The beginning of the year is my favorite time to do this. As a strategist, every January I go down the same rabbit hole: reports, forecasts, trend decks, hot takes.
Most trend reports falls into one of two buckets:
1. Obvious things everyone already knows
2. Shiny tactics that won’t survive the next quarter.
This piece is neither.
What you’ll find here are changes happening in the market. I broke each trend down into three parts:
- How it used to work
- What changed
- How to apply it to your brand, product, or content
The trends I've included are the logic shaping B2B marketing in 2026.
Let’s get into it.
*This analysis pulls from repeated signals across reports by AXA, Info-Tech, Forrester, FT Strategies, Activate, Fratzke, Emplifi, and more.
TL;DR
- Buyers don’t care where you’ll take them in 3 years. They care what won’t break next week.
- Content that stays in one place dies there. Your best ideas need to show up in social feeds, AI answers, newsletters, and videos.
- Omnichannel isn’t “be everywhere.” It’s “be coherent everywhere.” If your story changes between your website, LinkedIn, and sales deck, you look unsafe.
- Stop marketing “AI-powered.” Show what disappears from the workflow after adoption.
- Human tone isn't enough for trust building.
- In 2026, the buyer doesn’t always land on your page. But AI does. You can’t optimize for LLMs if you don’t track where and how they surface your content.
- The most “creative” brand rarely wins. The easiest-to-explain brand does.
- 2026 rewards AI content systems, not random prompts.
Scroll for the examples. You’ll see exactly how these trends show up.
TREND 8: From the big vision to plain simple risk control
Before
For most of the last decade, trust was built through vision. If your brand sounded like it had a map of the future, buyers assumed you were competent enough to lead them there.
So everyone sold the same story:
- Enterprise platforms pushed multi-year roadmaps and sold “transformation”
- Consultancies sold “future readiness”
- Cloud vendors sold “foundations for innovation”
And in a relatively stable world, this worked.
Risk felt distant. Waiting felt acceptable.
You could sell the big future because today felt manageable.
What changed
Risk moved closer. Teams feel it in real time. They’re losing sleep over:
- Geopolitical instability disrupting supply chains and delivery
- AI hallucinations and automation errors playing out at scale
- Data leaks, misinformation, compliance failures
- Tools that promise “efficiency” but create new failure points
So vision stopped being enough.
Today, trust forms when decisions feel safer.
Not: “We’ll transform your business”.
More: “Your core workflows won’t break next week”.
How to put this into practice
Shift your messaging from aspiration to risk reduction. Instead of talking about what your product enables, talk about what it prevents:
- What errors does your product block?
- What uncertainty does it remove from day-to-day decisions?
- What becomes more predictable and less fragile?
- Where do you reduce the chance of a costly “we didn’t see it coming”?
Make your product feel like a stabilizer (it absorbs chaos rather than adding complexity).
Example: how this already plays out
The strongest brands are quietly repositioning as:
- risk-management partners, not “software vendors”
- decision-support systems, not feature lists
- predictability engines in an increasingly unstable environment
Take CrowdStrike. They don’t lead with a vague “security vision.” They sell speed-to-response: detect threats fast, contain them faster, reduce blast radius.
The promise is practical:
When something goes wrong (because it will), the system reacts faster than humans can. And that gap is what keeps a bad day from turning into a headline.
“But what if we’re selling a service, not a product?”
Same trend. Buyers don’t hire service partners because they want bold promises.
They hire them because they don’t want their project to become a slow-motion disaster.
That’s why this positioning works for agencies, development shops, consultancies, and delivery partners.
Take as an example our client.
Modeso positions itself as a safe delivery partner. Not: “We’ll build your next big thing.” Instead, predictable execution, reduced delivery risk, fewer surprises in scope, timeline, or quality, faster time-to-market because the process is controlled.
They’re selling control. That’s what buyers trust right now.
TREND 7: Content must be everywhere
Before
Content used to live in a few predictable places: your website, your LinkedIn, maybe your clients's inbox. Basta.
If you published something high-quality and optimized it well, visibility usually followed.
Discovery was linear: publish → rank → get read.
Distribution was something you did after the work was done. If did it at all.
What changed
People don’t “sit down and read” the way they used to. They absorb ideas while: scrolling a feed, half-watching a video, skimming a Slack thread, listening to a podcast on 1.5x, asking ChatGPT for a summary.
So content that waits politely to be discovered gets skipped. Ideas that only exist in one format die in one format.
Today, your content needs more surface area. If it doesn’t show up across feeds, conversations, tools, and channels, it doesn’t exist. No matter how good it is.
How to put this into practice
- Start with one sharp idea, not a format. The same core insight should show up in social feeds, sales conversations, AI answers, newsletters, internal decks, and long-form content.
- Distribution doesn’t work when it’s treated like a one-off effort. Build a distribution system you can repeat.
- Choose fewer ideas and push them harder (Consistency compounds faster than constant reinvention).
Example: how this already plays out
Notion does this well with “proof content”.
They don’t treat customer stories as one thing. They treat them as a reusable asset that moves across channels.
Customer Stories on the website and Customer Stories playlist on YouTube: the same narrative repackaged into smaller clips, highlights, and product use cases.
That’s the play now: One idea. Many touchpoints. Repeated until it sticks.
TREND 6: Omnichannel is one POV everywhere
Before
Omnichannel used to mean “multi-channel presence.” If a company: had a blog, posted on LinkedIn, ran email campaigns, had a sales deck — that counted as omnichannel.
Even if every channel told a different story. One message on the website. Another in pitch decks. LinkedIn posts written in a completely different tone. Ads pushing a different promise.
Nobody treated this as a problem.
Because buyers weren’t stitching everything together in real time. They mostly entered through one channel, evaluated there, and moved on.
So consistency was optional.
What changed
Distribution is easier than ever. AI tools help every team publish more. It’s not so hard to show up everywhere.
The hard part is showing up everywhere without becoming incoherent.
When your message shifts between touchpoints, trust breaks. Inconsistency signals risk. It reads like:
- Your teams aren’t aligned
- You're not confident in what you stand for
- Your product might be just as inconsistent
Omnichannel now means one thing: sound like the same company everywhere.
Formats can change.
Meaning can’t.
How to put this into practice
- Define a single positioning spine.
- Lock one core point of view.
- Website, LinkedIn, sales decks, newsletters, AI outputs are all different formats to spread the same idea.
Example: how this already plays out
One of our clients, Wiseboard, does this great. They don’t treat channels as separate.
One POV runs through everything: posts, newsletters, offline talks, blog content, and video.
So the brand becomes easier to recognize, and easier to trust. Visibility grows because the market keeps hearing the same thinking.
TREND 5: Don’t sell AI as a feature
Before
When AI first showed up in B2B products, it was treated like a differentiator. Something you slapped on your homepage to look modern.
So “AI” became the message:
- AI-powered
- Smart
- Built with AI
- Uses machine learning
The assumption was: if it sounds advanced enough, buyers will connect the dots and imagine the value.
And for a while, that worked.
AI felt new and that novelty carried weight. Saying “AI” made you look ahead of the market, even if the product experience didn’t change much.
What changed
AI stopped being special. Most products already use it. Buyers expect it the same way they expect integrations.
What really matters isn't if this uses AI, but what changes after users turn it on:
- Do decisions happen faster?
- Are there fewer manual steps?
- Is the operational cost now lower?
AI became invisible. Impact is the selling point.
How to put this into practice
Stop selling AI as a feature.
Start selling what work looks like after AI is in place. That means:
- Show which tasks no longer need human input
- Show how work moves differently after adoption
- Explain which decisions move without manual reviews
- Highlight which risks are handled automatically inside workflows
Messaging should reflect operational reality.
Example: how this already plays out
Stripe is a great example of this done right. It uses AI everywhere, but you rarely see them talking about it directly.
Take Smart Retries. Stripe doesn’t hype the model. They say businesses recover an average of 57% of failed payments (more successful payments, less lost revenue). The AI part shows up quietly. It's just the engine under the hood.
TREND 4: Humanwashing stops working. Humanity needs proof
Before
When AI made content faster and cheaper, brands responded in the most predictable way possible.
First: they used AI to scale production.
Then: they realized everything started sounding the same. So they tried to “fix” it with tone. Emotion got layered on top (they ask AI to use friendly language for their text and vulnerable-sounding hooks, add handwritten-style visuals, etc).
The goal was to sound human.
And for a while, that worked. Warm copy felt refreshing next to stiff corporate messaging.
Relatability stood in for credibility, even when there was no real experience behind it.
What changed
People got better at spotting fake “human” content. Buyers can tell when:
- Opinions sound like they could belong to anyone
- Stories aren’t tied to real decisions or consequences
- The writing feels polished but empty
Now this kind of content backfires.
Warm language without evidence doesn’t feel authentic anymore. It feels engineered. Like someone trying too hard to be relatable.
And when buyers sense that, they stop trusting the message.
Research from people like Dave Fratzke points to a pattern: The teams earning attention and trust aren’t the loudest or the most “human.” They’re the most specific. The ones willing to attach names, context, and responsibility to what they say.
How to put this into practice
Stop trying to make AI content sound human. Bring humans back into the system. Focus on content from people doing the work. Let founders explain business models, engineers show technical moments. Prioritize formats like demos and workshops.
Example: how this already plays out
Two of our clients execute this perfectly well. They let people inside the business publish their thinking.
Flyaps gives engineers space to share how they build. This content sounds true because it comes from people doing the work, not people describing the work.
Stfalcon does the same from the leadership side. The founder talks openly about running the business:
- growth decisions
- mistakes
- constraints
- lessons learned the hard way
That's real and relatable.
TREND 3: Zero-click and AI search break the traffic model
Before
For years, traffic was the scoreboard. You published content. People searched. They clicked. They landed on your site.
SEO was both the distribution engine and the measurement system. Rankings, pageviews, and organic sessions were treated as proof that content worked.
Visibility and traffic were basically the same thing.
If you were seen, you got the click. If you got the click, you got the audience.
What changed
Discovery moved away from websites. Google shows the answer directly in search. People get answers in social feeds, email, or AI assistants and… don’t click.
As FT Strategies’ Future of Discovery research shows: visibility still exists but clicks don’t automatically follow.
You can be part of the conversation everywhere and still own nothing.
How to put this into practice
Track visibility beyond clicks. Measure where your content appears in AI answers, summaries, and comparisons (not just how much traffic it gets).
Example: how this already plays out
At Zmist & Copy, we run LLM visibility tracking to see where client content is being cited by AI tools and which pages show up in AI answers.
That data helps us optimize content to be referenceable inside AI systems.
TREND 2: B2B brands compete on clarity, not creativity
Before
For years, B2B marketing tried to win through expression: better copy, sharper visuals, more clever campaigns, more “stand out.”
Creative positioning was treated as an advantage: if you sounded different, buyers assumed you were better.
The goal was memorability. Attention was more focused and buyers had time to interpret what you meant.
What changed
In complex markets, the most creative brand rarely wins. The most understandable one does.
Buyers are tired of figuring things out. They’ve had enough of buzzwords, vague promises, messaging that means different things to different people.
Research from Forrester, FT Strategies, and others all points to the same thing: when buying feels risky, clarity is what brands compete on.
How to put this into practice
- Replace clever headlines with clear ones.
- If a buyer can’t explain what you do after reading the hero section, rewrite it.
- Show the workflow, not the promise.
- Walk buyers through what actually happens before and after your product is in place.
- Publish comparisons that reduce thinking effort.
Example: how this already plays out
Twilio is a great example. They rebuilt their documentation as a product, treating clarity as a competitive advantage.
“We’ll make this simple for you”
In today’s market, that promise beats creativity every time.
TREND 1: Not one AI bot – a system
Before
AI first showed up in content as a speed boost. Most companies used one AI tool for everything: research, drafting, editing.
And yes, content got faster. But it didn’t get better.
Because one tool produces one way of thinking, scaling content anyone could publish.
What changed
Teams had more drafts, but fewer ideas that actually worked.
If your process is weak, AI scales the weakness.
If your thinking is fuzzy, AI makes it fuzzy faster.
That’s why many teams moved away from “one AI tool for everything.” Instead, they started building AI systems. Each tool handles a specific job. Together, they work like a team.
How to put this into practice
Stop using AI as a tool. Start using it as a system. This means:
- Build strategy and POV into the setup, not into every prompt
- Use different AI agents for different jobs, instead of one tool doing everything
- Connect those agents into a single workflow, so context doesn’t get lost
- Keep outputs consistent across formats and channels, as volume increases
When AI works like this, it supports your thinking.
Example: how this already plays out
Instead of prompting AI, we train systems to follow a strategy. Positioning, context, and rules are built into the workflow. Different agents handle different things. That’s when AI supports your content.
Conclusion
None of these trends are about being louder, faster, or more creative. They’re about being safer, clearer, and easier to trust.
If your marketing reduces uncertainty, explains reality, and shows up consistently wherever decisions are made, you’ll win attention without chasing it.
