Marketing is entering a phase where AI isn’t just accelerating execution—it’s reshaping how teams operate, how decisions get made, and where humans create the most value. Automation can now handle the middle of the workflow with remarkable speed, but strategy and judgment still rest squarely on human shoulders.  

To explore how marketers can navigate this shift, we spoke with Laura Stevenson, EVP, Data & Marketing Automation at Mod Op about the evolving human–machine dynamic and what mindset changes brands need to make as AI becomes embedded across every part of the marketing ecosystem. 

How is the blend of human creativity and machine intelligence reshaping modern marketing — and what new possibilities does that unlock for brands? 

It’s humans working at a higher strategic altitude. We learned early on that automation isn’t a “set it and forget it” solution — things break, and experiences drift from the original strategic intent if no one’s watching. Humans still need to make the authentic strategic calls that guide AI, not let it run loose. That means human-centric marketing and advertising powered by the speed of machines: working smarter and faster without losing the judgment, meaning, and trust that only people bring. 

What emerging capability across AI, data, or technology do you believe will most reshape the industry over the next 12–18 months? 

Right now, we’re in the phase of AI experimentation, and people are quickly becoming adept at using AI. Over the next 12–18 months, the winners will be the ones with a solid data foundation feeding AI clean inputs — avoiding the “garbage in, garbage out” problem. Data readiness and deployment are paramount to success. And technology and AI will win out when they’re leveraged for use cases that generate revenue, not just productivity metrics — those are quickly becoming table stakes, and increasingly hard to defend for budget. 

What mindset shift will be most important for brands that want to thrive in an AI-accelerated marketing landscape? 

There are actually three key shifts that need to take place for brands to thrive in this new landscape. Marketers need to move their mindset from: 

1. “Campaigns” to “Always on.” Stop thinking in launches and start thinking in always-on, adaptive systems that learn. At Mod Op, we’ve been doing this work for over 10 years using automation — now we’ve built AI into it to stay in front of customers and prospects, personalizing their experiences even more fluidly. 
2. “Adopt AI” to “Engineer the human/machine handoff.” The winners won’t be the ones with the most AI — they’ll be the ones most disciplined about what humans do versus what machines do. 
3. “Productivity” to “Growth.” Stop measuring AI by hours saved; start measuring it by revenue created. 

Where does human judgment matter most as automation becomes more embedded in marketing workflows? 

Human judgment matters most at the two ends of the workflow: the very beginning, and the moments of consequence. 

At the beginning, humans set the strategic intent and the guardrails. Machines optimize relentlessly toward a goal, so a human has to decide which goal — and make sure the optimization doesn’t quietly drift from what the brand actually stands for. At the moments of consequence — brand voice, ethical use of data, whether a message builds trust or erodes it — these are judgment calls with no “optimal” answer a model can calculate. 

The real value is humans owning the intent up front and the high-stakes, brand-defining calls, and letting the machines run the reliable middle. 

What’s one misconception about AI-driven marketing that you wish more brand leaders understood? 

Two things, if you don’t mind: 

1. “AI is a set-it-and-forget-it engine.” The misconception that you can turn it on, walk away, and no longer need budgets for agencies and marketing staff to guide the strategic output. 
2. “AI is the hard part; the data is a detail.” Leaders overvalue the model and undervalue the data foundation when building AI intitatives. In reality, the model is increasingly commoditized — the data is the moat. 

Perfecting The Human–Machine Balance 

As AI moves deeper into workflows and intelligent agents begin taking on meaningful tasks, advantage will shift to brands that build always‑on systems, engineer disciplined human–machine handoffs, and measure AI by the growth it creates—not the hours it saves. In an industry being rebuilt in real time, that discipline is what will separate the leaders from the pack. 

At its core, marketing has always been about knowing your audience. But with the rise of AI, we’re seeing a bigger shift in what’s possible and, more importantly, in what we’re willing to imagine. 

We sat down with Patty Parobek, Senior VP of AI and ML Transformation to talk about what AI actually unlocks for modern marketers, and the answer might surprise you. It’s not faster content or leaner teams but the ability to finally pursue the ideas that always seemed just out of reach — the ambitious, meaningful work that execution pressures never left room for. 

How is the blend of human creativity and machine intelligence reshaping modern marketing — and what new possibilities does that unlock for brands? 

AI has dramatically lowered the cost and effort it takes to bring ideas to life. Tasks that once required days to weeks of production can now happen in minutes, allowing marketers to spend less time creating assets/executing and more time solving real, meaty business problems. Bigger, better and more meaningful ideation towards real results in marketing are being unlocked.  

What does that mean? The real ROI of AI will be in a brand’s ability to wield the technology  successfully too, enabling better decisions, stronger customer experiences, and more meaningful human connections. It goes way beyond “creating more content, faster.” We often start with this question knowing now that technology can solve for anything:  

What have you always wanted to do (for this brand, this customer, this community) that you haven’t had a chance to before?  

You’ll be able to think of hundreds of ways to utilize AI to make that big hairy audacious goal more of a reality, and a near-term one. 

What emerging capability across AI, data, or technology do you believe will most reshape the industry over the next 12–18 months? 

AI agents. Rather than simply generating content or answering questions, AI is beginning to execute work (well) across connected business systems. 

We’re already seeing agents research markets, analyze customer feedback, generate digital twins of audiences, draft campaign strategies, coordinate workflows, code (of course) and interact with enterprise applications. As organizations become more comfortable with governed AI, these systems will evolve from assistants into trusted collaborators and marketing teammates. 

In today’s reality, where nearly every marketer has access to AI, the competitive advantage will come from how well organizations redesign work around humans and intelligent agents working together. It will be incredibly interesting to see what AI-native startups and marketing systems come into play as models become increasingly capable.  

What mindset shift will be most important for brands that want to thrive in an AI-accelerated marketing landscape?  

Everyone needs to know how to use AI to drive innovation. Your role in marketing is no longer about the amount of content or widgets you put out, but how much value you’re creating. Every marketer should be able to answer, “How do I redesign the way I create value?” And contribute to “How do we redesign the way our team creates value?”  

Where does human judgment matter most as automation becomes more embedded in marketing workflows?  

AI can surface insights, generate recommendations, and automate execution, but people remain responsible for defining objectives, interpreting nuance, making ethical decisions, understanding customer needs, motivations, or emotions, and deciding when AI is wrong. 

Marketing has always been about understanding people. AI can recognize patterns in data, but it doesn’t understand context the way humans do. Trust, reputation, and brand perception are still built through human judgment. I don’t anticipate the need for that will lessen, in fact, I expect a greater emphasis on human contextual understanding as use cases become far more complex. 

What’s one misconception about AI‑driven marketing that you wish more brand leaders understood? 

One of the biggest misconceptions I see right now is that AI is treated primarily a cost reduction tool. 

Efficiency matters, and we cannot discredit the importance of starting with productivity to build skills and confidence using AI. However, organizations that focus only on saving time will undoubtedly miss the larger opportunity. AI enables marketers to ask better questions, test more ideas, uncover insights that were previously impossible to find, and deliver more personalized and valuable experiences at scale. This generates more value and innovating to provide added value is where AI creates lasting competitive advantage. 

The Real Opportunity 

The brands that will win in an AI-accelerated world aren’t the ones who automate the most — they’re the ones who ask better questions, take on harder problems, and use technology to get closer to their customers, not further away.  

Efficiency is the entry point, but value creation is the destination.

In the age of AI, long‑trusted marking assumptions are starting to break down. AI is accelerating how information is created, interpreted, and surfaced — while simultaneously making the buyer journey harder to see, measure, or influence directly. In this moment of rapid change, the role of human judgment is becoming more — not less — central to how brands make decisions.  

To explore what this shift means for modern marketers, we sat down with Hannah Woodham, SVP, Media Strategy and Operations at Mod Op to discuss the realities of working in an AI‑accelerated landscape, the capabilities that will matter most in the months ahead, and why the fundamentals of brand are quietly regaining their power. 

How is the blend of human creativity and machine intelligence reshaping modern marketing—and what new possibilities does that unlock for brands? 

The human is the most important part of the equation in the human-machine dynamic. Machine intelligence is an excellent tool for gathering and synthesizing large data sets to help surface possible actionable outcomes, but it is critical to keep a human in the loop to discern, scrutinize, and pressure-test what the technology proposes. The unlock for brands is speed. Marketers can move faster and explore more options than ever before. That speed only creates value when it is anchored to clear priorities. Every recommendation the machine generates should be evaluated against the question of whether it advances the strategy or simply adds to the noise. Brands that get this balance right will be the ones that use AI to amplify human creativity and judgment rather than replace it. 

What emerging capability across AI, data, or technology do you believe will most reshape the industry over the next 12–18 months? 

The most significant shift is the erosion of visibility into the buyer journey as AI search reshapes how people discover, research, and evaluate solutions. This is causing real disruption in how marketers measure their value and demonstrate success. Many of the traditional metrics tied to direct attribution will become less reliable, and marketers will need to find new ways to tell the story of their impact. The capability that will matter most is our ability to measure influence in a world where the path to purchase is no longer linear or fully observable. That means developing approaches that account for brand affinity built early and reinforced often, even when we cannot draw a straight line from touchpoint to conversion. 

What mindset shift will be most important for brands that want to thrive in an AI‑accelerated marketing landscape? 

Marketers need to accept that buyers are increasingly creating their own path to purchase, and brands have less direct influence and visibility in that process. Forrester research continues to confirm that buyers are increasingly turning to AI engines versus traditional touchpoints to guide their decisions.  

The mindset shift required is a return to the fundamentals of brand. We need to invest in thought leadership and content that builds affinity well before a buyer is ever in market. For years, budgets and priorities have skewed toward lower-funnel tactics because the measurement was clean and the attribution was simple. The pendulum has to swing back toward upper and mid-funnel investment.  

Brands that show up consistently, with a clear point of view and valuable content, will be the ones buyers consider when they finally surface. Those that have only optimized the bottom of the funnel will find themselves invisible at the moments that matter most. 

Where does human judgment matter most as automation becomes more embedded in marketing workflows? 

Human judgment is paramount, and we cannot lose sight of the value that critical thinking plays regardless of the technology we deploy. Judgment matters most at the points where the stakes are highest: setting strategy, defining brand voice, interpreting ambiguous signals, and deciding what not to do. Automation is very good at executing within defined parameters, but it cannot tell you whether the parameters themselves are right. It cannot weigh reputational risk, sense cultural nuance, or recognize when a technically optimal recommendation is the wrong choice for the brand. Human marketers also serve as the ethical check on the system, ensuring that what is possible is also appropriate. The teams that will get the most from automation are the ones that are most disciplined about where they insert human review and where they trust the machine to run. 

What’s one misconception about AI‑driven marketing that you wish more brand leaders understood? 

AI is not something you turn on and leave running. It is only as good as the data feeding it. If your data is fragmented, messy, or incomplete, you cannot leverage AI fully, and you will get outputs that look credible but lead you in the wrong direction. Trash in, trash out. Before brand leaders invest in the next layer of AI capability, they need to invest in the foundation: clean, connected, well-governed data. That is the less glamorous work, but it is what separates the organizations that get real value from AI from the ones that end up with expensive tools and disappointing results. 

Where Marketing Goes From Here 

What is clear is that AI isn’t simplifying marketing — it’s raising the stakes. Speed without direction creates noise. Automation without judgment creates risk. And data without governance creates false confidence. The brands that will navigate this new landscape successfully are the ones willing to rebuild their foundations: stronger data discipline, clearer strategic priorities, and a renewed commitment to showing up early in the buyer’s journey. AI can widen the field of possibility, but only human marketers can decide which possibilities are worth pursuing.

EMARKETER recently released its GEO cheat sheet. The infographic offers recommendations on five things to do now to optimize for AI platforms, including adapting your SEO playbook.

EMARKETER’s first tip is to “move deliberately, not desperately” because “GEO best practices are still forming.” What’s the #1 thing marketers who are concerned about AI visibility can do today? 

Stop waiting for the playbook to be finished.  

The brands that are going to win in AI search aren’t the ones who waited for the “definitive GEO guide” to drop. They’re the ones who started treating their content like reference material right now. That means structured answers, clear entity definitions, and pages that can be quoted without context — because that’s exactly how LLMs use them. 

If I had to name one thing: audit your most important pages for answer density. Can a language model extract a clean, accurate answer from each page without reading the whole thing? If not, that’s your first fix. Every page should be able to stand alone as a source. 

The deliberate part is real, though. Don’t chase every AI platform the same way. Understand which systems your audience is actually using to research your category, then optimize for those first. Spread thin and you optimize for nothing. 

EMARKETER’s cheat sheet calls out that “many SEO tactics transfer directly to AI search.” Can you share some examples of where you’ve seen this hold true? 

Quite a bit transfers across GEO and SEO, honestly — but the reason it works is different, and that distinction matters. 

Take structured content. In SEO, we use H2s and H3s to signal hierarchy to Google. In GEO, that same structure helps LLMs chunk your content into discrete, quotable units. Same tactic, different mechanism. Same result: you get cited. 

Schema markup is another one. We’ve been recommending JSON-LD for years from an SEO standpoint — FAQPage, HowTo, Organization. That same structured data is exactly what AI systems rely on to understand what a page is about, who authored it, and whether the source is credible. You’re essentially handing the model a fact sheet. 

E-E-A-T signals — author credentials, first-hand experience, editorial standards — were an SEO priority after Google’s Helpful Content updates. They’re just as relevant for GEO. Models that are trying to surface trustworthy answers are looking for the same signals Google was: who wrote this, are they qualified, does the content reflect real experience? 

The biggest gap is intent coverage. SEO pushed us to go deep on long-tail keywords. GEO pushes you to go deep on conversational questions — the full arc of what someone might ask about your topic, not just the head terms. Same instinct, bigger scope. 

We know that major LLMs pull from community platforms like Reddit, YouTube, and Wikipedia. How should brands be thinking about their presence on those platforms as part of a GEO strategy? 

This is one of the most underrated parts of GEO, and most brands aren’t treating it with nearly enough urgency. 

LLMs are trained on the open web — and the open web heavily weights community-generated content. Reddit threads show up in ChatGPT responses. YouTube transcripts get indexed. Wikipedia is essentially a primary source for entity resolution. If your brand is absent or poorly represented in those spaces, you have a gap that no amount of on-site optimization fixes. 

The practical move here is a presence audit. Search for your brand on Reddit, check if your category conversations even mention you, look at what Wikipedia says (or doesn’t say) about you or your competitors. That’s your baseline. 

From there, it’s not about gaming forums — that approach erodes trust fast. It’s about earning mentions through genuinely useful contributions: thought leadership that practitioners reference, data that journalists cite, explanations clear enough that communities organically link back to your site. Those are the signals that compound over time. 

For our clients, we treat community platform mentions as a GEO factor in their own right. If a brand is invisible on Reddit and YouTube in their category, that’s a real visibility deficit — not a “nice to have” fix. 

EMARKETER notes that “credible, first-party content raises your AI visibility.” How does this align with SEO best practices? Is there a genuine double-dip opportunity here? 

Yes — and this is where GEO and SEO are most aligned. First-party, authoritative content has always been the foundation of sustainable search visibility. GEO just makes the stakes higher. 

In SEO, we talk about topical authority: owning a subject area by publishing comprehensive, interlinked content that demonstrates depth. That architecture — pillar pages, supporting content, internal linking — is exactly what helps LLMs understand that your brand is a credible source on a given topic. The double-dip is real. 

What “first-party” means in GEO goes beyond just publishing on your own domain, though. It means content that contains something no one else has: your proprietary data, your client outcomes, your operational experience, your named experts. That’s what differentiates you as a source from every other brand publishing generic thought leadership on the same keywords. 

The brands I see getting cited in AI answers consistently have three things: original data or frameworks they created themselves, named experts attached to that content, and a track record of publishing that predates the AI search era. That history matters. Models assign more weight to sources that have accumulated consistent, high-quality mentions over time — not just brands that showed up last quarter optimizing for AI.  

So yes — if you’re creating genuinely original, well-structured, expert-attributed content, you’re building equity in both channels simultaneously. That’s probably the most efficient place to put your content investment right now. 

EMARKETER notes: “The AI search landscape will look dramatically different in two years.” What do you predict will be the biggest change between now and how marketers approach GEO in 2028? 

The measurement problem gets solved — and that changes everything. 

Right now, GEO is being treated as a belief system by some and a black box by others. The brands investing in it are doing so on faith and early signals. By 2028, I think we’ll have attribution models that can credibly connect AI-driven brand mentions to pipeline, not just impressions. When that happens, GEO moves from a content team conversation to a revenue conversation — and budgets will follow. 

The second shift I’d bet on: personalization at the query level. The AI search experiences we have today are relatively static. You ask a question, you get an answer. What’s coming is systems that understand your role, your context, your prior queries, and surface sources calibrated to you specifically. That means generic B2B content loses its edge fast. Brands that create genuinely differentiated, audience-specific content — not just repurposed whitepapers — will pull ahead. 

And the third thing: brand entity strength becomes a real competitive moat. Right now, entity optimization is still a gap most brands haven’t closed. Wikidata records incomplete, Knowledge Panel data inconsistent, NAP data scattered. By 2028, the brands that treated entity consolidation seriously will have a structural advantage in how models recognize and cite them. It’s not flashy work, but it’s defensible. 

Any final thoughts?

Start now. Win later. 

The marketers who approach GEO like it’s SEO circa 2012 — early, systematic, and patient — are going to look very prescient in a couple of years. That’s not a prediction about technology. It’s a prediction about discipline. The brands that audit their content today, close their entity gaps this quarter, and earn community mentions before AI attribution is table stakes will have a compounding advantage that latecomers simply can’t buy their way into. GEO rewards consistency and history. The best time to start was six months ago. The second best time is now. 

Interested in more? Check out the GEO Periodic Table: A Framework for Generative AI Optimization and be on the lookout for Mod Op’s new GEO audit, coming soon! 

The Cannes Lions International Festival of Creativity is known as the global advertising and marketing industry’s largest and most prestigious annual awards event, but it’s also a stress test of an industry in flux. What were the biggest trends spotlighted at this year’s Cannes Lions? 

Mod Op’s Chris Harihar spend the week on location, sharing his perspective with PRDaily, MediaPost, and Performance Marketing World. Here’s a few of his takeaways from Cannes 2026:

Trust Shines as the Difference-Maker 

Early in the week, Chris noted “authenticity” as a key theme, calling out that, “the challenge is no longer just reaching people. It’s reaching them in a way that feels credible.”

That desire for authenticity is likely what made influencers and creators a big topic at Cannes – more on that in a moment. The theme also showed through in how brands leveraged partners and platforms during the event. 

Read more on MediaPost: Forget AI, ‘Authenticity’ Is The Talk Of Cannes 

Creators Took Center Stage 

Between shifts in the media landscape and the desire to build trust with customers, it’s no surprise that Cannes has become increasingly creator driven. But, as Chris shared with PR Daily readers, “this year felt like the first where creators and creator partnerships became a dominant focus.” 

Despite creator presence at Cannes, Chris was quick to point out that all creator-brand engagements aren’t created equal: “The relationship between a brand and a creator has to feel ‘real’ and genuine. If it comes across as a cash grab for the creator or an audience rental for the brand, it will fail.” 

Read more on PR Daily: 5 PR takeaways from the Cannes Lions 

Brands are Looking for Agencies that Provide Creativity, Judgement and Expertise – Not Hours 

Cannes conversation included the topic of agencies moving away from more traditional billing structures to more output-based engagements. It’s not a new topic, but one that takes on new context in the age of AI. 

“It’s interesting to think about how agencies can continue to use AI to improve operations and efficiency,” Chris shared in a piece for MediaPost. “At the same time, one theme I’ve heard repeatedly during Cannes is that creative work should remain largely sacrosanct. AI can help optimize creative, drive scale, and adapt content for different audiences, but the creative work itself is still valued because it requires the [human] judgment, creativity, and expertise that great agency work demands.” 

Read more on MediaPost: Takeaways On The Future of Agencies  

Looking for more insights from upcoming events? Connect with Chris Harihar and the team on LinkedIn. 

Note: The following is for informational purposes only and does not constitute legal advice. For guidance specific to your situation, please consult qualified legal counsel.

AI is moving fast. And the law is moving with it. New York’s synthetic performer disclosure requirement, which took effect June 9, 2026, is a prime example of how quickly the regulatory landscape is shifting. It’s the first law of its kind in the country. And it won’t be the last. It’s not just for the lawyers either. For brands, agencies, and content creators, staying up on these changes isn’t just a compliance exercise, it’s becoming part of how good creative work gets made. 

Here’s what you need to know right now.

Who does New York’s synthetic performer law apply to? Would it cover paid content creators?

The law targets anyone who “produces or creates” a commercial advertisement in any medium for a product or service. That’s a wide net. Paid content creators are a gray area for the moment. Platform revenue share alone may not trigger it, but sponsored posts and brand deals almost certainly do. Our rule of thumb: if money is changing hands to promote something, assume it applies.

What is the definition of a synthetic performer?

It’s any digitally created asset, generated by AI or any software algorithm, designed to look like a human performer who isn’t recognizable as a real, identifiable person. Notably, it doesn’t have to be AI-generated to qualify. Traditional VFX stuff counts too. And it’s not just lead talent. Digital extras in the background could be covered as well.

What does this law mean for brands and advertisers using AI-generated performers?

Three things: audit, flag, and disclose. Brands need to inventory any campaigns using synthetic humans and flag it early. For agencies, this is a new gate in production. The disclosure conversation needs to happen at the brief stage, not after the spot is live.

Does the synthetic performer disclosure requirement apply to publishers? What about print and billboards?

Newspapers, magazines, TV networks, streaming platforms, billboard companies are explicitly shielded. The obligation sits with whoever creates the ad, not whoever runs it. And the law covers “any medium,” so yes, print and out-of-home are in scope for advertisers. The only carve-outs are audio-only ads and AI used strictly for language translation.

What’s the penalty for non-compliance with the AI ad disclosure law?

$1,000 for a first violation, $5,000 for each one after that. Per violation. For a campaign running across multiple placements the math gets ugly fast. 

Will other states follow New York’s lead in passing synthetic performer disclosure laws?

Almost certainly. And this is where the speed of change really shows. There’s a wrinkle right now: a federal executive order is pushing for a single national AI standard that would preempt state laws, and that fight is still playing out in the courts. But the direction of travel is clear, and the pace is only picking up. 

Build Once, Scale Everywhere

Our recommendation? Build your disclosure workflow to scale now. The compliance infrastructure you put in place for New York, i.e., how you flag synthetic performers at the brief stage, how you document it, how you communicate it etc., is the same foundation you’ll need when other states follow. And they will – so stay ahead of the curve.

As AI reshapes every corner of marketing, experiential marketing is undergoing one of its most dramatic shifts yet. What once required weeks of concepting, production, and iteration can now happen in hours—opening the door to experiences that are more adaptive, more personal, and more emotionally resonant than ever before.  

To understand what this transformation means for brands, we spoke with Mark Bennett, EVP of Experiential Media at Mod Op who shared how the blend of human creativity and AI is redefining craft, compressing timelines, and turning live environments into living, responsive systems. 

How is the blend of human creativity and machine intelligence reshaping modern marketing—and what new possibilities does that unlock for brands? 

The way I see it from the experiential marketing side, it’s less about replacement and more about compression. What used to take weeks of concepting, production prep, and iteration can now happen in hours. That means we can spend more time thinking, creating, and strategizing while AI handles the visual iterations. We get to focus on the stuff that actually matters: the experience design, the human connection, the physical details, the moments that make people stop and feel something. For brands, that unlocks the ability to personalize at scale without losing the craft. You can build an experience that feels bespoke for thousands of people simultaneously. That’s a level of craft at scale that simply didn’t exist before. 

What emerging capability across AI, data, or technology do you believe will most reshape the industry over the next 12–18 months? 

Real-time personalization in physical environments. We’re getting close to a point where a live event or an in-store activation can respond dynamically to who’s actually in the room, what they’re responding to, what’s landing, what’s not. Combine computer vision, behavioral data, and AI-driven content systems and suddenly the experience is almost alive. That’s going to fundamentally change how we produce and how brands think about live touchpoints. We won’t say “we built this experience” anymore. We’ll say “we built an ongoing, real-time adaptive experience engine” that shifts based on the people, the music, the crowd energy, and the cultural moment. No two experiences will ever be exactly the same. 

What mindset shift will be most important for brands that want to thrive in an AI‑accelerated marketing landscape? 

Stop treating AI like a cost-cutting tool and start treating it like a creative collaborator. The brands that are going to win aren’t the ones using AI to do the same things cheaper. They’re the ones using it to do things that weren’t possible before. That requires a different brief, a different internal culture, and honestly a different relationship with your agency partners. You have to create a culture of experimentation and accept that not everything will work. But that’s always been true in experiential marketing. You prototype, you iterate, you learn. The difference now is you can do all of that in the morning and have a whole new set of human and AI-driven concepts ready for the client by afternoon. 

Where does human judgment matter most as automation becomes more embedded in marketing workflows? 

Human judgment matters most at every stage: the beginning, the middle, and the end. At the start it’s about intent, understanding why we’re doing this, what we want people to feel, and what the brand actually stands for. In the middle it’s about knowing how to massage the inputs, refine the prompts, and push back on the output until it actually feels right. And at the end it’s the final read on whether something is resonant or just technically correct. I’ve seen AI produce work that checks every box and still feels hollow. The people in the room who say “this isn’t it yet” are irreplaceable at every stage. Bottom line, you need human judgment at every step to make the AI sing. 

What’s one misconception about AI‑driven marketing that you wish more brand leaders understood?

AI is not a magic solution. It’s a tool. A genuinely incredible tool, but still just a tool. And like any great tool, it’s only as good as the people using it. If you don’t invest in building the team and the culture that knows how to use it well, it just sits in the toolbox gathering dust. A lot of brands are going to be disappointed because they went in with the wrong expectations. Use it like a search engine and you’ll get search engine results. Train on it, push its boundaries, and you’ll get things you never could have imagined. Good strategy gets sharper with AI behind it, but garbage in is still garbage out, just faster and at greater expense. 

Why This Moment Matters 

The tension ahead isn’t automation versus creativity—it’s whether brands use AI to reduce craft or to elevate it. Mark points to a clear path forward: treat AI as an accelerant, keep humans in the loop at every stage, and build experiences that respond to people in real time. The brands that get this balance right will define the next era of experiential marketing.

Buyers are changing how they discover, compare, and choose. 

For both B2B and B2C brands, AI has become part of that decision path. People are no longer relying only on search results, brand sites, reviews, or sales conversations to shape an opinion. They are asking generative engines for recommendations, comparisons, summaries, and shortcuts. In many cases, that answer is influencing the decision before a brand ever has the chance to speak for itself. 

That shift creates a new kind of visibility challenge. It also creates a real opportunity. 

AI Is Becoming the First Filter 

When someone asks an AI engine – whether it’s ChatGPT, Claude, or Gemini – what to buy, who to consider, or which brand stands out, the response does more than inform. It narrows the field. 

That matters because brand visibility is no longer just about where you rank. It is about whether you are included in the answer at all, how your brand is described, and which signals the engine is using to form that view. If your brand is missing, unclear, or misrepresented, you are starting behind before the real evaluation begins. 

For marketers, that changes the job. It is no longer enough to focus only on discoverability in traditional channels. You also need to understand how AI sees your brand and what it is learning from the broader digital ecosystem around you. 

AI Visibility Without Accuracy Is a Risk 

Being present in AI is only part of the equation. The bigger issue is whether the story being told is the right one. 

AI engines pull from a mix of sources to assemble an answer. That means your positioning, product story, authority, and relevance are often being interpreted from signals spread across your site, earned coverage, third-party mentions, structured content, and the consistency of your brand presence overall. 

When those signals are weak or fragmented, the output can be too. 

A brand can be overlooked. It can be flattened into a generic option. It can be described with outdated language. It can lose ground to competitors that have done a better job of making their value legible to machines. 

The risk is quiet, but the impact is not. 

You Cannot Improve What You Cannot See 

This is where a GEO assessment becomes valuable. 

Generative Engine Optimization, or GEO, is the practice of improving how your brand appears across AI-driven experiences. A strong GEO strategy helps brands understand where they show up, how they are being interpreted, and which gaps are holding them back. 

An assessment creates the baseline. It gives you a clear view of current AI visibility, surfaces where competitors may be gaining advantage, and identifies the areas most likely to improve performance first. 

That is important because AI search visibility is not controlled by one team or one tactic. It is shaped by content quality, technical structure, brand authority, citation strength, and how clearly your digital presence reinforces what your brand stands for. Without a diagnostic view, it is easy to chase symptoms instead of fixing causes. 

The Opportunity Is Bigger Than Search 

The brands that move early have an advantage. 

A GEO assessment is not just about keeping pace with a changing channel. It is about building a clearer, stronger, more resilient presence in the places where decisions are being shaped. It can sharpen how your brand is understood, strengthen the signals that support trust, and help ensure your value is easier for both people and machines to recognize. 

In that sense, this is bigger than optimization. It is a brand visibility strategy for the next phase of digital discovery. 

And the upside is practical. Better AI visibility can lead to better consideration. Better clarity can lead to better conversion. Better alignment can help every downstream marketing and sales effort work harder. 

Now Is the Right Time to Get a Baseline 

Most brands do not need more noise around AI. They need a clearer starting point. 

A GEO assessment helps answer the questions that matter right now: Are we showing up? Are we being represented accurately? Where are we strongest? Where are we vulnerable? What should we fix first? 

Those are strategic questions, not technical ones. And they are becoming more urgent by the day. 

AI is already influencing how brands are discovered and evaluated. The opportunity now is to understand your position before the market moves further ahead. If your brand has not measured its AI visibility yet, now is the time to start. 

Discover where your brand stands in AI search. Contact Kevin Krekeler [email protected] to learn more about our GEO assessment.

Why Customer‑Led Strategy Is The New Marketing Imperative 

The strongest marketing strategies reflect the customer, not the business model. 

Across industries and company sizes, the most common misstep we see — whether from a first-time marketer or a seasoned operator — is building a strategy around the business model instead of the customer. It’s an easy trap: revenue targets, product priorities, and internal narratives feel concrete. Customers, on the other hand, move fast. They shift behaviors, expectations, and attention long before most organizations adjust. 

But in 2026, the brands that win are the ones that reverse the order. They start with the customer, then align their positioning around what those customers value. 

This is the strategic reset many marketing teams need. 

Start with the Customer. Every Time. 

Most marketing leaders will tell you they already start with the customer, and they’re half right. They have the personas. They’ve done the research. But there’s a meaningful difference between having customer data in a slide deck and genuinely building your strategy around customer priorities. The former is a starting ritual. The latter is a discipline that has to run through every decision that follows. 

To start with the customer means asking, before any channel is selected or budget is allocated: where is this customer right now, and what do they need from us at this stage of their journey? The brands getting this right aren’t just mapping touchpoints; they’re aligning business priorities with customer priorities from first awareness all the way through to advocacy. That alignment is where sustainable growth lives. 

Channel Strategy Is a Customer Question, Not a Business One. 

When leadership asks, “where should we be showing up?”, the answer can’t come from internal preference or competitive benchmarking alone. It must come from a clear picture of where your customers are, what they’re doing, and what they’re looking for at each stage of their journey. This becomes especially important as the channel landscape shifts — particularly around AI search and traditional SEO, two channels that are often conflated but serve meaningfully different purposes. SEO points users toward options; it works well when customers are exploring. AI search gives a direct answer, generated uniquely for every query, and the practice of optimizing for it commercially is still being developed across the industry.  

The practical takeaway: traditional SEO is still the right starting point, but it is no longer the whole strategy. You need both running in parallel, and you need visibility into how your brand is showing up in AI-generated answers — not just where you rank. We’ve recently launched a tool to help clients do exactly that. 

If You Only Track One Thing, Track This. 

Once the strategy is in motion, the instinct is to jump straight to revenue metrics: pipeline, conversion rates, ROAS. Those matter, but they’re lagging indicators. They confirm what already happened. If you want to know whether your customer-first strategy is actually working, start with engagement. Not impressions or follower counts, but the signals that show people are paying attention and finding genuine value: time spent with your content, repeat visits, shares, saves, replies, and the quality of inbound conversations. These tell you whether the message is landing with the right customer, in the right place, and that’s the foundation everything else is built on. 

Engagement is the leading indicator that pipeline, conversion, and retention will follow. If it’s not there, no downstream optimization will fix it. If it is, you’ve validated the approach and earned the right to scale.

The Takeaway for CEOs and CMOs 

The brands winning right now are not necessarily the ones with the biggest budgets or the most sophisticated tech stacks. They’re the ones with the clearest picture of their customer, and the discipline to let that picture drive every strategic decision. 

Reverse the order. Start with the customer. Understand where they are, what they need, and how they engage. Build your channel strategy around that understanding. Measure your progress with the signals that tell you whether the foundation is working before you pour resources into scaling it. 

That’s not a new idea. But in a market moving this fast, it’s the one that matters most. 

Ready to build a strategy that starts with your customer? Let’s talk about where your brand stands today — and what it takes to grow from here. 

At Adobe Summit 2026, one thing became clear: AI has moved beyond theory and into practical application, but humans are still in the driver’s seat. 

The Mod Op team returned from Adobe Summit in Las Vegas with a fresh perspective on Adobe’s rapidly evolving ecosystem. Across keynotes, live demos, hands-on sessions, and networking events, we saw how smarter systems, cleaner data, and more connected automation are helping marketers keep pace with rising customer expectations. 

I chatted with Mod Op Director, Marketing and Automation Strategy Tracy Smith, Senior Manger Marketing Automation Grace Han, and Manager, Campaign and Journey, Lindsay Chu to get their biggest takeaways from this year’s Adobe Summit. Here’s what they had to share.  

From AI Hype to AI in Practice 

A major theme throughout Summit was that Adobe is no longer positioning AI as a distant possibility. This year’s focus was on practical, embedded AI tools that support real marketing work now. 

One of the biggest announcements was Adobe CX Enterprise, an end-to-end agentic AI system designed to help manage the customer lifecycle. Closely tied to that was the introduction of CX Coworker, an AI-powered assistant built to support audience segmentation, creative asset development, performance analysis, editing, implementation, and reporting. 

What stood out most was not just the scale of Adobe’s AI vision, but its usability. The focus centered on helping teams move faster across three critical areas: 

• Content supply chain 
• Customer engagement 
• Brand visibility 

The Summit team also noted a stronger emphasis on Adobe Journey Optimizer, Business-to-Business edition (AJO B2B), signaling Adobe’s continued push toward more connected, journey-based orchestration across the B2B marketing ecosystem. It allows designing hyper-personalized journeys with the help of AI virtually in seconds.  

The platform was positioned as a more modern, drag-and-drop environment for omnichannel orchestration, with Marketo continuing to power critical back-end marketing operations. What made AJO B2B especially noteworthy was the amount of attention Adobe gave it, suggesting it will play a larger role in how B2B marketers design and manage connected customer journeys going forward. 

Marketo’s AI Evolution is Built for Efficiency 

For anyone working in marketing operations, some of the most exciting updates came from Marketo. Several stood out as meaningful time-savers for enterprise teams: 

• Interactive webinars with generative AI 
• Image to HTML Converter 
• GenAI for copy, image, and subject line generation 
• Adobe Express integrations for quicker image edits 

These updates matter because they reduce friction in day-to-day execution. Instead of switching between disconnected tools or rebuilding assets from scratch, marketers can increasingly work within a more unified environment. That is a big deal for operational teams. It means less time spent on manual production and more time focused on campaign quality, segmentation, testing, and performance. 

One standout demo showed Marketo’s generative AI transforming a hand-drawn napkin sketch into a functional email template in minutes. The workflow was simple: upload the sketch, and Marketo builds the email structure directly from the drawing. It still requires human refinement, but the technology can take teams from idea to a highly developed prototype from a single image, dramatically accelerating the path from concept to execution. 

The Rise of AI Agents in Marketing Operations 

One of the most talked-about innovations was Marketo’s growing use of AI agents, including: 

• Prebuilt Agents 
• Callable Agents 
• Model Context Protocol (MCP) Server 
• Product Knowledge 

Prebuilt agents offer a range of practical features. They can run quality assurance (QA) on a program, generate a downloadable QA report, and support lead imports by cleaning data, removing duplicates, and normalizing state and country values before records are brought in through the Import Leads agent. The current prebuilt agents are: 

• QA Agent – Ensures program meets quality assurance and generates a QA report 
• Import Leads Agent – Simplifies lead intake by cleaning data, removing duplicates, and normalizing values like country and state 

Other features, such as the Lead Investigation Agent and Create Program Agent, are still in development. Once available, the Lead Investigation Agent will help marketers save time by surfacing activity history and answering questions such as why a lead did not become an MQL. 

Callable Agents can be triggered directly within Smart Campaign workflows to automate tasks such as bot detection and data standardization, normalization, and enrichment. They can also automatically fix inconsistencies (for example, company names, job titles, and country codes) before a record is stored or routed to the CRM. This eliminates the need for manual cleanup or downstream fixes, reducing errors and preventing broken workflows. 

What makes them especially valuable is that they bring AI execution into existing marketing operations processes, helping teams reduce manual work, improve data quality, and move faster without leaving Marketo. 

The  MCP Server was another notable announcement. It is designed to connect Marketo with external AI tools such as ChatGPT, Claude, and others, opening the door for more connected AI workflows. 

The Product Knowledge  feature also impressed the team as an in-product coach that can provide step-by-step guidance backed by Adobe documentation. 

Better Interfaces Support Better Adoption 

Adobe’s evolving user experience, particularly within Marketo, introduced a modernized interface and redesigned email builder that make it easier for teams to create, edit, personalize, and QA assets with greater speed and efficiency. Adobe is listening to user feedback: improvements to HTML access, drag-and-drop editing, reusable fragments, and brand alignment checks suggest a more mature and practical product direction. 

For brands managing complex campaigns across audiences and business units, usability matters. Better interfaces support faster adoption, fewer errors, and more scalable execution. 

Beyond Marketo: Other Standout Summit Demos 

While Marketo updates drew a lot of attention, there are several broader Adobe innovations worth watching. 

• Adobe Firefly + Sharpie: One hands-on session showed how  Adobe Firefly can turn simple drawings into AI-generated content. The demo underscored how quickly rough ideas can become usable visual assets, social content, and design outputs.

• Brand Audit with Adobe: Adobe’s Digital Opportunities Portal can generate a brand performance report based on company name. For teams focused on visibility and digital maturity, this kind of audit functionality offers a useful shortcut to identifying opportunities.
• Adobe Pro and Express: Another standout area was the growing set of AI tools built into Adobe Pro and Adobe Express. Features like PDF spaces, AI Assistant, brand review, audience-specific summaries, and even podcast generation show how Adobe is embedding automation into tools marketers already use every day.
• Adobe Experience League: A practical resource for ongoing learning, especially its AI training content and Acrobat updates.

What This Means for Brands Right Now 

Another important thread from Summit was Adobe’s view that the traditional marketing funnel is no longer as linear as it once was. Customers are increasingly using LLMs and AI tools to research vendors, compare solutions, and narrow consideration sets before ever arriving at a website. That means brands need to think beyond conventional funnel planning and begin preparing content, structure, and discoverability for an AI-shaped buyer journey. 

Adobe’s introduction of  LLM Optimizer  reinforced this shift. As AI-mediated discovery becomes more common, brands will need to think more strategically about how they appear in AI-generated answers and recommendation flows. 

Top 10 Tips for Future Adobe Summit Attendees 

Adobe Summit is always packed with learning opportunities, but it is also a lot to navigate. Here are a few of the most useful takeaways from the Mod Op team for anyone attending in the future: 

• Arrive the day before.  You’ll have time to get your badge, get oriented, and start the week with less stress. 
• Plan your schedule early.  Sessions fill up fast, so use the Summit app as soon as it opens. 
• Block time for meals.  If you don’t schedule lunch, the day will absolutely run away from you. 
• Wear comfy shoes.  This may be the most important tip of all. The attire is business casual and sneakers are completely acceptable. Your feet will thank you. 
• Hydrate constantly.  Conference air, hotel air, desert air — it all adds up. Bring a water bottle and refill whenever you can. There are plenty of refill stations throughout the conference. 
• Take breaks.  You do not need to make every single session. 
• Find the meditation room or recharge spaces. When you’ve spent hours surrounded by thousands of people, a few quiet minutes can make a huge difference. 
• Sit a few seats in. It’s a simple networking trick: people are more likely to sit next to you, which makes it easier to strike up conversations. 
• If you’re getting certified, do it before the conference starts. That way you can spend the event focused on learning, networking, and having fun. 
• Accept that you may get lost in The Venetian. Everyone does. 

And yes, if the therapy dogs make a return, they are absolutely worth a visit. 

Final takeaway 

Adobe Summit 2026 made one thing clear: the future of marketing will be shaped by connected systems, stronger automation, practical AI, and a growing ability to identify data anomalies faster and more accurately. But success will still depend on the people guiding the strategy behind it all. 

That is where Mod Op comes in. As an Adobe partner with Adobe Certified Masters – Marketo Engage Architects on our team, Mod Op helps clients turn marketing automation strategy into scalable, high-performing execution across all major marketing automation platforms and CRMs, including Adobe.