From GEO Insight to Action: 5 Takeaways from Jasper + BCG X

AI search has moved quickly from an emerging behavior to an influential part of how buyers discover and evaluate brands. According to Boston Consulting Group, 90% of CMOs believe generative AI is already reshaping how consumers discover and evaluate brands. Among consumers already using LLM search, 85% rank it one of their five most influential purchase touchpoints.

For marketers, the challenge now is responding to a fundamental shift in how buyers discover, evaluate, and ultimately choose brands.

This week at our webinar, From Insight to Action: Why Marketers Need Agents to Win AI Search, I had the opportunity to talk about it with Raakhi Agrawal and Robert Derow, Managing Directors and Partners at BCG X and experts on the changing GEO landscape.

Here are five of the most important takeaways.

Download the full webinar here →

1. AI Search Visibility Is a Core Marketing Metric

As LLMs become a universal part of the AI search experience, marketers need a clear view into how their brands perform in those platforms and an active strategy for optimizing it.

That starts with knowing what to measure. Robert pointed to prompting as the place to start:

“We put a ton of emphasis on prompt strategy,” he shared. “We think about products, services, geographies, business units, personas. Really try to build a taxonomy so then you can de-average it.”

From there, marketers can track signals such as brand presence, share of voice, position, sentiment, and citations. But that performance is most useful when marketers can understand what’s driving it rather than reducing everything to one rolled-up number.

“You want to look at it as it pertains to that stage of the customer journey, or that new marketing campaign, or that business unit,” Robert said.

The takeaway: AI search visibility should be treated like any other core marketing performance metric, with a clear baseline and a strategy for improving it over time.

2. GEO Has to Move From Insight to Action

For many marketing teams, monitoring is the first step to GEO. They can see whether their brand appears in AI answers, how often it gets cited, and where competitors may be performing better.

But winning at GEO requires a continuous loop between understanding performance and acting on what you learn.

Raakhi described a scenario she hears often from clients: An LLM makes a claim about a competitor that the brand knows is wrong. Correcting it requires understanding why the model reached that conclusion in the first place.

“Where is the LLM sourcing the information? How can you affect that change?” she said. “That’s a little bit of a daunting task. And then creating the content to go supply it is also daunting.”

That’s the gap marketers have to close. Once a team identifies an opportunity in AI search, it needs to trace that opportunity back to the content or sources influencing the answer and put the right fix into market.

But the work doesn’t end there. Teams need to see whether that action changed how the brand appears in AI search, use what they learn to identify the next opportunity, and keep the cycle moving.

The takeaway: Winning at GEO requires a continuous loop between insight and action, where every change creates new information about what to do next.

3. Agents Make Continuous GEO Possible—with the Right Foundation in Place

Agents offer a way to close the gap between insight and action without creating an entirely new layer of manual work for marketing teams. Instead of leaving marketers to identify each opportunity and then coordinate the work required to address it, agents can take on more of the execution and keep GEO moving all the time.

But most marketing orgs haven’t yet built the foundation to work that way. BCG research found that 96% of CMOs describe their function as undergoing significant AI transformation, yet 42% still use GenAI primarily for individual tasks. Teams still need to take the leap from using AI as a tool to building an operating model where agents can take on more of the work. 

To do that, they need a governance framework that gives agents the right company context, access, and permissions to act within clearly defined boundaries. Human oversight remains part of that framework, particularly as agents take on more responsibility.

“The human employee,” as Raakhi emphasized, “is still ultimately responsible for what goes to market.”

The takeaway: Agents can make continuous GEO practical at scale, but autonomy depends on context and control. Agents need the right brand, product, and audience intelligence, clear permissions and governance, and human oversight to act effectively on a company’s behalf. 

4. GEO Extends Beyond Your Website 

Unlike traditional search, LLMs draw on a wide range of sources to determine which brands appear in their answers and what they say about them, many of which sit beyond brand-owned content.

Robert broke the landscape into four areas brands can influence: on-site technical foundations, on-site content, syndication across external sources, and ecosystem integrations.

Sources are also weighted differently depending on the model. A brand’s visibility in one LLM may be shaped by a totally different mix of sources than in another. But across the board, external sources can have an outsized impact.

As Robert shared, “I’ve been shocked and surprised where a single listicle could really drive share of model inclusion.”

The takeaway: Effective GEO requires marketers to understand which sources are shaping AI answers beyond their own websites and where they have an opportunity to influence them. 

5. GEO Is Building the Foundation for Agentic Commerce 

AI search is still evolving, and one of the next major shifts brands should be preparing for is fully agentic commerce. As consumers increasingly rely on agents to act on their behalf, brands will need to be accessible to those agents in entirely new ways. Laying a solid GEO foundation now is crucial.

“Being discoverable [by AI] today,” Robert emphasized, “will allow you to be transactable tomorrow.”

Getting there will require more than optimizing content for AI visibility. Robert pointed to product feeds, agent-to-agent integrations, and emerging protocols as key parts of the infrastructure that could enable AI agents to transact directly with brands.

His advice? Start building that connective tissue now, even if the immediate business case is still developing.

The takeaway: GEO is laying the groundwork for a future where AI agents can do business directly with your brand.

Turn Insight into Action with the Jasper GEO Agent

As our conversation with BCG X made clear, improving visibility requires an ongoing cycle of understanding how your brand performs in AI search and the factors influencing it, then acting on those insights with intention.

That means GEO has to evolve beyond a way to monitor visibility. It needs to become a continuous operating system for improving it, connecting intelligence directly to execution and using the results to inform what happens next.

The Jasper GEO Agent operationalizes that model by bringing GEO intelligence and execution into one workflow.

It continuously monitors brand performance across leading LLMs, surfaces the highest-impact opportunities, and puts AI agents to work against them using the brand, product, and audience context already built into Jasper.

Learn more here about how the Jasper GEO Agent can power your agent-driven AI search strategy.

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