The US marketing company CoSchedule has just published the results of its recent survey of 900 marketers, reporting on their expected priorities for 2026.

Here are some of the results that caught our eye (the data is theirs, many of the conclusions below are ours):

AI Tools: Using Less Than You'd Think

Most of marketers' current use of AI Tools is focussed into three (obvious) main categories: writing tools, Generative AI and Chatbots. Adoption of other tools is limited. Marketers are using AI for production and efficiency, not foresight.

AI Improves Performance

79% of marketers say AI improved their performance in the last year. It’s no longer a debate about the merits of AI, that battle has been won.

This Year? Significant AI Impact Expected

More than 70% expect that AI will have a substantial impact on marketing in 2026 (though the most common expectation is that there will be no major structural change to their team).

Personalisation: Not So Much

Despite industry hype, only 9% of marketers are prioritizing personalisation.

AI made personalisation easier, but not more valuable in marketers’ minds. For marketers pressured to deliver ROI, personalisation isn’t seen as a reliable driver of results.

Marketers Don't Consider Themselves AI Experts

In a surprising display of modesty, most marketers admit that they're still learning this AI stuff. Given these results, there's a real opportunity for today's marketers to get ahead by upskilling themselves in AI (you might like to check out our AI training courses).

Traffic Impact? Not Yet

Most marketers say that the rise of AI as a search and discovery engine hasn't yet hurt their website traffic (and for some, it's actually grown).

But a Majority Already Turn to AI

More than half of marketers have already turned away from classic search, gathering insights and information from the likes of ChatGPT and Google.

Optimising for AI

Unsurprisingly, then, nearly nine out of ten are adjusting what they publish, to improve their chances of being chosen in AI search results.

Focus on Social Media

Social Media continues to attract its share of attention, with more than half of marketers saying it will be their biggest focus in the year ahead.

Biggest Challenge: Drowning in AI Slop

They might have described it more tactfully, but getting seen amidst a torrent of AI Slop was marketers' top concern for 2026.

So what do we make of all this?

Beyond the "Slop": Navigating the AI Paradox of 2026

If 2025 was the year the marketing world finally stopped fighting AI and started using it, 2026 is shaping up to be the year we realise we might be using it wrong.

The results from the CoSchedule survey paint a picture of an industry in a state of enthusiastic contradiction.

On one hand, we have achieved mass adoption: 79% of us say AI has improved our performance, and a staggering 75% are using it to write content. The "battle for merit" is indeed over.

But look closer at the data, and a paradox emerges. Our biggest fear for 2026 is "oversaturation" and getting lost in "AI slop". Yet, by using AI primarily as a writing generator rather than a strategic scalpel, we are actively fuelling the very torrent of content we are terrified of drowning in.

As we move through 2026, the data suggests four critical disconnects that marketers must address to stay ahead.

1. The Production Trap vs. The Relevance Gap

The most alarming statistic in this report isn't about what marketers are doing, but what they are not. Only 9% of marketers are prioritizing personalisation in 2026.

This puts the average marketer at odds with the wider industry direction. While CoSchedule’s respondents are focused on content production, major consultancies like PwC and HubSpot have identified "hyper-personalisation" and "agentic AI" as the primary drivers of ROI for 2026.

The disconnect is striking: AI has made marketers more productive without making marketing more effective. We're producing more content, launching campaigns faster, and automating countless tasks. But we're not necessarily winning more customers or building stronger brands.

This reveals something profound about the nature of AI's impact on marketing. The technology excels at reducing friction and accelerating execution, but it doesn't automatically translate to strategic advantage. As one survey participant noted, it's becoming "nearly impossible to demonstrate which marketing activities are actually driving revenue" amidst customers interacting across ten or more touchpoints.

The reality is that AI has lowered the barriers to entry for producing marketing content, which means everyone is producing more of it. Twenty-nine per cent of marketers cited oversaturation of AI-generated content as their top concern for the industry—more than ROI pressure, budget cuts, or attribution challenges combined. We've collectively flooded the market with content whilst simultaneously making it harder for any individual piece to stand out.

We have fallen into a "Production Trap." We are using powerful engines to create more generic emails and blog posts faster than ever, but we aren't using that same power to make them relevant. If we continue to view AI solely as a copywriter rather than a data analyst, we risk becoming efficient producers of noise that nobody wants to hear.

The Fix: Stop optimizing for volume. Shift your AI focus from Generation (writing text) to Prediction (analysing customer behaviour). Use AI to determine who needs to hear from you, not just to write what you want to say to everyone.

2. The "Searchquake" is Internal First

For years, SEO experts have warned about the shift from Search Engines to Answer Engines. That shift has now arrived, but in a surprising way: marketers themselves have defected first.

According to the survey, 53% of marketers now rely on AI tools (like ChatGPT or Gemini) for information, compared to just 35% who rely on traditional search engines. This is a watershed moment. If we—the people whose job it is to understand digital behaviour—have stopped clicking on blue links, why do we assume our customers are still doing it?

This correlates with the broader trend of "Zero-Visit Visibility" observed in 2026 search trends. Your customers are getting answers directly from LLMs without ever visiting your website.

The Fix: You can no longer just optimize for keywords. You must optimize for answers. Ensure your content is structured clearly enough for an LLM to digest and cite. If your brand isn't part of the AI's training data or retrieval set, you are invisible to the 53% of users bypassing Google.

3. The Human Premium

With 84% of marketers noting that AI hasn't hurt their traffic yet, there is a false sense of security. The "Slop" concern indicates that audiences are becoming hypersensitive to synthetic content.

As the quantity of AI-generated content explodes, the value of human connection skyrockets. The "Expert" tier of marketers (currently just 3%) knows that the winning strategy for 2026 is "Cyborg Marketing": using AI for the heavy lifting of structure and research, but ensuring the final voice, opinion, and empathy are unmistakably human.

The Fix: Audit your content. If an AI could have written it without your input, delete it. It adds no value. Focus on "Opinionated Content"—unique viewpoints, case studies, and personal stories that an LLM cannot hallucinate.

4. The Skills Paradox: Everyone's Using It, Nobody's Mastering It

Perhaps the most telling statistic from the CoSchedule research is this: just 3 per cent of marketers identify as AI experts. Three per cent. Despite AI being integrated into nearly every marketing workflow, despite 88% of marketers using these tools daily according to industry research, almost nobody considers themselves truly proficient.

This creates a dangerous dynamic. When everyone has access to the same tools and nobody has mastered them, the result is a race to mediocrity rather than excellence. The advantage goes not to those using AI—since everyone is—but to those who can use it strategically, creatively, and with genuine understanding.

Over 75 per cent of marketers see AI skills as a gap in their professional development, yet training remains inconsistent and often superficial. Many marketers are learning on the fly, experimenting with prompts and tools without systematic development of their capabilities. Over half of B2B marketing teams recognise an AI skills gap, with marketers expressing concerns about being "left behind" as adoption accelerates around them.

The irony is palpable: the tool meant to democratise marketing excellence has instead created a new form of inequality between those who truly understand AI's capabilities and limitations, and those who simply use it as a faster typewriter.

Actions for 2026: What Marketers Must Do Now

Based on the survey findings and broader industry research, here are the critical actions marketers should take to stay ahead:

A. Invest in Genuine AI Literacy

Don't settle for surface-level tool familiarity. The 2025-2026 period represents the integration era, where AI stops being a campaign feature and becomes the foundation of every marketing system. This requires understanding not just how to use AI tools, but how to architect AI solutions—defining data flows, evaluation criteria, and governance frameworks.

Action steps:

Allocate dedicated budget for AI training, not as an afterthought but as a permanent line item
Focus training on three core competencies: prompting (how to get quality outputs), vetting (how to evaluate AI-generated content), and adapting (how to align AI outputs with brand and strategy)
Create internal knowledge-sharing channels where team members share successful prompts and workflows
Require experimentation—set aside time for team members to explore new AI capabilities

(We would be remiss if we didn't point you to our own AI training courses: https://netmarketingcourses.co.nz/ai-courses/)

B. Build Systems, Not Just Campaigns

The best marketing organisations treat AI orchestration as core intellectual property—a competitive system that compounds knowledge over time. Rather than using AI to create individual pieces of content, build systems that learn and improve.

Action steps:

Document your most successful AI workflows and turn them into repeatable processes
Create feedback loops where campaign results inform future AI-generated content
Invest in data infrastructure that makes your proprietary knowledge accessible to AI systems
Implement quality control processes that combine human judgement with AI efficiency

C. Differentiate Through Creativity and Brand

In a world where oversaturation of AI content is marketers' top concern, the competitive advantage belongs to those who can create genuinely distinctive work. AI should amplify your creativity, not replace it.

Action steps:

Use AI to handle production tasks so humans can focus on strategy, creativity, and relationships
Invest more heavily in brand building and distinctive creative work
Don't let AI flatten your brand voice—develop clear brand guidelines that inform AI outputs
Prioritise quality over quantity, even though AI makes quantity easier

D. Master Multi-Channel Orchestration

With performance fragmenting across channels, success requires coordination rather than channel-specific excellence.

Action steps:

Implement integrated marketing calendars that show how all channels work together
Develop cross-channel attribution models that acknowledge the complexity of modern customer journeys
Focus on incremental gains across multiple channels rather than breakthrough wins in one
Use AI to identify patterns across channels that humans might miss

E. Prepare for the AI Search Transition

Eighty-nine per cent of marketers are optimising for AI-driven search, but many are doing so without clear frameworks for what this actually means.

Action steps:

Create comprehensive, authoritative content that AI systems will want to cite
Build brand authority through thought leadership, research, and expertise
Structure content to be easily parsed and understood by AI systems
Develop relationships and mentions across reputable sources
Focus on being the answer, not just ranking for the question

F. Build Governance and Evaluation Frameworks

Governance—bias detection, fairness assessment, output validation—has become the critical skill that separates AI operators from AI orchestrators.

Action steps:

Define clear processes for when AI outputs require human validation
Create quality criteria for evaluating AI-generated content before publication
Establish guidelines for AI use that protect brand reputation and ethical standards
Build systems to detect and prevent AI hallucinations and errors

G. Focus on Strategic Advantage, Not Just Efficiency

Remember that high-performing organisations aim for growth and innovation, not just cost reduction from their AI efforts.

Action steps:

Measure AI's impact on business outcomes, not just task completion
Explore how AI can help you enter new markets or serve customers in new ways
Use the time saved by AI automation to do more strategic work, not just more of the same work
Set transformation goals alongside efficiency goals

The Path Forward

The CoSchedule survey reveals a marketing profession at an inflection point. AI has delivered on its promise of making work faster and easier, but it hasn't yet delivered the strategic transformation that separates leaders from followers. The tools are ubiquitous, but mastery remains rare. Productivity is up, but so is competition. ROI is harder to achieve across every channel.

This isn't a reason for pessimism—it's an opportunity. The gap between those who simply use AI and those who truly master it represents the biggest source of competitive advantage in marketing today. With only 3 per cent of marketers identifying as AI experts, there's enormous opportunity for those willing to invest in genuine capability building.

The winners in 2026 and beyond won't be those with the best tools—everyone will have access to excellent tools. They'll be the marketers who understand how to architect AI solutions, who build systems that compound knowledge over time, who create work that stands out in an AI-saturated landscape, and who use AI to amplify distinctly human capabilities like creativity, strategic thinking, and genuine connection.

The productivity gains are real, but they're table stakes now. The question is what you'll do with the time and capability AI provides. Will you simply do more of the same faster, or will you use it to do genuinely different and better work?

The choice, and the opportunity, is yours.

FAQ: AI in Marketing (2026 Edition)

Q: Is SEO dead in 2026?

A: No, but it has mutated. With over half of marketers and consumers now turning to AI tools for answers, "Classic SEO" (ranking for ten blue links) is sharing the stage with "LLM Optimisation." You now need to be the source that AI cites in its answer, not just a link on a page.

Q: Why is everyone worried about "AI Slop"?

A: "Slop" refers to low-quality, AI-generated content that provides no unique value. It is the top concern for marketers in 2026 because it saturates channels, making it harder for high-quality, human-led content to be seen.

Q: Should I stop using AI for writing?

A: Not necessarily. 75% of marketers use it. The key is to use it as a drafting tool or a research assistant, not a final publisher. The most successful marketers use AI to build the skeleton, but humans add the muscle and skin (tone, examples, empathy).

Q: Why is personalisation such a low priority?

A: It’s a dangerous blind spot. Only 9% of marketers are prioritizing it, likely because it is technically difficult to implement compared to simply generating text. However, this offers a massive competitive advantage to the few brands that do invest in using AI for personalised customer journeys.

Q: Will AI replace my marketing team?

A: Most marketers (70%+) expect substantial impact, but the consensus is that it won't lead to major structural changes in teams yet. The shift is toward upskilling—moving from "writers" to "editors" and "strategists."

Q. Is AI actually improving marketing results, or just making marketers busier?

A: According to the CoSchedule survey, 79% of marketers report that AI improved their performance, yet the same research shows declining ROI across every marketing channel. This paradox reveals that AI excels at improving workflow efficiency and reducing execution time, but doesn't automatically translate to better business outcomes. AI makes it easier to produce more content and launch campaigns faster, but without strategic application, this increased productivity can lead to market oversaturation rather than competitive advantage. The marketers seeing genuine results are those using AI for transformation—not just automation—building systems that learn and compound knowledge over time rather than simply completing tasks faster.

Q. What percentage of marketers consider themselves AI experts in 2026?

A: Just 3% of marketers identify as AI experts, despite 88% using AI tools in their daily work according to industry research. This enormous gap between usage and mastery represents both a challenge and an opportunity. The vast majority of marketers place themselves somewhere in the middle—comfortable using AI tools but far from true proficiency. This skills gap is widely recognised, with over 75% of marketers seeing AI capabilities as lacking in their professional development. The disparity between widespread adoption and limited expertise means there's significant competitive advantage available to those who invest in genuine AI literacy beyond surface-level tool familiarity.

Q. How is AI affecting website traffic and search visibility?

A: Currently, 84% of marketers report that website traffic has held steady since AI's mainstream adoption, but this stability may be temporary. A majority of marketers (53%) now get their information from AI tools rather than traditional search engines like Google, signalling a fundamental shift in discovery behaviour. In response, 89% of marketers are actively optimising for AI-driven search, preparing for a future where being cited by AI matters more than ranking in traditional search results. Organic search is cited as the most common area of performance decline (by 31% of marketers), suggesting the transition is already underway even if overall traffic numbers haven't collapsed yet.

Q. Which marketing channels are delivering the best ROI in 2026?

A: Email marketing leads as the strongest channel, but only by a narrow margin—just 25% of marketers identify it as their best performer. This reflects a broader fragmentation where no single channel dominates. Among social platforms, LinkedIn delivers the best results, whilst Twitter/X is seen as the least reliable for ROI. However, the most striking finding is that owned channels—organic search, website traffic, and email—are declining faster than paid channels. This represents a significant shift from previous years when owned media offered the best cost-to-return advantage. The new reality requires competence across multiple channels rather than deep expertise in one dominant platform.

Q. What's the biggest concern marketers have about AI?

A: Oversaturation of AI-generated content ranks as the top concern, cited by 29% of marketers—more than worries about ROI pressure, budget cuts, or measurement challenges. This fear reflects the reality that AI has made content production so easy that markets are becoming flooded with material, making differentiation increasingly difficult. Marketers are concerned that AI will flatten distinctive brand voices and make it harder for quality work to stand out. Secondary concerns include data privacy and security (35% of marketers), reliability issues like AI hallucinations, and the lack of adequate skills and training. Interestingly, only 3% of marketers believe AI is actively harming the industry, suggesting optimism about the technology's potential despite concerns about its current applications.

Q. What AI skills do marketers actually need to develop?

A: The most critical AI competencies for 2026 centre around three areas: First, prompting skills—the ability to provide AI with the right context, constraints, and examples to generate strategic, on-brand outputs rather than generic results. Second, evaluation and governance—knowing how to assess AI outputs for accuracy, brand alignment, and quality before publication. Third, strategic orchestration—understanding when to lead and when to let AI work, and how to architect AI solutions rather than just operating AI tools. Marketers don't need to become engineers or data scientists, but they do need to understand how to define data flows, create evaluation criteria, and build governance frameworks that make AI reliable and valuable. The competitive advantage comes from treating AI as a collaborative partner that amplifies human creativity and strategic thinking, not as a replacement for them.

Q. Are marketing jobs at risk from AI automation?

A: Concerns about job displacement have increased significantly, with 60% of marketers now worried that AI might replace their roles—up from 36% the previous year. However, the data suggests a more nuanced reality. Only 9% of organisations report reducing headcount due to AI implementation, whilst 73% expect AI to significantly reshape daily work. This suggests AI is transforming roles rather than eliminating them wholesale. The marketers most at risk are those doing routine, undifferentiated work that AI can easily replicate. Those focusing on strategy, creativity, brand building, and genuine human connection are better positioned. As one industry expert noted, AI is "a productivity and effectiveness tool like no other, but it's not going to be the gamechanger that totally shifts who becomes the number one in the market"—suggesting competitive advantage still depends primarily on human capabilities.

Q. How should marketing budgets be allocated for AI in 2026?

A: Currently, 47.6% of marketers allocate less than 10% of their budget to AI-driven initiatives, but 59% plan to increase AI investment in 2026. The smartest allocation strategy involves dual investment: in your people's skills and in the AI systems that augment them. Training should be a permanent budget line item, not an afterthought, covering everything from formal certifications to hands-on workshops using your actual marketing data. For tools and technology, focus on solutions that integrate with existing systems and provide clear ROI rather than chasing every new capability. The highest-performing organisations (according to McKinsey research) set growth and innovation objectives for AI, not just efficiency gains, suggesting budgets should support transformation rather than mere automation. Expect to invest more as you progress from experimentation to full integration.

Q. What's the difference between using AI and mastering AI in marketing?

A: Using AI means employing tools to complete tasks faster—generating content, automating emails, or creating images. Mastering AI means architecting solutions that compound knowledge over time. Users configure existing platforms; masters engineer the context, data flows, evaluation criteria, and governance frameworks that make AI reliable and strategically valuable. The difference shows up in results: AI users achieve productivity gains, whilst AI masters achieve competitive advantage. Masters build feedback loops where campaign results inform future AI outputs, create systems that learn from data, and develop proprietary processes that competitors can't easily replicate. They understand not just how to prompt AI effectively, but how to structure entire marketing systems around AI capabilities. As noted in the CoSchedule survey, with only 3% of marketers considering themselves experts, this mastery gap represents the single biggest opportunity for differentiation in modern marketing.

Q. How can small marketing teams compete with AI-powered larger teams?

A: AI is potentially the great equaliser for small teams because it democratises access to capabilities that previously required large budgets and extensive resources. A small team that masters AI can generate content, analyse data, and execute campaigns at a scale that would have required a much larger team just a few years ago. The key advantages for smaller teams are agility and focus—you can experiment faster, iterate more quickly, and build proprietary AI systems tailored to your specific needs rather than managing complex enterprise implementations. Focus on building systems rather than just using tools, develop deep expertise in your niche rather than trying to compete broadly, and use AI to punch above your weight in production whilst maintaining human focus on strategy and creativity. Small teams that master AI orchestration can absolutely compete with—and even outperform—larger teams that merely use AI as a productivity tool.