The State of B2B Marketing. What's working & What's not.
What founders actually think about marketing right now
B2B marketing is changing at a rapid pace.
I’ve recently spent a bunch of time with founders and other marketing leaders. These are my unfiltered notes on the state of B2B marketing now. What’s working and what’s not.
1. Brand / Product Positioning.
The challenge for all brands right now is that AI is consuming all the online oxygen. ChatGPT and Claude alone have created an army of content creators who cover every single feature they launch. Every channel is awash with content about AI and content generated by AI. It’s hard for any brand to make noise.
To stand out, the best companies are positioning around the buyer’s immediate problem state rather than static persona descriptions. What does that mean?
Slack didn’t position itself as “chat software.” It positioned itself as “where work happens,” creating an entirely new mental category that made feature-by-feature comparisons irrelevant. The result: dominant market share in a space crowded with messaging tools, and a $27.7B acquisition by Salesforce.
Notion escaped the “note-taking app” comparison trap by positioning itself as a flexible workspace. Instead of competing on features with Evernote and Google Docs, it attached to a broader job-to-be-done—result: 100M+ users and a $10B valuation.
Everyone wants to elevate their brand campaigns and positioning in this way (because all products & features are starting to sound the same).
The person who can do this is in very high demand. The challenge is, there’s a significant gap between the top tier in this role and everyone else. It’s hard to find and hire for this role.
2. AEO (Answer Engine Optimization)
Everyone I talk with is bought into optimizing their content and brand to be more visible in LLMs (predominately Google’s AI overviews & ChatGPT). Most have been doing it for some time.
What I’m starting to see is a growing % now asking, “Wait, what am I getting back for all this work?” Today, all you can measure is referral traffic (people who clicked on links). What I’m hearing is the quantity of traffic you can measure directly from LLMs is < 4% of what you used to get from Google’s blue links. This is a huge change.
The interesting nuance, though: Conductor’s 2026 State of AEO Report found that visitors arriving from LLMs convert at twice the rate, in one-third the sessions, compared to traditional search. And Semrush found that brands appearing in AI Overviews saw a 9% increase in branded search volume within 90 days. So the traffic is smaller, but it’s higher intent, and it’s seeding downstream searches you might not be attributing back to AEO.
The problem is most teams aren’t set up to measure this way. 85% of marketers say AI has changed their search strategy, but only 22% have fully integrated SEO and AI search into a single measurement framework. Most are still looking at the AEO line in their analytics dashboard, seeing a small number, and questioning the investment. The real return is showing up in branded search lifts, higher-converting visitors, and pipeline influence that sits across multiple touchpoints. Much harder to measure.
There is little anyone can do about this other than OpenAI, Google, and other LLM providers. The hope is that, as these platforms begin to expand advertising within their LLMs, they’ll provide more visibility to help customers optimize their ads.
3. Paid Advertising
There is a renaissance in paid advertising. At HubSpot, we invested near zero dollars in paid advertising in our first 10 years. There was a period of time when all companies I spoke with were primarily investing in inbound marketing (SEO & Content). Paid was something they did, but wasn’t held in the same regard. It was something you had to do, but the goal was to limit the amount you spent.
AI has turned this on its head. There is a renewed focus on paid ads.
The best teams are moving to value-based bidding (telling the ad platforms what a good lead actually looks like, not just optimizing for volume). That means ingesting way more first-party data back into the platforms. They are using AI to scale creative testing, generating and iterating on ad variations at a speed that wasn’t possible before. And measurement has become meticulous about attribution, incrementality, and proving what’s actually driving revenue.
This is already showing up in real results. One SaaS company reported that AI-generated ads now drive 60%+ of their Meta spend, without buying a separate tool. An agency ran an $85k side-by-side test across clients comparing AI-generated creative against human-produced creative, and the AI ads performed comparably on ROAS, with significantly faster iteration cycles. The question has shifted from “can AI make good ads?” to “can you afford not to test at AI speed?” This is the lever most companies are pulling right now.
And it’s aligned with where the platforms are heading. Google is consolidating inventory under AI-first campaign types like Performance Max and AI Max. Meta’s Andromeda update strengthened automatic audience creation, conversion prediction, and creative adaptation. The ad platforms are essentially saying: give us your first-party data, let our AI handle the targeting and creative optimisation, and get out of the way.
4. Social/Content
AI has eaten informational content. People don’t want to read your ‘how to’ article. They want to ask an LLM. It means the focus of content has shifted from blogging to social. And like point one, it’s not easy to stand out on social.
The majority of people I spoke with are bought into ‘creator-led’ social, e.g., individuals > brand. That means there’s a lot of resources going towards founder-led content - turning your founder into a personality online / and some select employees.
LinkedIn’s own 2026 guidance makes this explicit: activate “people close to the work” and create “with people, not for them.” LinkedIn is favoring individual voices over brand accounts in the algorithm. This is the trend across all social channels, podcasts, YouTube, and community forums. And now those very things influence how you appear in the LLM results.
Creator-led content strategies are a must-have.
5. Creators
We bought theHustle (for 27m) back in 2021. Our thesis was that B2B would start to look a lot more like B2C over time. That meant the attention would start to divert from brands to individuals in the form of creators/influencers.
This was correct, and the trend is accelerating. Today, creators are a core part of HubSpot’s marketing engine. Nearly every AI-native startup I speak with prioritized their creator program before they began to look at traditional marketing channels like SEO and paid.
The numbers show how fast this is moving. Creator marketing currently accounts for roughly 5% of global advertising spend, but budgets are accelerating; CreatorIQ reports influencer marketing budgets grew 171% year over year, with nearly two-thirds of that new spend reallocated from traditional paid and digital channels. LinkedIn’s own buyer research shows 6 in 10 B2B buyers now discover new brands through creator content, two-thirds use creator perspectives during consideration, and nearly half visit a vendor site after engaging with a creator. Creators now influence a huge part of your buyers’ journey.
The challenge is, demand for B2B creators is accelerating, and the pool of B2B creators to work with is still relatively small. It’s going to result in the cost of creators increasing. And there isn’t a straightforward way to measure the return on creators. Most brands are measuring their return on impressions/engagement, as part of their brand metrics. Others would like to measure on a mix of impressions/engagement and direct conversions. An increasing number are looking for creators to help influence their positions in the LLMs, given platforms like LinkedIn, YouTube, and Reddit are widely used by LLMs to determine their results.
That last point is worth underlining. Creator content is becoming a cornerstone of how LLMs build their answers.
6. Prospecting (AI)
I’m increasingly seeing marketing go further down the funnel. Most commonly through prospecting. This has been a huge AI success story for us at HubSpot, and I see it being replicated at the most AI-pilled companies I speak with. I’d break this into three buckets:
Triggered Prospecting: this is integrating AI into your triggered email workflows against high-intent actions that result in meetings booked for your sales team. At HubSpot, we were able to drastically improve conversion rates into meetings booked using AI to personalize the copy.
BDR Prospecting: This is integrating AI to help BDRs increase their coverage by automating emails, generating call scripts, and social outreach.
SMB Prospecting: A large part of our business is selling into small companies. We don’t have BDRs in our SMB segment for obvious reasons. So, we do the same automation as point 2 for our SMB reps.
Most companies I’ve spoken with are still surprisingly early in how they’re using AI across prospecting.
7. Marketing Leadership
Nearly all founders don’t want a traditional marketing leader. They want a marketing leader who has depth of knowledge in GTM (worked in different motions), depth of knowledge in working with sales, product, and engineering, is incredibly strong in AI, is a systems builder, and isn’t a ‘brand awareness’ CMO. The profile they’re looking for is incredibly hard to find.
And the data backs this up. A recent survey of 75 SaaS CMOs found the top priorities are now pipeline, conversion, ARPU, and retention, not awareness (Gripped, 2025). That’s a different mix than a traditional CMO has been asked to own.
One founder on X put it bluntly:
“AI is changing marketing as fast as eng, so hiring a CMO who can’t IC anymore is like hiring a VPE that can’t code anymore. Personally, I just hired ‘head of’ for demand gen and appointed myself CMO. Much lower risk.” — @calcsam
Founders would rather stay as CMO themselves than hire someone who can’t get their hands dirty. CEO’s want a marketing leader who they believe can do the work.
8. AI (Native)
You’ll need to be strong in AI to get hired onto the marketing teams I’ve been speaking with. All have integrated AI into their hiring process. Many are mandating the use of AI as part of the interview process; e.g., you’ll have an exercise to complete and need to demonstrate how you used AI to solve it.
The job postings tell the story. 78% of marketing job descriptions now mention AI, but only 11% name a specific tool; employers want AI-fluent marketers, not tool specialists (Dexity, 2026). In B2B specifically, demand gen roles lead the way with 50% of postings referencing AI skills, followed by content marketing at 43%.
One hiring manager on X shared exactly the kind of exercise founders are now running:
“If I were hiring a marketer, I would make them build a micro app. I would also require them to complete the job application and prepare for interviews using AI, and provide a link to the chat thread they used to do so. This is the best way to verify that you can trust someone to use AI on the job.” — mfishbein.
Hopefully this rundown was helpful.
Until Next Time,
Happy AI’fying
Kieran