strategic reset.
To stay relevant, marketers must learn how to influence the systems consumers increasingly rely on. LLM optimization, a new approach to impacting search results, is quickly becoming marketing’s next imperative.
To prepare your marketing organization for the move from SEO to LLM optimization, and other challenges facing modern marketers, download IDC’s Strategies for a Changing World: Six Scenarios for Marketing Leaders.
IDC forecasts companies will spend up to five times more on LLM optimization than traditional SEO by 2029. This significant budget reallocation signals a broader move from AI experimentation to complete AI integration.
The momentum is clear. In response to ChatGPT’s debut in late 2022, major technology companies have launched (or are developing) their own customer-facing LLMs. Investment is accelerating as well: IDC projects a 59% compound annual growth rate (CAGR) in GenAI spending between 2023 and 2028.
Consumers are moving just as quickly. Over 45% of people now use GenAI weekly, often for personal research and recommendations. The parallels to the early days of search are striking, but this time, implementation is happening in just a few years, not decades.
For CMOs, this means visibility, strategy, and budget will increasingly hinge on how well the brand is represented within LLM systems.
SEO was built for a search-first internet. Keywords, backlinks, and metadata drove rankings and reach. But the AI experience era is changing search in ways SEO alone cannot address.
Most major engines now feature enhanced search, where AI-generated summaries appear above traditional rankings. Even the best-optimized content is pushed further down the page. And when customers move directly to platforms like ChatGPT or Perplexity, they bypass ranked results entirely.
In this environment, the familiar metrics of SEO lose influence. A page may be perfectly optimized for keywords yet never shape how an AI model interprets or recommends a brand. Representation is increasingly determined by what the model ingests and prioritizes, not by where content appears in a list.
To remain discoverable, marketers must look beyond search engines. The question isn’t how to rank higher, it’s how to be recognized and represented in AI-powered responses.
Generative AI has introduced a new standard for digital discoverability. LLMs don’t rank pages; they synthesize responses and recommend options. That means fewer opportunities for discovery, with higher stakes for inclusion.
This new environment is giving rise to practices like Generative Experience Optimization (GEO). GEO focuses on structuring content so it can be ingested and surfaced by generative engines. Research shows it works: brands that apply GEO practices can see up to a 40% increase in visibility within AI-generated responses.
But GEO is only the beginning. It’s a bridge to the broader discipline of LLM optimization: the ability to shape how models interpret, prioritize, and present brands across conversations, shopping experiences, and enterprise tools.
The growing consumer expectation for personalization makes this transition even more important. Customers now frame queries by values and preferences – for example, asking for sustainable brands, locally sourced products, or companies with strong ESG records.
Meeting these demands requires more than SEO tactics. It requires a full LLM optimization strategy to ensure your brand is consistently represented in the answers customers already trust.
LLM optimization isn’t another channel shift. It’s a new foundation for reach and relevance.
Marketing leaders are under pressure to adapt to the new AI-powered paradigm:
It’s clear: waiting is not an option for marketing leaders. LLM optimization will determine which brands are consistently elevated in the channels where customers are discovering new products and solutions.
As with AI adoption, implementing LLM optimization requires more than experimenting with new tactics It demands a deliberate transition in how marketing organizations approach visibility. IDC has identified three priorities for leaders preparing for this transition:
This is just the starting point. Full transformation will require cross-functional alignment, new success metrics, and a commitment to showing up where decisions begin.
The shift from SEO to LLM optimization marks a new era of discovery where AI determines which brands are visible, trusted, and recommended. For marketing leaders, the risk of inaction is invisibility in the very channels where customers go for answers.
The opportunity is clear. Those who prioritize LLM optimization will shape how their brand is represented in an AI-first world, ensuring they have a voice in the conversations that drive decisions. The future of marketing is no longer just about rankings. It’s about investment, leadership, and earning consumers’ trust.
Dive deeper into how to prepare for the future of LLM optimization with IDC’s Four Disconnects Reshaping Marketing Today and Tomorrow. Explore the strategic frameworks, emerging roles, and high-impact actions that will define success in the LLM era.
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