B2B marketing is facing some of its biggest market disruptors in years. AI is rewriting search, low-quality content is eroding trust, and Europe’s privacy rules are reshaping data strategies. What looks like disruption is actually growth in disguise—new levers, higher standards, smarter plays. This month’s Brief explores how teams in the US, APAC, and Europe are turning these shifts into an advantage.

In this issue:

• AI Slop is Breaking B2B Content Marketing. What's Next?

• AI Max on Google: The SEM Tool Blowing Up Your Tech Stack

• Privacy as Progress: The Shift Away from Third-Party Data is More Than a Technical Adjustment

AI Slop is Breaking B2B Content Marketing. What's Next?

Let's wear our microeconomist hats for a moment.

We know that supply (without the presence of large outside forces) does what supply always does: It chases demand.

Demand shows up, supply supplies. Pretty simple, right?

That’s how it works in content marketing, too. B2B buyers want information, and B2B marketing teams provide it.

But not all supply is equal, and marketing teams know that. So we weave first- and third-party data, experience, and insights gleaned from sales teams to shape the content we create. The result? A sharper, more accurate match between what buyers want and what marketers deliver. That accuracy matters because it creates trust, which can be parlayed into sales potential. If I trust you to explain to me how to solve a problem, chances are I’ll trust you to solve it too. It’s the raison d'être of consulting.

In B2B marketing, AI is great at solving this matching problem. It looks at patterns in the data, tells us what different kinds of buyers are searching for, and informs us where the gaps are. Entire billion-dollar businesses, Google being the obvious one, were built on this idea.

All good so far, right?

But here’s where it gets messy.

The Rise of AI Slop

Supplying the demand for information is a two-part punch. 

First, we have to know what buyers are actually looking for (the matching problem above). Marketers have been using AI tools for years to do this, and now, with generative AI, they can push even further.

The second punch is generating the assets themselves. Here too, generative AI looks promising. It can speed up research; crank out copy, images, videos, and podcasts; and help marketers personalize campaigns at scale. 

Now comes the catch. That same ease has unleashed something else: The rise of AI slop. And it’s distorting supply and demand. AI slop is mass-produced, low-quality, generic AI content, created for volume over value.

Let’s take one of the biggest use cases of AI in marketing: Personalization. According to Nielsen’s 2025 Annual Marketing Report, 62% of marketers in Asia Pacific already use AI for campaign personalization and optimization. That’s well above the 50% in Europe, and a notch higher than the 60% in North America.

Personalization can take a lot of forms. Recommendation engines powered by AI. Chatbots programmed to deliver tailored responses. And generative tools that spin up copy, visuals, or webpages unique to each user.

That last one is where AI slop is starting to show up fast. Today, 34% of B2B marketers use generative AI to research customers and personalize content such as emails, says Adobe. But many are doing it badly. Here’s how one senior B2B marketer in APAC reacted after encountering it firsthand. (TL;DR: Meera Guthi, a marketing and content strategist at NTT DATA, received a ‘personalized’ email that used AI to scrape her profile to tailor a message.)

Evidence of sloppy AI personalization isn’t just anecdotal. It’s starting to show up in the data. According to Gartner, 53% of B2B buyers say personalization “did more harm than good during their latest buying journey”. 

In APAC, the costs of AI slop can sting even more. According to Forrester, 72% of business buyers in the region are millennials or from Gen Z, and they have higher expectations for seamless personalization.

From Slop to Flop

It’s easy to dismiss AI slop as a teething problem. But those teeth bite. And they are starting to leave marks. Here are some of the ways AI slop hurts:

• Trust is eroded: A flood of low-quality content makes most buyers skeptical of most content, even the good stuff.

• Attention becomes more expensive: More skepticism leads to buyers raising the bar. Which means good marketers must work even harder to cut through the noise.

• Acquisition costs go up: As the cost of attention rises, marketers must pay more (ads, sponsorships, etc.) to be heard.

• Sales are impacted: The buyers Gartner surveyed said they were 3.2 times more likely to regret their purchase, and 44% were less likely to buy from that brand again.

A New Equilibrium. And Some Guidance

This brings us to the big question: If slop (which isn’t going away) breaks the old model, what comes next? One way to answer that is with economics. AI slop isn’t just noise; it’s a structural force that distorts supply and demand. And when markets get distorted, they reorganize. Economic modeling gives us three possible futures.

Of these, the K-shaped model is the most likely. Why? Because it’s how disruption often plays out. For B2B marketers in APAC, that means the critical question isn’t whether AI slop will reshape the market, but where we want to end up on the K.

Smart B2B marketing teams know they need to climb the upper branch of the K. Slop won’t earn the trust it takes to sell complex, high-cost solutions, especially in Asia. The “how” is more complicated because it’s still taking shape. In the meantime, leaders are doubling down on first principles: Factual, well-structured, relevant writing that leans on AI for efficiency. The full playbook is still being written. Watch this space.

AI Max on Google: The SEM Tool Blowing Up Your Tech Stack

AI Overviews are rewriting the SERP. What used to be a clean list of ads and links is now a dense, often chaotic block of generative answers. Ads appear above, below, and—surprise!—inside the Overview. Now imagine… your brand is nowhere to be seen. Yikes. 

Thanks to AI Overviews and the rise of zero-click search, that nightmare is becoming routine. Across our client base, we’re seeing the same challenges emerge: impressions up, clicks down, and visibility harder to earn and easier to lose.

At ROI·DNA, we’ve already built a full-funnel, AI-optimized strategy across SEM, SEO, and generative engine optimization, or GEO (yes, that’s a thing now). But staying ahead means staying curious, especially when Google rolls out something new.  

Enter AI Max: Google’s latest SEM beta designed to get your ads inside AI Overviews and the chat-style AI Mode. Is it a silver bullet? No. Your core SEM strategy—solid keywords that align with assets and landing pages, and smart bidding strategies—is still doing the heavy lifting. However, zero-click behavior is accelerating, with click-through rates falling by up to 30% in some categories, including B2B software (Bain & Company). Google is clearly positioning AI Max as its newest ad format strategy to counter the issue. 

The Hype vs. Reality of AI Max

Google is framing AI Max as the next evolution of paid search—smarter, more contextual, more “in tune” with how people search today. But let’s not forget: Performance Max was pitched as the same kind of revolution, and many marketers (us included) are still fighting its lack of transparency and quality control. 

While Google claims AI Max can deliver up to 14% more conversions at similar CPA—or 27% gains for exact/phrase-heavy campaigns, these claims are very “results not typical.” Google’s betas often come with performance volatility, including irrelevant traffic, lower conversion quality, and a general loss of control without careful oversight. 

So, is it all hype or worth testing? Let’s break it down.

How AI Overviews Flip the Script for B2B SEM

AI Overviews shift the goalposts in two critical ways:

1. Search isn’t just SERPs anymore. Research happens inside AI-generated summaries, not just in the list of links below. If your SEM strategy doesn’t win there, you risk vanishing from the buyer journey altogether.
   

2. Answers now act like solutions. AI Overviews favor content that solves a problem. Your ads can’t feel bolted on—they need to position your brand as part of the answer.

AI Overviews are far from perfect. They can misinterpret intent, cite thin sources, miss obvious brands, and straight up get things wrong. Lest we forget, Google’s favorite caveat is, “AI responses may include mistakes.” But there is no denying, if you can land inside them, your visibility jumps to the front of the line, and you start shaping how your audience thinks before they even reach your site.

So What Does AI Max Actually Do?

AI Max doesn’t replace your SEM strategy, it layers on top of it. Instead of relying on rigid keywords, it “listens” to user queries and Google’s own AI summaries, then decides when (and where) to drop your ad in.

Here’s the stripped-down version of what it offers—and where we see cracks:

• Intent-based matching. Looks beyond keywords to query phrasing and AI context. But early testing shows relevancy gaps, especially with competitor terms Google interprets as “similar.”
  

• Dynamic ad copy. Auto-tests multiple headlines and descriptions. That’s great for scale, but it also means losing some control of messaging.
  

• Flexible landing pages. Google decides the “best” spot on your site for the click. Guardrails like URL inclusions are critical, or you risk traffic bleeding into irrelevant or non-localized pages.
  

• Some control, not full control. You can still manage negatives, assets, and exclusions. But don’t confuse that with the precision of traditional campaigns.

Bottom line: to make it really work, you need to plug in the data that matters most. 

A Little Pilot Goes a Long Way

Before fully committing to any beta or folding it into our standard playbook, we look for performance signals that are both scalable and repeatable for our clients — things like clear conversion lift, transparency, consistency in controls, and reliable benchmarks. That said, we have a beta testing playbook for AI Max to help get this rolling.

Our Playbook:

1. Control the parameters. Start small, test a single campaign or product line to understand AI Max’s performance without overcommitting budget or introducing potential performance dips to your broader strategy. Evaluate the impact before you scale up. 
   

2. Audit key settings. Don’t just rely on the out-of-the-box setup. There are key campaign-level settings that need a closer look, such as text customization, final URL expansion, and brand inclusions/exclusions. One setting to pay extra attention to is URL inclusions. They’re essential for keeping campaigns in a controlled environment, especially for in-language efforts. Without that guardrail, Google can easily pull in other languages or unintended pages.

   • If you want to get granular control at the ad group level, many of the same settings are available, but in addition, there are search term matching and locations of interest.
     

3. Wire up your CRM for offline tracking. Every MQL, SQL, and opportunity gets imported into Google Ads so AI Max-enabled search campaigns can spot which signals are leading to pipeline. The fresher your CRM feed (updated lead scores, won/lost outcomes, deal value), the smarter AI Max’s intent matching becomes. Over time, you’ll see it stop chasing low-value clicks and start zeroing in on contacts ready to move. 

   • Ensure that you are optimizing to the lowest funnel CRM conversion event signals that have enough volume to meet the threshold of at least 15 conversions in the last 30 days. The more volume we have over this threshold is a bonus, so AI has more data to stay up to date on what counts as a “win.” 
     

4. Launch your pilot campaign. Allocate a modest budget (around 5 percent of your search spend) to your AI Max experiment. Keep a close eye on irrelevant queries and ad performance. Adjust negative keyword lists, asset exclusions, and URL exclusions as early warning signs of waste.
   

5. Analyze results and scale thoughtfully. In the first 2–4 weeks, focus on early signals like CTR, CPC, engagement quality, and conversion rates to MQLs. As campaigns run longer, layer in mid-funnel metrics such as cost per SQL and sales acceptance. True pipeline and revenue impact will take more time — typically several months in B2B buying cycles — but the asset report can still give you immediate insight into which headlines, landing pages, and creative are performing best. Apply those learnings back into both AI Max and your standard campaigns.

TL;DR: AI Max = Cautious Optimism

AI Overviews aren’t going away—and if your ads aren’t showing up in them, someone else’s are. Google is clearly betting big on this new SERP experience, and AI Max doesn’t seem like it will be going anywhere anytime soon.

It’s still early days but some of our initial tests have given us pause and even more reason to test and measure with rigor.  AI Max cannot be adopted blindly. We’re leaning in with structured pilots — testing within defined parameters, auditing results at the CRM level, and holding performance to the standards that matter for revenue impact.

The key is disciplined experimentation. Following steps from our playbook can help you build clear hypotheses, control the environment, and let real data guide your next moves. Testing with intention is how a beta becomes a reliable path to success. For more on how AI is reshaping search — and what it means for both SEM and SEO — see our post on Semantic Search: The Next Leap in Search Intelligence. 

Privacy As Progress: The Shift Away From Third-Party Data Is More Than a Technical Adjustment

In the last decade, Europe has been at the forefront of privacy regulation, with the General Data Protection Regulation (GDPR) setting a benchmark also at global level. But in 2025, the landscape is shifting again. The stricter enforcement of consent policies, together with the ongoing debate across the European Commission on how to manage third-party cookies, and growing audience awareness are not just compliance challenges: they are catalysts for transformation.

Marketers across Europe are being called to evolve. The old playbook – built on broad targeting and opaque, mostly siloed, data management– is being replaced by a new paradigm. It demands a move from broad, impersonal outreach to trust-first engagement, where transparency, relevance, and respect for buyer autonomy are paramount. In a sector where relationships drive revenue, this evolution is not just necessary – it’s powerful.

A Uniquely European Balance

In Europe, the marketing environment is shaped by a complex mix of cultural, linguistic, and regulatory factors. Buyers moved from being just passive recipients of content, to active participants in the conversation. They want tailored experiences, but they also demand transparency and control. For example, platforms like LinkedIn are tailoring their advertising functionalities according to specific regional needs – giving EU users the option to choose whether to see or not sponsored ads in their Inbox. 

In such a context, consent-driven marketing isn’t just a legal requirement – it’s a brand differentiator. B2B buyers are increasingly scrutinizing how vendors handle data, and companies that demonstrate ethical, transparent practices earn trust faster.
This is also empowering a Mindful Marketing ethos, meaning a strategy built on first-party data, explicit consent, and hyper-personalized messaging – often crafted on a “segment of one” basis.

In B2B, where buying cycles are long and decisions are high-stakes, this approach pays dividends. It allows marketers to build credibility, nurture leads with precision, and foster loyalty in ways that generic outreach never could. 

Room for Opportunity: Turning Regulation Into Relationship

Rather than viewing privacy regulations as limitations, forward-thinking marketers are using them as a springboard for innovation. Here’s how:

1. First-party data as a strategic engine
   In B2B marketing, every interaction – whether it’s a webinar registration, a whitepaper download, or a demo request - offers valuable first-party data. These touchpoints not only signal interest but also provide insights into where buyers are in their decision-making journey. However, the true value of this data emerges only when it is collected with consent, managed responsibly, and effectively integrated across multiple sources – such as CRM systems, marketing automation platforms, and website analytics. This integration is pivotal to building a unified customer view and avoiding fragmented insights. Equally important is the messaging used to promote those assets, to reach the right target: it must be crafted to resonate with the buyer’s specific needs, challenges, and pain points. When messaging is aligned with real business concerns, it not only drives engagement but also reveals intent – helping marketers understand what truly matters to their audience. This combination of thoughtful data management and strategic content design enables more relevant, personalized, and insight-driven engagement throughout the B2B funnel.
   

2. Contextual targeting and consent frameworks
   Contextual targeting offers a privacy-safe alternative to behavioral tracking. B2B marketers are aligning content with the environments where buyers consume information (industry publications, professional forums, niche platforms, etc). Transparent consent frameworks ensure that this targeting respects user preferences, reinforcing trust while maintaining relevance.
   

3. Long-Term value creation
   Privacy-first strategies naturally align with the long-term nature of B2B relationships. Instead of chasing short-term conversions, marketers are investing in education, thought leadership, and consultative selling. This builds brand equity, positions companies as trusted advisors – an essential role in complex buying environments – and fosters sustainable growth.

When Compliance Goes Hand in Hand With Connection

Europe isn’t falling behind due to stricter privacy standards – it’s leading the way. By embracing trust-first strategies, marketers are not simply complying with regulation, they’re redefining what meaningful engagement looks like and what they need to really connect with their actual buyers.

In this new era, success belongs to the teams who see privacy not as a hurdle, but as a hallmark of quality. Those who build with consent, personalize with purpose, and communicate with clarity will be the ones who lead.

Powered by ROI•DNA & Hotwire