By Kurt Lambert, Senior GEO Strategy Manager, Jasper

From Search to AI Discovery: Building a Content Strategy for the Agentic Era

The bottleneck in marketing has changed, and most content strategies have not caught up.

I have spent 17-plus years in SEO and content strategy, including several years leading AEO and GEO practices at the agency level, before joining Jasper to lead GEO strategy. For most of the last decade, the hard part of content marketing was production: could a team write enough, fast enough, to compete for search rankings? That question is now largely settled, thanks to tools like Claude, ChatGPT, Copilot and Gemini Enterprise. As Forrester put it recently, enterprise AI is everywhere now. The hard part is producing content that represents your brand accurately across every audience, everywhere AI happens to surface you. That is the constraint I see across nearly every marketing team I work with: the question is no longer can we make more content, it is can we represent our brand accurately at scale.

The Old Search Playbook Broke a Year Ago, and Most Teams Haven’t Adjusted

Buyer behavior has already moved past the point most marketing teams have adjusted for. Research from February 2026 found that 94 percent of B2B buyers now use generative AI somewhere in their purchase decisions. Meanwhile, in my own work with clients, I have seen at least a 50 percent decline in organic traffic since the first quarter of 2025 on many sites. Leadership has noticed too: Forrester recently reported that 70 percent of marketers now say AI visibility is a top priority for their CMO or CEO.

There is an upside inside this disruption. Visitors who arrive through a large language model convert between four and a half and 23 times better than typical SEO traffic, according to Semrush and Ahrefs data, because AI has usually already vetted them as further along the decision journey. The risk is just as real: 60 percent of AI answers cite the wrong source or misrepresent brand information entirely. Teams see the resulting drop in performance metrics without seeing the cause. I call that the execution gap.

GEO Is a Trust Problem, Not a Page Optimization Problem

I want to clear up a misconception I run into constantly. GEO is not a checklist applied to individual pages. The first wave of GEO tactics optimized for one metric, getting mentioned by AI as often as possible, and produced a flood of thin, interchangeable content built to be cited rather than to represent the brand well. AI systems are now actively penalizing that behavior, echoing the pattern search engines set with content farms years earlier.

Clarity is the most actionable fix. AI mirrors a brand’s own precision back to it. A vague line like we help businesses grow gives a model nothing concrete to repeat, while naming the exact category, the use case and a single factual differentiator, repeated consistently across core pages, gives AI language it can reuse accurately. This matters most on the homepage, since large language models crawl it at least 20 times more often than other pages.

Speed matters more here than it ever did in SEO. Perplexity refreshes its preferred sources every two to three days; other models hold a source for roughly 45 to 90 days before favoring something fresher. Freshness is now its own ranking force, separate from quality. Winning AI search comes down to volume and governance operating together in a repeatable loop: monitor brand presence across AI platforms, decide which gaps matter, act on the highest priority ones, and measure before repeating the cycle.

Most Teams Aren’t Behind on AI Adoption, They’re Behind on Coordination

Most marketing teams have adopted AI, but few have built a coordinated system around it. The manual version of this work is slow: a human audit can take two to four hours per cycle, competitor research and GEO checks are often skipped, and a manual brief-to-publish cycle can run 12 to 18 months, far too slow given today’s freshness windows. An agentic workflow compresses that substantially, combining automated audits, impact-ranked GEO scoring, bulk refresh work and brand-governed drafting into one system with always on monitoring.

The data shows why coordination matters more than adoption alone. Ninety one percent of marketers are already using AI as a baseline driver, yet only 51 percent of marketing leaders say they can track clear ROI on it, down from 59 percent the year before even as adoption climbed from 63 percent. Adoption went up while confidence in results went down, a sign of disconnected activity rather than a connected system. Fixing that means treating content operations as one system with four linked parts:

Audience: ICP, persona, channel, buying stage, region and language
Triggers: campaigns, sales requests, strategy pivots, product launches, events
Content types: email, landing pages, social, blog posts, sales decks, ad copy
Execution layer: website CMS, social platforms, CRM and related systems

Volume Without Governance Is Just Faster Slop

Many teams assume they must choose between moving fast and staying careful. Forrester frames the trade off directly: the appearance of scale without governance to sustain it, and the appearance of visibility without the discipline to earn it. Buyers are noticing: 63 percent of B2B decision makers say vendor content is too product-focused, and 56 percent worry AI generated content favors persuasion over accuracy.

I think about governance as four layers, and most teams have solved for two and missed the other two entirely. Brand voice and audience context are usually documented well. Product truth, meaning approved specs, claims, pricing and disclaimers, and knowledge, meaning proof points and competitive context, are the layers I see missed almost universally, and they carry the highest stakes: a wrong spec is not a tone problem, it is a compliance problem once AI is repeating it to buyers at scale.

GEO is also not a project with a finish line. Citations are temporary unless a brand keeps earning them. I advise teams to treat any priority page that has gone more than 12 weeks without a substantive refresh, meaning updating at least 20 percent of the content, as overdue and at risk.

Where to Start This Week, Not Someday

The right first move depends on where a team is actually starting from. Early adopters need a starting structure. Teams in mid transformation need workflow integration and a credible path to measurable ROI. AI mature operators need continuous optimization and expanding scale. Regardless of stage, here is where I tell teams to start: audit existing content for accuracy gaps before adding more agents, build governance first in this order, brand voice, audience context, knowledge, then product truth, map the content supply chain as one connected system, and treat the shift as an operational change rather than a software rollout.

Measuring the results is still evolving, and I will be honest that no tool does it with full accuracy today. There is no single authority metric equivalent to domain authority in traditional SEO. The most reliable approach is triangulation: brand mentions, citation frequency and sentiment as leading indicators, connected to referral and direct traffic and ultimately pipeline and revenue. Longer form content, generally 800 to 1,000 words and organized around clear subheaders, tends to perform well in my experience, though it still depends on the topic.

This piece is adapted from a session I gave at a recent Marketing AI Pulse webinar hosted by Spark Novus, a Jasper partner. It was a genuinely fun one to put together with their team, and I appreciated the chance to dig into these questions with the people who showed up to ask them.

Kurt Lambert leads GEO strategy at Jasper with 17-plus years in SEO and content strategy, including several years leading AEO and GEO practices at the agency level. He helps enterprise and mid-market brands understand how AI search is reshaping visibility, while building content strategies that keep them cited, trusted and recommended across Google, LLMs and other AI-driven surfaces.

Ready to Win at GEO for Your Brand?

Whether you're just getting started with generative engine optimization or looking to scale AI visibility across your content, Spark Novus helps marketing teams build the governance, systems, and strategy to show up accurately wherever AI surfaces your brand. Let’s talk.

GEO, or generative engine optimization, is the practice of helping a brand show up accurately in answers from AI systems such as ChatGPT, Perplexity and Gemini, rather than in traditional search rankings. SEO and GEO share a foundation, since both depend on clear site structure, strong user experience and content that demonstrates real expertise. GEO adds new requirements on top of that foundation, including consistent brand clarity, frequent content freshness and governance over what AI is allowed to say about a brand.
Refresh cycles in GEO are shorter than most teams expect. Perplexity can update its preferred sources every two to three days, while other large language models typically hold a source for 45 to 90 days before favoring fresher competing content. A useful internal benchmark is to treat any priority page that has gone more than 12 weeks without a substantive update, meaning at least 20 percent new content, as overdue.
Brand governance is the set of rules and shared source material that keeps AI generated and AI assisted content accurate and on brand as production scales. It operates across four layers: product truth, which covers approved specs, pricing and disclaimers; knowledge, which covers proof points and competitive context; audience context, which covers how messaging should shift by persona; and brand voice, which covers tone and style. Most organizations have brand voice reasonably well documented but have not centralized product truth and knowledge, which creates the highest risk of factual errors at scale.
There is no single tool that measures AI visibility ROI with full accuracy today. The most reliable method is triangulation across several signals: whether a brand is being mentioned and cited in AI answers, whether that translates into referral traffic from AI platforms or an increase in direct and organic traffic, and whether those traffic patterns eventually connect to leads, sales or revenue in the CRM. Tracking these signals together over time reveals directional trends even without a single definitive metric.
No. SEO and GEO overlap substantially rather than functioning as competing strategies. Traditional SEO fundamentals, including clear site structure, strong user experience and well organized content, remain relevant because AI systems value many of the same signals search engines have long prioritized under frameworks such as Google’s experience, expertise, authority and trust model. GEO adds new layers on top of that foundation rather than replacing it.
Early GEO tactics optimized for a single goal, appearing in as many AI answers as possible, which produced large volumes of thin, interchangeable content built to be cited rather than to be useful. AI systems have since adjusted to penalize that pattern, down weighting low quality, high volume content in favor of material that shows original research, named frameworks, expert perspective, or verifiable customer evidence. Mentions were always a proxy for trust, not the goal itself, and that proxy stopped working once it was gamed at scale.
The most effective starting point is an audit of existing content for consistency and accuracy gaps, completed before adding AI agents or scaling content production further. Adding automation on top of an ungoverned content library simply produces inaccuracies faster. Once brand voice, audience context, knowledge and product truth are documented in that order, a team is in a much stronger position to scale content production without also scaling its inconsistencies.

From Search to AI Discovery: Building a Content Strategy for the Agentic Era