Most likely, the person who asked you doesn’t actually know what GEO is. Let’s say it’s a senior board member, so we’re all visualizing the same person, hearing the same intonation. They heard about it at an event, or maybe they saw people squabbling about it on the LinkedIn echo chamber, so now they know just enough to know it’s important, but not enough to speak to it with any level of confidence.

Which puts you in an interesting spot. Because maybe you don’t know either. Maybe you’ve told yourself you’ll dig into it when you have time.

Well, now you’re here. And I’ll guide you through it. After you read this, you’re going to sound super duper smart the next time you’re asked about GEO.

What is GEO?

Definitionally, Generative Engine Optimization (GEO) is the practice of optimizing your content and digital presence so that AI-powered search engines (ChatGPT, Perplexity, Google’s AI Overviews) surface, cite and synthesize your brand when generating responses to user queries.

In human speak, GEO is SEO for AI tools.

It’s possible you’ve heard the term AIO (Artificial Intelligence Optimization), which is the same thing as GEO. Neither are creatively named, but the consensus seems to be that GEO is what we’re going with. As you see in the Google Trends report below, GEO (shown in red) has won the title.

Whereas SEO earns you a position in a ranked list of links, GEO earns you a mention inside the actual answer a person reads within their AI tool of choice.

Instead of a blue underline or a click of a link, your brand is woven into the response as a credible source, or not woven in at all. A growing number of organizations are in the second category and haven’t figured that out yet.

Where Did GEO Come From?

GEO didn’t emerge from a clever agency rebrand or a LinkedIn thought leader in need of content. It emerged from a real and disorienting gap that SEO practitioners began to notice as AI search tools matured and spread.

As ChatGPT, Perplexity, and Google’s generative features began handling a serious volume of informational queries, marketers and SEOs found themselves confronting an uncomfortable reality: strong organic rankings weren’t translating into visibility in AI-generated responses.

A brand could hold a dominant position on page one of Google for a competitive keyword and still be completely absent from the AI answer a prospective customer received about that same category. The usual playbook wasn’t covering the new field.

Researchers at Princeton, Georgia Tech, and IIT Delhi were among the first to formalize what practitioners were already sensing in the field, publishing rigorous academic work that coined the term and began mapping the specific content signals that influence AI citation behavior. The terminology stuck, outlasting the aforementioned AIO, and the practitioner community organized around it, and GEO has been developing as a distinct discipline ever since.

GEO vs. SEO: What’s the Difference?

SEO and GEO share enough surface-level vocabulary that it’s easy to assume they’re the same mannequin, simply sporting different fits. While they’re related disciplines, they possess meaningfully different mechanics, objectives, and success metrics.

SEO optimizes for ranking algorithms that evaluate pages and return an ordered list of results. The user sees that list and decides where to click. GEO optimizes for generative AI systems that read across many sources, synthesize a response, and hand the user an answer. The user reads that answer, often without visiting any website at all. In SEO, winning means a position. In GEO, winning means inclusion in the output.

The practical takeaway is that strategic SEO remains a worthwhile investment and builds real infrastructure that GEO strategy can extend. But organizations treating these disciplines as interchangeable are optimizing for a version of search that handles a shrinking share of the queries that matter most.

Getting back to my hypothetical in the introduction, whoever asked you about GEO is right. You need to have a plan, and that plan cannot be a carbon copy of your SEO strategy.

How Generative Engines Work

Generative AI search tools are trained on vast heaps of text scraped from across the internet. Through that training, they develop a dense web of associations between concepts, entities, claims, and sources. When a user submits a query, the model draws on those learned associations and, increasingly, on live retrieval from current web sources, to synthesize a coherent and authoritative-sounding response. This is why, instead of a list, a user gets an answer.

Take a look at the image above. The same search, one on Google. The other on ChatGPT.

Now here comes the somewhat frustrating part. What determines whose content gets pulled into that answer? We don’t know for certain.

AI tools are less forthcoming with their, for lack of a better phrase, ranking factors than search engines like Google and Yahoo are.

We do know that a combination of impact, answer structure, authority, and citation density is preferred by the tools. However, that knowledge has been gleaned largely by researchers, and not from the engineers of the tools themselves.

This is a marked difference from SEO where Google engineers would regularly provide guidance to SEO practitioners.

Why GEO Matters Right Now

ChatGPT crossed 100 million users faster than any consumer product in recorded history, reaching that milestone in two months. Instagram needed two and a half years. It took Gmail over 5 years. The growth curve of AI search adoption is truly unprecedented. It is, at once, tremendously exciting and horrifying.

A large and growing share of informational queries, the kind that move prospective customers through awareness and into consideration, are now being answered directly by AI tools. Users get a synthesized response and often go no further.

That means a company can maintain a strong, carefully tended organic search presence and still be invisible to a meaningful portion of the audience that matters most to them, simply because their content isn’t being surfaced in AI-generated answers. Scary!

AI tools develop persistent associations between brands and categories over time, as citations reinforce familiarity, which in turn drives further citations. Getting into those patterns early, before a category’s default sources are calcified, is a genuinely time-sensitive advantage – much in the same way that organizations that adopted SEO early still dominate rankings today. 

How to Optimize for GEO

Now you know what GEO is. You have a basic understanding of how it works and how it differs from SEO. You know why it’s important. Now lets get into actionable steps you can take.

1. Start by auditing your existing content for citability

Pull up your highest-value pages and read them with a specific question in mind: does this page make a clear, quotable claim, and is that claim findable within the first two paragraphs? Pages that bury their value proposition under extended setup are the first candidates for revision.

2. Map your content to the questions your audience is actually asking AI tools.

AnswerThePublic, Reddit threads in relevant communities, and direct customer research are all useful here. The goal is to understand the specific, conversational questions your audience is typing into ChatGPT and Perplexity, then build content that answers those questions with genuine depth and specificity.

Another tool is Trakkr, which provides you with some insight into how you’re currently showing up in AI tools. 

3. Establish named, credentialed authorship across your content.

Every substantive piece should carry a named author whose expertise is verifiable and documented externally, on LinkedIn, in published bylines, in speaking appearances, and in press coverage. AI systems factor author authority into citation decisions, and anonymous or generic corporate content loses that signal entirely.

Actively build your off-site footprint. Pitch bylines to credible trade publications and legacy media. Pursue earned media coverage that mentions your organization and your people by name. Seek out podcast appearances, speaking engagements, and partnership content that generate third-party references to your brand. The goal is a diverse, credible web of external mentions that corroborates your own content.

Build an AI presence monitoring practice. Run your most important queries in ChatGPT, Perplexity, and Google AI Overviews on a regular schedule. Track when your brand is cited, when it isn’t, and which competitors are appearing in your place. Without this feedback loop, you have no way to know whether your investments are working.

Who Needs to Care About GEO

Is GEO relevant to your organization? Most agencies will tell you YES! But in reality, it’s not as important to some organizations as it is to others. It all depends on your buyers’ activity.

The single most useful question to ask is: Does my buyer use search, or something that behaves like search, to research before they make a decision? If the answer is yes, GEO deserves serious attention. If the answer is no or sometimes, it should sit lower on the priority list than the people trying to sell you GEO retainers would prefer.

Organizations that should prioritize GEO now:

Professional services firms, B2B software, and SaaS companies must have a GEO plan. Their prospective buyers shop for their solutions in a comparative manner. Being cited as a credible voice in your category before a buyer ever hits your website is a real and meaningful advantage.

Consumer brands in considered-purchase categories (home improvement, financial products, health and wellness, insurance, higher education) also have strong GEO incentives. These are purchases where buyers spend real time gathering information, and AI tools are increasingly where that process starts.

Content-driven media organizations and publishers have an obvious stake. Being cited is, in many ways, the new being read.

Organizations where GEO is a lower priority:

Local service businesses with hyperlocal demand (plumbers, dentists, dry cleaners) operate in a world where Google Maps and direct referrals still dominate discovery. GEO is unlikely to move the needle for them in the near term.

Businesses driven almost entirely by word-of-mouth and relationship sales, certain enterprise deals, niche professional networks, and family-owned distributors have buyer journeys that don’t run through search of any kind. No amount of AI citation optimization changes that.

Commodity e-commerce competing on price and speed is also a weak fit. When the decision is “who has this item cheapest and fastest,” the buyer isn’t consulting an AI for a synthesized answer about brand authority. They’re checking price and shipping timeline.

The underlying logic is consistent: GEO is valuable in direct proportion to how much your buyer’s decision-making process involves open-ended research. The more research-dependent the journey, the higher the return on getting in front of it.

Go Sound Smart

You now know what GEO is, where it came from, how it works, and what to do about it. That is more than most people in your building can say.

When the board member asks again, you won’t be nodding along, hoping the conversation ends. You’ll have something real to say.

Tunheim works with organizations just like yours. If you want to talk through what a GEO strategy looks like for your brand, let’s get into it.

The post What is GEO? Here is Everything You Need to Know appeared first on Tunheim.

A doozie I’ve noticed lately is a persistent feeling of busyness. Everyone feels swamped! Yet many of them report that lead generation has declined. 

If your growth team feels busier than ever but your sales results are sliding, you are not imagining things. You’re probably stuck on the content treadmill. And for many teams, it’s quietly draining time, energy, and focus without delivering meaningful returns.

The Content Treadmill Is Real

Fueled by AI (more on that later), growth teams are producing more content than at any point in recent memory. Blogs. Social posts. Videos. Thought leadership. Newsletters. Sales decks. The calendar is chock-full, and the workload is burdensome. And yet, the impact often feels empty.

The expectation for publishing content is simple: more! The logic is simple: more content creates more opportunities to be seen. 

And with AI propelling your generation, you have no excuse for not pumping out a high-volume of content. But in practice, the treadmill keeps moving regardless of the content’s performance.

How to solve it:
Pause volume-driven publishing and audit what actually gets used by sales or referenced by buyers. If content is not influencing conversations or decisions, it does not need to exist

Why Publishing More Stopped Working

Despite what self-absorbed “leaders” lusting after engagement on LinkedIn may suggest, content itself is not dead. The problem is not that content no longer matters. 

It’s that the formula for organic performance has become increasingly muddled, shaped by shifting algorithms, fragmented distribution, AI-driven discoverability, and a volume of content that makes it harder for any single message to stand out in a meaningful way.

The signals that once helped teams understand what was working are no longer as dependable as they once were. Algorithms change frequently, platforms reward different behaviors, and what performs well in a feed does not always align with what actually influences a buying decision. As a result, visibility has become less predictable, and consistency alone is no longer a reliable indicator of relevance.

At the same time, the sheer volume of content competing for attention has grown dramatically, even as attention spans have declined. 

Nearly every competitor is publishing at a similar pace, often addressing the same topics with similar language and framing – especially if they’re all generating content using these same repetitive tools. In that environment, producing more content does not necessarily create differentiation. In many cases, it simply increases the likelihood of blending in.

How to solve it:
Shift your content strategy from distribution-first to decision-first. Build fewer assets that map directly to buyer questions, objections, and moments of hesitation rather than chasing algorithmic performance.

The Quiet Erosion of Vanity Metrics

For years, metrics such as impressions, engagement, and page views served as proxies for progress. They were easy to track and presented beautifully on reports. Up and to the right!

In 2026, those metrics have lost much of their meaning.

Leaders no longer perk up when they hear about an increase in website traffic. They want to know about leads and net-new growth. 

The problem with vanity metrics is that they measure activity rather than impact. 

The result is a dangerous illusion of momentum. Teams feel productive, but sales conversations do not get easier. Buyers do not move faster, and decisions still stall. As you chase the vanity metrics, you’re just running in place on the content treadmill.

How to solve it:
Redefine success around the outcomes sales can feel. Measure content by usage, influence, and deal acceleration, not by how often it is viewed or liked.

The AI Flood and the Trust Problem

If you haven’t noticed from the four previous mentions, AI is a major contributor to content treadmill exhaustion. Artificial intelligence has dramatically increased the volume of content in the market while simultaneously decreasing content quality. 

AI-generated content is fine and polished and fast but is it good? 

No. It all reads the same. Down to over-indulgence of em dashes.

Buyers are getting better at recognizing generic language and surface-level insights. Content that feels automated, abstract, or interchangeable is easier than ever to ignore. The problem is not accuracy. It is credibility.

The consensus amongst many of my marketing peers is that AI has lowered the bar for content. But I disagree. AI slop has raised the bar. In a sea of AI-generated content, trust and authenticity are becoming precious commodities. 

And they have always been what actually influences buying decisions.

How to solve it:
Use AI to accelerate production, not to replace perspective. Anchor content in real experiences, real examples, and real points of view that only your team can provide.

Why Authenticity Is, and Always Has Been, a Competitive Advantage

An adage I’ve heard literally hundreds of times throughout my career in marketing, is that ‘content is king’. But that’s not true. Authentic content is king.  

Buyers trust specificity. They respond to real experience and anecdotes, not theoretical best practices. They don’t want to know what you’ve done; they want to know how you’ve done it and what the measurable impact was. 

Content rooted in actual sales conversations, real objections, and lived expertise carries weight in ways generic thought leadership does not.

The most effective content in 2026 will not try to sound impressive. It will aim to be useful. It will reflect how sales teams actually talk. It will address the real trade-offs buyers are wrestling with.

How to solve it:
Build content alongside sales, not in isolation. Let real conversations, objections, and deal dynamics shape what you publish and how you say it.

We’ll Help You Off the Treadmill

The answer to content exhaustion is not to stop creating. It is to stop creating content that exists only to satisfy a cadence.

Getting off the treadmill starts with a shift in your intent. Away from publishing for visibility and toward creating for usefulness for your buyers. Away from content designed to perform in feeds and toward content designed to support real buying moments. Away from measuring success by how much is produced and toward measuring whether the work actually helps someone make a decision.

That often means fewer assets, built with more care, grounded in real conversations, and aligned tightly with how sales teams engage buyers day to day. It means choosing clarity over volume and confidence over reach.

In a market saturated with noise, the teams that win will not be the ones who publish the most. They will be the ones who say something real, say it consistently, and say it in a way that actually helps.

And for exhausted teams feeling stuck on the content treadmill, that shift can feel less like doing more and more like finally getting their footing back. 

Need support? Get in touch with us to schedule a time to discuss your current growth approach, and we can talk through how my team can help.

The post Why the Content Treadmill Is Exhausting Your Team and Limiting Lead Generation appeared first on Tunheim.

AI Discoverability: A New Way to Control What AIs Say About You

In the new era of conversational computing, your stakeholders’ first touchpoint is no longer a search engine, it’s an AI. When your investors, customers, policymakers, or future employees ask ChatGPT, Gemini, or Copilot a question about you, what do they hear?

The AI’s best guess… or your verifiable truth?

AI Discoverability Isn’t Just Marketing. It’s Enterprise-Wide Strategy.

Because our methodology is integrated across our entire agency, it delivers value far beyond the marketing department.

• For Crisis: You don’t want an AI “guessing” your side of the story. Our framework ensures your verified truth is the foundational data set.
• For Public Affairs: When a policymaker asks an AI to summarize a complex issue, your nuanced position is what it finds.
• For Management Consulting: The “Conversational Journey” audit reveals what your market truly thinks, providing invaluable data for your next business strategy.

This is why AI Discoverability matters now across your C-suite.

Don’t React to AI. Teach it.

Right now, your brand, reputation, and core value proposition are being defined for you by a black box. It’s time to take control.

The “Platform-First” Trap: Why GEO and AIO Aren’t Enough

Other agencies are now selling “Generative Engine Optimization” (GEO) or “AI Optimization” (AIO). These are tactical, “platform-first” approaches.

They start by auditing what an AI gets wrong and then react to it, scrambling to fix errors with a flurry of PR hits or basic schema recommendations. This is a reactive game of ‘whack-a-mole’ you will never win, because you are always one step behind the algorithm.

Reacting to the bot is a losing strategy. Teaching the bot is the only way to win.

The Tunheim Solution: A Stakeholder-First Approach

We’ve built a different, more powerful methodology. We don’t start with the platform; we start with your stakeholders.

We believe you cannot influence a machine until you deeply understand the human who is using it.

Our AI Discoverability service is a strategic, C-suite process that architects your company’s foundational truth. We’ve mastered this approach by developing a unique, proprietary process: The “Stakeholder-to-Syntax” Pipeline.

1. Stakeholder Intelligence: We begin with the deep, human-centric research that defines our agency. We build robust personas and map the entire conversational journey of your key stakeholders, from buyers and investors to policymakers and potential hires.
2. Concept Optimization: We use that intelligence to build the foundational “Knowledge Graph” for your brand. This is your conceptual truth, your expertise, your executive voices, and your position in the market. It becomes the official “answer key” for the AI.
3. Technical Execution: We translate this strategic blueprint into the native, machine-readable language of AI (Schema.org / JSON-LD) and deploy it directly onto your owned properties. We don’t just “recommend” schema; we architect it.
4. Ecosystem Validation: Finally, we use our full-service media, digital, and public affairs expertise to validate this truth across the entire digital ecosystem—from the high-authority earned media that AIs trust to the critical databases like Wikidata that form their training data.

This Isn’t Our First Algorithm

For 30 years, Tunheim has guided the world’s leading organizations through the algorithms that control information flow.

• We mastered email spam filters to get your message delivered.
• We mastered Google’s search rankings to get your brand seen.
• We mastered social media feeds to get your story told.

Generative AI is just the next, most complex, evolution. We provide Algorithmic Resilience based on a pattern of adaptation we’ve proven for three decades.

Stop chasing the algorithm. It’s time to teach it.
Architect your AI Discoverability framework.

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Brand discovery is undergoing a seismic shift. 

Generative AI and Large Language Models (LLMs) like ChatGPT and Gemini are no longer just futuristic concepts; they are rapidly becoming the go-to sources for answers, recommendations, and even initial brand discovery for millions worldwide. 

The global conversational AI market was projected to expand from $12.24 billion in 2024 to $61.69 billion by 2032. More specifically, the chatbot market, valued at $7.01 billion in 2024, is anticipated to reach $20.81 billion by 2029, growing at a Compound Annual Growth Rate (CAGR) of 24.32%.

A YouGov poll indicated that 56% of Americans use AI tools, with 28% using them at least weekly. Another survey found that 88% of people had engaged in at least one conversation with a chatbot in the past year.

Statista data projects that the number of AI tools users globally will grow from 115.90 million in 2020 to a projected 729.10 million by 2030, with an estimated 378.80 million users by 2025.This adoption is having an effect on search engine referrals, as Axios reports:

Additionally, social media channels have been imposing link penalties for years that suppress website traffic.

Lastly, we are seeing generative AI technology increasingly being integrated into everything, from coding tools to social media platforms.

As a Chief Marketing Officer, if you’re not asking how your brand appears in these AI-driven conversations, you are overlooking a critical factor in your future success.

It’s time to consider an AI Brand Visibility Audit.

This isn’t just another tech trend to monitor; it’s a fundamental change in how audiences will find and form opinions about your organization.

An AI audit is a crucial component of preparing for AI Visibility; it is your first essential step to understanding and navigating this new terrain. It’s about looking under the hood to see how your brand is currently reflected, understood, and communicated by these influential AI systems.

The Silent Storyteller: How AI Is Shaping Your Brand Narrative (Whether You Know It or Not)

Every day, individuals turn to LLMs for quick summaries, complex explanations, product comparisons, and solutions to their problems. The responses they receive are shaping perceptions and influencing decisions, often without them—or you—realizing the full extent of the AI’s influence.

Think about it:

• When someone asks an LLM about the “best solutions for X industry problem,” is your company mentioned?
• If a potential customer queries an AI about your products, is the information accurate, up-to-date, and reflective of your core messaging?
• What sentiment is conveyed when your brand is discussed in AI-generated text?

The challenge is that LLMs can sometimes be a “black box.” Their training data is vast, and the algorithms complex. Without a deliberate effort to investigate, you might be operating in the dark, unaware of how your brand is being portrayed or, critically, if it’s being overlooked entirely. This is where an AI audit becomes indispensable.

AI Visibility Research is a Strategic Imperative for Today’s CMO

For forward-thinking marketing leaders, conducting an AI Audit isn’t just a box-ticking exercise; it’s a strategic imperative with tangible benefits:

1. Safeguard Your Brand Reputation: Your brand identity is meticulously crafted. An AI audit helps ensure that AI platforms are reflecting your story accurately. Are there outdated facts, misinterpretations of your mission, or a negative sentiment skewing how your brand is perceived? Early detection is key.
2. Understand the Evolving Customer Journey: The path to purchase is no longer linear, and AI is introducing new touchpoints. An AI audit provides insights into how your target audience might encounter your brand (or your competitors) during their AI-assisted research and discovery phases. This helps you understand your presence—or absence—at critical decision-making moments.
3. Gain Competitive Intelligence in the AI Arena: How does your brand stack up against competitors when AI is the interrogator? An AI audit can reveal if competitors are being more favorably positioned or more frequently mentioned for relevant industry queries, giving you vital intelligence to refine your strategy.
4. Proactive Risk Management: Misinformation, negative narratives, or even subtle biases in AI-generated content can emerge. An AI audit acts as an early warning system, allowing you to identify and strategize responses to potential reputational threats before they escalate.

Build the Foundation for AI Discoverability: You can’t optimize what you haven’t measured. An AI audit provides the crucial baseline understanding of your current AI visibility. These insights are fundamental to any subsequent efforts to enhance how your brand is discovered, understood, and ultimately recommended by AI systems. This is the core of what AI visibility research aims to achieve.

What Key Insights Does an AI Visibility Audit Deliver?

While the specific methodology of an AI audit can be detailed, the objective is clear: to provide you with a comprehensive picture of your brand’s standing within the AI landscape. Key areas of illumination include:

• Information Accuracy: Verification of core company details, product/service information, leadership, and other factual data as presented by LLMs.
• Brand Messaging & Tone Alignment: Assessment of whether the AI’s portrayal resonates with your official brand voice, values, and key marketing messages.
• Sentiment Analysis: Understanding the overall emotional tone (positive, negative, neutral) associated with your organization in AI-generated content.
• Visibility & Discoverability Gaps: Identifying if, and how, your organization appears for relevant keywords, industry topics, and problem/solution-based queries. Are there significant omissions?
• Competitive Positioning: A snapshot of how your organization is represented in comparison to key competitors within AI responses.

These insights form the bedrock of a robust strategy to enhance your organization’s presence in this emerging AI-driven ecosystem.

From Visibility Audit to Action: The CMO’s Strategic Advantage

The findings from an AI audit are not just interesting data points; they are actionable intelligence that should directly inform your strategic planning. As a CMO, this research empowers you to:

• Refine Content Strategy: Identify content gaps or areas where your existing materials aren’t being effectively surfaced or understood by AI. This can guide the creation of new, AI-friendly content or the optimization of current assets.
• Enhance SEO & Digital Footprint: Remember, LLMs are often trained on the vast expanse of web content. Insights from an AI audit can provide a new lens for your SEO and digital presence strategies.
• Inform PR & Communications: Equip your communications team to address any inaccuracies or negative sentiment discovered, and to proactively shape the narrative.

Future-Proof Your Brand: By understanding and adapting to how AI influences perception and discovery, you position your brand for sustained relevance and growth.

Take Control of Your AI Narrative

The rise of AI in information discovery is undeniable. As a CMO, you have an opportunity to be proactive. An AI audit is more than just a technical check; it’s an investment in your brand’s future, ensuring you are not just a passive subject of AI conversations, but an active participant in shaping your narrative.

Understanding your current AI visibility is the crucial first step. It’s time to ask the critical questions and seek the data that will empower you to navigate the AI revolution with confidence and strategic foresight. Is your organization prepared? Tunheim can help.

The post Is Your Brand Invisible in the Age of AI? appeared first on Tunheim.

In this episode of the Being Understood podcast, Bess Ellenson, Senior Director of Media and Storytelling at Tunheim, joins host David Erickson to explore the evolving landscape of public relations and media strategy.

From foundational messaging and audience targeting to advanced crisis communications and the growing intersection of traditional and digital PR, Bess shares actionable insights that senior communications leaders can immediately apply.

This episode is a must-listen for CMOs, VPs of Communications, and PR Directors navigating the challenges of a transforming media ecosystem, shifting consumer behaviors, and the growing complexity of managing brand narratives in today’s digital-first world. 

The shift to a digital-first news ecosystem is reshaping how your audiences discover, trust, and engage with information. Marketing communications professionals who ignore these seismic changes risk losing relevance, brand credibility, and competitive advantage.

Tunheim’s Digital News Revolution report reveals the latest trends disrupting consumer behavior—from the rise of TikTok news influencers to the resurgence of email newsletters and the impact of AI on audience trust.

Don’t risk falling behind. Understand how your marcomms strategy must evolve to meet your audiences where they are—and where they’re headed.

Get the Report!

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