27%
of marketers report speed and agility as AI's #1 performance gain
Foreword
AI in the loop will help marketers outlearn, outmarket, and outgrow their competitors
As a marketing leader, the most valuable asset your business has today is your raw marketing intelligence. That marketing intelligence lives inside the minds of your employees, in the experiments you run, the data you get back, and the insights you get from customers.
If you’re not thinking ahead, that intelligence will leave with your best employees or, worse still, be outsourced to AI models.
As part of HubSpot's annual "State of AI" studies, we surveyed over 1,700 marketers from individual contributors to CMOs to understand how, why, when, and where they’re using AI in the marketing process. Our recent data shows that there are still massive gaps between those adopting AI at a transformational level, and those still experimenting. And many still don’t even have their teams’ data meaningfully connected to their AI tools.
In this report, we’ll break down the data. But we’ll also teach you how you can take action. Plus, you’ll find a customizable plan you can tailor to your brand. We’re here on the journey, too, and sharing results from our experiments as things evolve by the minute.
Introduction
Most teams are in the AI game, but few are winning it
To get started, we asked marketing respondents using AI to rate their company and department's level of AI adoption on a scale from "Early" to "Transformational."
Here’s how we defined each of these stages:
- Early
- AI use is still taking shape at our company. It is mostly experimental, limited to a small number of tasks or use cases, and outcomes are not yet consistent.
- Emerging
- AI is being used in real workflows at our company and is delivering value, but usage, processes, and outcomes are still evolving.
- Established
- AI is used reliably in repeatable workflows where it delivers consistent value. Teams know where it fits, how it should be used, and what outcomes to expect.
- Transformational
- AI is a foundational part of how the company operates and is materially reshaping workflows, decisions, and business outcomes.
In some summaries below, "advanced" AI usage or adoption refers to respondents who mapped their team's AI maturity level as "established" or "transformational."
Most marketing teams are using AI in some way, whether in the emerging, established, or transformational stage of adoption. However, only 10% of the marketers whose teams do use it say they are at the transformational level. There’s room to grow, and many marketing teams are widening their perspective on what AI can do for them.
Though 10% seems small, marketing is the #1 GTM function for advanced AI adoption — with maturity stages far ahead of service and sales professionals. When comparing marketing results to that of 4,000 global sales and service professionals surveyed concurrently, 42% of marketers reported advanced AI use (transformational and established) compared to 23% of service, and 27% of sales professionals.
Marketing teams are also more likely than sales or service teams to say AI is making revenue targets easier to hit. In fact, marketing leads every major AI metric, including: highest advanced AI use, highest active agent use, highest time savings, highest budget growth, strongest reported AI impact on company revenue.
72%
of marketers say AI makes it easier to hit company revenue goals and MQL targets.
65%
of marketers say AI makes it easier to hit company operating cost goals.
66%
of marketers say AI makes it easier to hit CAC targets.
Key Findings
How is AI actually changing marketing right now?
-
There’s still room to grow AI acumen
98% of marketing teams are using AI in some way, but only 10% have reached a transformational level.
-
AI helps with speed to market
Speed and agility is the #1 area where AI has improved performance.
-
Teams are employing AI agents
86% of marketing departments now use AI agents, and 76% of those say agent usage increased in the past 6 months.
-
Marketers feel threatened by AI, but it’s linked with career growth
53% of marketers are concerned AI could automate their role. But 1 in 5 transformational adopters credit AI for career trajectory gains.
-
AI skills are expected, but not required
35% of marketers say informal AI expectations already factor into hiring, performance reviews, and compensation.
-
Companies are increasing bets on marketing AI
67% of marketers say their departments have increased AI investments in the past 6-12 months.
Opportunity
AI is working,
but are you working it?
AI is helping marketing teams hit their goals, but where it supports most depends heavily on role and level of organization-wide AI adoption. Smaller companies lean on AI for individual output, but enterprise teams use it for communication and strategic impact. Early adopters are able to move faster, but advanced adopters are able to move up in their careers.
Now that AI has moved past the experimental stage, the biggest barriers holding marketing teams back from advancement are related to trust, security, and compliance concerns. This holds steady from 2025, when data privacy concerns were the biggest barrier to adopting new AI tools.
What can AI do for you?
22%
of marketers of transformational adopters credit AI for career trajectory gains — vs. 5% at early stage
For transformational AI adopters, team communication depth is almost 2x higher than all respondents. Individual contributors see gains in speed, volume, and productivity, while directors report improvements in strategic areas like business impact and team motivation.
How marketers say AI has improved performance
Speed and agility lead AI performance gains at 27%, followed by creativity at 23%.
Source: The State of AI in Marketing Report 2026 • Created with Flowerplot
| Category | Overall | Small business | Mid-market | Enterprise |
|---|---|---|---|---|
| Speed and/or agility | 27% | 27% | 25% | 31% |
| Creativity | 23% | 25% | 21% | — |
| Personal productivity | 21% | 22% | 19% | 26% |
| Volume of completed work | 19% | 20% | 19% | 18% |
| Accuracy | 18% | 20% | — | — |
| Prioritization, timeline planning, and/or resource allocation | — | — | 19% | — |
| Better problem-solving skills/capability | — | — | — | 25% |
| Insight and/or depth in team communication | — | — | — | 19% |
“In just a few months, I went from barely using AI to building a personal brand strategy that drove over 3 million impressions on LinkedIn, landing paid partnerships, and consulting with other founders. And, I did it with the help of ChatGPT. What started as a tool to help me brainstorm quickly became a career accelerator. It changed how I work, how I show up, and how I earn.”
AI maturity and goal attainment move together
The further along a company is in its AI journey, the more likely marketers are to say AI helps them hit goals. 96% of transformational adopters say AI makes it easier to hit revenue goals, compared with 74% of established, 44% of emerging, and 12% of early-stage teams. Advanced adopters also report more budget, headcount, and strategic impact from AI.
The barriers holding AI adoption back
53% of respondents are at least moderately concerned that AI could automate their role. Barriers also cluster around trust, privacy, compliance, reputation risk, and a lack of time to configure tools.
Top challenges to AI adoption
Trust, privacy, and security concerns rank as the top departmental barrier to AI adoption.
- Trust, privacy, or security concerns about AI
- Privacy, compliance, or legal restrictions limit what data we can use with AI
- Concern that AI use could harm our reputation with prospects or customers
- Lack of time to configure, train, or troubleshoot AI
- Unclear how to use AI effectively or which tools to use
Source: The State of AI in Marketing Report 2026 • Created with Flowerplot
The Loop Playbook
How HungryHungry uses AI to help hospitality venues serve guests better
Rather than replacing employees with AI, leaders are instead opting to blend AI into existing headcount — using those tools to amplify the human connection and employee performance. By leaning into HubSpot's Loop Marketing framework, hospitality tech platform HungryHungry’s one-person marketing team did just that by building a "hybrid team" where a human sets the strategy and AI executes, decreasing campaign cycles (and human time spent working on them) from quarterly to weekly.
Here’s how their AI-boosted Loop came together:
-
Stage 1
Express
Brand-specific AI agents were fed HubSpot CRM data, support tickets, and survey responses so each agent understood tone, audience, and context.
-
Stage 2
Tailor
They ran an A/B test pitting a plain-text control against a personalized video email featuring an AI-generated avatar; that variation delivered a 29% CTR against zero clicks for the control.
-
Stage 3
Amplify
HungryHungry automated the research, drafting, and delivery for approval of community social posts so they could go live within a day instead of a week.
-
Stage 4
Evolve
Quarterly campaign reviews were replaced with weekly iteration with Breeze’s performance data surfaced immediately after each campaign.
Strategy
Your AI strategy is only as strong as your intelligence layer
Most respondents we've polled across GTM say their companies want to be at an "established" AI maturity level by 2027. But notably, 1 in 5 marketers say their companies are aiming for transformational adoption.
Goal stage of AI adoption by the end of the year, by region
Nearly half of marketers (45%) aim for Established AI adoption by year-end; only 23% target Transformational.
Source: The State of AI in Marketing Report 2026 • Created with Flowerplot
| Category | Overall | North America | Europe | Asia-Pacific | Latin America |
|---|---|---|---|---|---|
| Established | 45% | 45% | 50% | 41% | 30% |
| Transformational | 23% | 28% | 17% | 22% | 33% |
| Emerging | 22% | 20% | 24% | 24% | 22% |
| Early | 7% | 5% | 6% | 9% | 11% |
| No formal goal/don’t know | 3% | 2% | 3% | 4% | 4% |
Across regions, companies in North America are more likely to anticipate reaching a transformational level of AI, while those in EMEA are most likely to have a goal of an established AI strategy.
What’s driving adoption?
60% of organizations expect some level of AI proficiency among their employees, but only 15% of respondents say that AI skill expectations are formal requirements.
Despite a lack of formal requirements, AI skills are still important for career growth.
35%
of marketers say that informal expectations of AI skills factor into hiring, performance reviews, promotions, or compensation.
Companies pursuing transformational AI should establish more documented expectations for AI proficiency, provide training, and benchmark performance.
Primary AI adoption drivers
Cost reduction and employee demand lead adoption drivers at 39% and 38% overall.
- Cost reduction or efficiency goals
- Employee demand; employees are finding AI tools valuable and advocating for them
- Competitive pressure or concern about falling behind peers or competitors
- Revenue growth goals
- Customer demand or expectations for AI-powered experiences
- Cost reduction or efficiency goals
- Employee demand; employees are finding AI tools valuable and advocating for them
- Revenue growth goals
- Competitive pressure or concern about falling behind peers or competitors
- Customer demand or expectations for AI-powered experiences
- Employee demand; employees are finding AI tools valuable and advocating for them
- Cost reduction or efficiency goals
- Competitive pressure or concern about falling behind peers or competitors
- Customer demand or expectations for AI-powered experiences
- Revenue growth goals
- Employee demand; employees are finding AI tools valuable and advocating for them
- Cost reduction or efficiency goals
- Competitive pressure or concern about falling behind peers or competitors
- Customer demand or expectations for AI-powered experiences
- Revenue growth goals
Source: The State of AI in Marketing Report 2026 • Created with Flowerplot
| Category | Overall | Small business | Mid-market | Enterprise |
|---|---|---|---|---|
| Cost reduction or efficiency goals | 39% | 38% | 39% | 39% |
| Employee demand; employees are finding AI tools valuable and advocating for them | 38% | 36% | 40% | 43% |
| Competitive pressure or concern about falling behind peers or competitors | 35% | 33% | 37% | 39% |
| Revenue growth goals | 34% | 34% | 35% | 27% |
| Customer demand or expectations for AI-powered experiences | 31% | 29% | 36% | 34% |
AI is leading to marketing team reorgs
74% of respondents believe they are proficient or fluent at using AI.
Marketing leaders report higher levels of personal AI adoption at an “established” level than managers or below. And they may be more effective in using AI, too.
Recent research found that senior-level professionals are more skilled in using AI because they push back on AI responses, whereas those who are more junior accept AI responses and “let AI think for them,” which erodes their confidence in its outputs. AI isn't making us dumber, but those who engage with it rather than trusting it blindly feel more confident in their AI-assisted work.
Most marketers say their role has changed because of AI, and only 7% say it hasn't changed at all. Even titles are changing, as companies hire or redeploy employees to certain roles.
How AI is changing marketing roles
AI roles companies are hiring or redeploying for in 2026
AEO specialists and AI coaches lead 2026 hiring plans at 36% each.
Source: The State of AI in Marketing Report 2026 • Created with Flowerplot
| Category | Overall | Small business | Mid-market | Enterprise |
|---|---|---|---|---|
| AEO specialists, strategists, content creators | 36% | 33% | 38% | 41% |
| AI coaches who train or create education resources for employees | 36% | 30% | 41% | 42% |
| AI Transformation or Adoption Executives (Chief AI Officer, etc.) | 33% | 28% | 38% | 31% |
| AI specialists who implement and scale tool adoption | 33% | 28% | 37% | 38% |
| AI governance, risk, or compliance roles | 30% | 24% | 36% | 30% |
AI is transforming marketing budgets and hiring decisions
More and more teams are experimenting with AI, and the majority are meaningfully investing in it.
69%
report an increase in company-wide AI investment in 2026
67%
report an increase in marketing-wide AI investments in 2026
As marketers work against “AI slop,” governance and data become more important, and they're top of mind for many teams, especially mid-market and enterprise teams where there are more cooks in the kitchen.
Companies are documenting AI policies and guidelines, and consistently updating them as new information comes in. In 2025, 18% of organizations had no stated policy on AI usage. In 2026, only 8% either have no AI policies at all or plan to create them. And at most companies, AI has some access to business context, but there are important gaps.
For 1 in 4 teams, data access is excellent — it's accurate, complete, reliable and easy to access. For most teams (53%), it's good. It's mostly reliable, with occasional gaps. And for 1 in 5 teams, data is either fair, with noticeable gaps, inconsistencies, or access issues, or poor, regularly hindering AI use.
Top 5 documented AI policies or guidelines at companies
Top documented AI policies by company size
Approved tools and data-sharing guidelines lead documented AI policies across company sizes.
- Approved tools / tool approval process
- Customer-facing AI use guidelines
- Data-sharing guidelines
- Data-sharing guidelines
- Approved tools / tool approval process
- Customer-facing AI use guidelines
- Approved tools / tool approval process
- Data-sharing guidelines
- Customer-facing AI use guidelines
Source: The State of AI in Marketing Report 2026 • Created with Flowerplot
| Category | Small business | Mid-market | Enterprise |
|---|---|---|---|
| Approved tools / tool approval process | 38% | 43% | 48% |
| Customer-facing AI use guidelines | 36% | 38% | 38% |
| Data-sharing guidelines | 30% | 43% | 43% |
Accessibility of data available to support AI use cases and deployments
For 1 in 4 teams, data access is excellent; for most teams (53%), it's good.
- Excellent 25%
- Good 53%
- Fair 19%
- Poor 3%
Excellent: Data is accurate, complete, reliable, and easy to access. Good: It's mostly reliable, with occasional gaps. Fair: Noticeable gaps, inconsistencies, or access issues. Poor: Regularly hindering AI use
Source: The State of AI in Marketing Report 2026 • Created with Flowerplot
The Loop Playbook
How First Alliance Credit Union cut launch times and creates member-driven content with AI
Minnesota-based credit union, First Alliance Credit Union has a lean marketing team that was taking too long to go from idea to launch. With HubSpot, they rebuilt their content operation to be more automated and personalized to actual members.
Here’s how their AI-boosted Loop came together:
-
Stage 1
Express
The team built a long-form video podcast as the source for all content, with their staff as subject-matter experts, that they used Content Remix to repurpose across channels.
-
Stage 2
Tailor
The team uses HubSpot’s persona-driven campaign tools to check if they can fill a need with existing content before creating anything new, and A/B test every send.
-
Stage 3
Amplify
Content Remix turns each podcast episode into an audio episode, four short-form social videos, and two full blog posts, all from a single recording session.
-
Stage 4
Evolve
The team now reviews content performance like views, downloads, engagement, and forecast versus actual weekly, a habit that didn't exist before the data did.
Use cases
AI is integrated in marketing workflows. Here’s where it’s moving the needle.
Marketers have gotten comfortable outsourcing tasks to AI to lighten their load and produce content at a faster pace. Content (tailoring and producing) leads narrowly as the main use case, but campaign planning, web development, and brand positioning are close behind. What's marketing not using AI for? Handing off leads to sales, coaching and skill development, and identifying and defining target buyers.
Marketing tasks using AI in 2026
AI starts as a content creation assistant, and grows to a strategic collaborator
SMBs lean hardest on AI for content creation, while midmarket and enterprise companies are more likely to use AI for strategy and planning briefs, suggesting AI becomes more of a thinking tool and less of a production tool as organizations grow. The same can be said when looking at early vs. transformational adopters: AI starts as a writing assistant and matures into a strategic collaborator.
Top ways AI assists with marketing content creation
Small businesses and early-stage adopters lean hardest on AI for drafting copy, while enterprise and transformational teams lean on it for strategy and planning briefs.
- Small business
- Mid-market
- Enterprise
- Early
- Emerging
- Established
- Transformational
- B2B
- Mix B2B/B2C
- B2C
Source: The State of AI in Marketing Report 2026 • Created with Flowerplot
| Category | Overall | Small business | Mid-market | Enterprise |
|---|---|---|---|---|
| Drafting or editing copy | 36% | 38% | 34% | 33% |
| Image/video generation or editing | 33% | 37% | 31% | 24% |
| Topic brainstorming | 30% | 32% | 28% | 29% |
| Strategy or planning briefs for individual pieces | 29% | 28% | 30% | 33% |
| Channel-specific optimization (SEO, AEO) | 27% | 25% | 29% | 30% |
| Category | Overall | Early | Emerging | Established | Transformational |
|---|---|---|---|---|---|
| Drafting or editing copy | 36% | 41% | 37% | 34% | 30% |
| Image/video generation or editing | 33% | 27% | 35% | 32% | 40% |
| Topic brainstorming | 30% | 28% | 30% | 29% | 31% |
| Strategy or planning briefs for individual pieces | 29% | 24% | 27% | 31% | 40% |
| Channel-specific optimization (SEO, AEO) | 27% | 19% | 25% | 34% | 28% |
| Category | Overall | B2B | Mix B2B/B2C | B2C |
|---|---|---|---|---|
| Drafting or editing copy | 36% | 31% | 41% | 38% |
| Image/video generation or editing | 33% | 30% | 38% | 33% |
| Topic brainstorming | 30% | 29% | 34% | 28% |
| Strategy or planning briefs for individual pieces | 29% | 29% | 33% | 26% |
| Channel-specific optimization (SEO, AEO) | 27% | 27% | 29% | 26% |
AI is everywhere in marketing channels, but best where personalization is possible
By channel, marketers use AI most in email, but when it comes to hyper-personalization, they’re using it for online advertising and social. The teams most successfully implementing intelligent personalization are using AI to gather insights about their audiences.
35%
of marketers say they use AI most for email and newsletters when it comes to channel work
32%
of marketers say online advertising and social are where AI personalization shows up most
Marketers aren’t fully outsourcing personalization to AI
Gathering insights about audiences leads personalization use cases at 31%, with ideation and targeting tools close behind. Teams still keep humans in the loop for judgment, brand taste, and final delivery.
How marketing teams use AI to support personalized or segmented marketing experiences
Gathering audience insights leads personalization use cases at 31%.
Source: The State of AI in Marketing Report 2026 • Created with Flowerplot
Transformational adopters are 3x more likely than early-stage teams to say AI personalization is driving stronger campaign performance.
Learn how to craft effective AI prompts for personalized marketing
The Loop Playbook
How Sandler drove 4x more sales leads by walking the AI walk
Corporate sales and business development training company Sandler stayed competitive in an AI-driven market while preserving human-first service using HubSpot's Breeze to create hyper-personalized experiences.
Here’s how their AI-boosted Loop came together:
-
Stage 1
Express
Sandler used Breeze to unify tone of voice and messaging across every channel.
-
Stage 2
Tailor
The team built hyper-personalized content tailored to specific personas and industries, and campaign development time dropped from weeks to days.
-
Stage 3
Amplify
Sandler turned their internal adoption into a proof point for their customers, which accelerated client pipeline.
-
Stage 4
Evolve
HubSpot's A/B testing and reporting tools helped the team validate and continuously refine AI-driven content, creating an ongoing loop of improvement.
Tools
How AI-forward teams are building their marketing tech stack
Despite all the Claude hype on LinkedIn, ChatGPT leads among AI tools. And this year, agents are everywhere and the teams moving fastest share one trait: they're choosing tools that are easy to use, integrate well, and protect their data.
Marketers are using a mix of AI tools and agents
ChatGPT has become the default starting point for most marketing teams, used by more than half of all respondents. But the stack is diversifying fast, with design AI (Canva), productivity AI (Microsoft Copilot), and creative generation tools (Adobe Firefly, CapCut) all gaining traction.
As company size climbs, Microsoft Copilot becomes more popular (22% at SMB, 21% at midmarket, and 39% at enterprise). Meanwhile, Claude indexes strongest at SMB (22%) and falls off sharply at enterprise (15%), suggesting it's a tool that smaller, more agile teams are adopting.
Companies in the transformational stage of AI adoption use more of everything, but the standout is Microsoft Copilot, which hits 31% (vs 19% at the early stage of AI adoption). ChatGPT is at 55–62% across all stages, confirming it's truly universal. It's worth noting that Microsoft Copilot and Google Gemini's high rankings likely reflect their deep integration into software suites most companies already use; these tools were already accessible before the AI boom, not necessarily chosen for AI specifically.
86%
of marketers indicate that their departments use agents
76%
of marketers who use agents saw agent usage increase in the past 6 months
37%
of HubSpot customers use built-in AI “much more often” vs. non-customers
AI tools currently in use
ChatGPT remains the dominant AI tool at 88% in 2026, with Gemini and Copilot next.
Source: The State of AI in Marketing Report 2026 • Created with Flowerplot
| Category | 2025 | 2026 |
|---|---|---|
| ChatGPT | 88% | 88% |
| Google Gemini | 52% | 52% |
| Microsoft Copilot | 44% | 44% |
| Meta AI assistant | 28% | 28% |
| Deepseek | 17% | 17% |
| Claude | 11% | 11% |
| Perplexity | 10% | 10% |
AI agents currently in use
ChatGPT and HubSpot lead agent usage among marketing departments.
- ChatGPT
- HubSpot
- IBM
- Salesforce
- Claude
Source: The State of AI in Marketing Report 2026 • Created with Flowerplot
Most teams are running 2–3 agents, but power users are scaling fast
In 2025, we found that one in five marketers planned to explore AI agents for end-to-end autonomous marketing. Now, two in five use 2-3 agents, and a growing cohort (14%) are managing 7 or more. Agent orchestration is becoming a core marketing competency. The teams scaling to multiple agents are the same ones reporting more significant gains in speed, creativity, consistency, career trajectory, depth in team communication, and goal attainment.
How many AI agents marketing departments are using
Most marketing departments run 2–3 agents (45%), with another 32% running 4–6.
- 2-3 agents 45%
- 4-6 agents 32%
- 1 agent 8%
- 7-9 agents 8%
- 10 or more agents 6%
- I don’t know 1%
Source: The State of AI in Marketing Report 2026 • Created with Flowerplot
Ease of use beats everything when teams choose AI tools
When recommending or approving AI tools for investment, marketers prioritize usability above all else. Friction in the onboarding process is still the primary barrier teams are trying to solve.
Data privacy and integration capabilities follow close behind. It’s becoming more complex to manage AI across connected marketing systems, leaving marketers to rely more on operations teams.
When looking at company size, enterprise companies prioritize demonstrated ROI and ease of governance more than SMBs. Larger orgs have higher accountability and oversight demands. Speed matters least to enterprise teams.
As the ones actually using the tools daily, marketing managers weigh ease of use and quality of output more heavily than directors. Directors and above lean more on vendor trust, vendor innovation confidence, and agentic capabilities, factors that reflect longer-term strategic bets rather than day-to-day usability. The biggest gap is vendor trust: directors are more likely to cite it than managers. Purchasing decisions at senior levels are about relationships and reputation.
The Loop Playbook
How Crunch Fitness used Breeze agents to build emails
Fitness studio brand Crunch Fitness solved their challenge of empowering 50+ franchise teams to run personalized, local marketing at scale by building their marketing engine on HubSpot's Marketing Hub.
Here’s how their AI-boosted Loop came together:
-
Stage 1
Express
The team at Crunch used Marketing Hub to build a branded campaign system that gave every franchisee a consistent Crunch voice.
-
Stage 2
Tailor
Franchisees could run region-specific campaigns built around local events, member behaviors, and seasonal promotions, speaking directly to their neighborhoods.
-
Stage 3
Amplify
Franchisees launched campaigns independently, sending 15M+ targeted emails every month and capturing millions of leads.
-
Stage 4
Evolve
With full autonomy to test and optimize, each franchise team iterates on what works for their market.
Loop Marketing
Get in the Loop
Here's how to apply the findings from this report to your marketing strategy using the Loop Marketing framework.
Stage 1
Express who you are
81%
use AI to document brand positioning, build briefs, align content to their brand position, and/or market research.
Strategy
Define your brand voice, positioning, and point of view, then use AI to express it consistently across every channel and format. AI can produce content at scale, but only if it knows what you stand for.
AI prompts/agents
Use Breeze Brand Voice to align AI-generated content with your brand guidelines before publishing.
Stage 2
Tailor your approach
24%
of marketers use AI to tailor content to specific channels and the audiences using them.
Strategy
Use AI to understand your audiences, then deliver experiences that feel built for them. The teams connecting here are using AI insights along with human judgment.
AI prompts/agents
Use Breeze Customer Agent to answer visitor questions and guide high-intent traffic to the right content and experiences.
Stage 3
Amplify your reach
44%
of marketers use AI to produce content in general or develop and design web pages, amplifying their message across channels.
Strategy
Extend your best content across channels without proportionally growing your team. AI enables one piece of content to become five, and one campaign to span twelve touchpoints.
AI prompts/agents
Use Breeze Social Media Agent to generate channel-specific posts optimized for each platform's format and audience.
Stage 4
Evolve in real-time
40%+
of marketers use AI to learn and adapt to data, and 38% use AI to drive conversion.
Strategy
Extend your best content across channels without proportionally growing your team. AI enables one piece of content to become five, and one campaign to span twelve touchpoints.
AI prompts/agents
Use Breeze Intelligence to automatically surface performance insights and recommended next actions after each campaign.
“Loop meets customers everywhere they are, uses AI to personalize each message at scale, and turns every interaction into a learning opportunity that makes the Loop stronger.”
Kipp Bodnar, Chief Marketing Officer of HubSpot &
Co-Author of
“Loop: Outlearn, Outmarket, Outgrow”
Closing
The intelligence era of AI marketing is here
There’s still a wide gap between teams experimenting with AI and teams running it as a connected system. The difference is proprietary data, documented strategy, and a Loop playbook that moves from Express to Tailor to Amplify to Evolve. The intelligence era of marketing has arrived. Own yours.
Methodology
HubSpot conducted a survey in June 2026 with a total of 1,754 marketers across North America, Europe, Asia, Australia, and Latin America across seniority levels and industries to gain these data points.
Report created in collaboration with Datalily.
AI rewrote the rules. We made them into a book.
The marketers winning right now aren’t using the most AI. They have the best taste. Loop turns that into a system: a four-stage operating model (Express, Tailor, Amplify, Evolve) built and proven on HubSpot’s own org.
