AI content creation has moved from experimentation into everyday marketing and creator workflows. HubSpot’s 2025 AI Trends for Marketers reports that 66% of marketers globally use artificial intelligence in their roles, while 91% of marketing leaders say employees or teams at their organization use AI to assist with their jobs. Adoption is broad, but the data also shows that human review, quality control, privacy, and integration remain central to publishing responsibly.
Table of contents
- AI adoption across marketing
- How marketers use AI to create content
- Productivity, quality, and return on investment
- Review, accuracy, and operational barriers
- Creators and the expanding content workflow
- Audience experience and content management
- Future outlook and market scale
AI adoption across marketing
The current pattern is organizational rather than purely individual. HubSpot’s 2025 survey found that 82% of marketers said their company invested in automation tools for employees to use in their roles. The same source reported that 66% said their organization builds internal AI tools specifically for marketing teams. Half of marketing leaders said their organization at least somewhat supports marketers using AI in their roles.
Expectations are also rising. In the HubSpot 2025 data, 65% of marketing leaders planned to increase investment in AI and automation tools over 2025. Another 65% of marketing directors believed most software they use would have AI or automation capabilities built in by 2030. Two-thirds of marketers expected most people to use a generative AI tool such as ChatGPT to assist them in their jobs by 2030, and 67% believed AI would significantly affect how they did their jobs in 2025.
Earlier HubSpot research shows how quickly the strategic conversation developed. In HubSpot’s 2023 AI Trends for Marketers, 82% of marketers said generative AI had already affected how they planned to create content in 2023, and 69% said AI was important to their overall content strategy. That 2023 measurement should be read as a historical snapshot, not as an independently verified current estimate.
How marketers use AI to create content
AI content creation includes a range of tasks, from research and quality checks to drafting and visual production. HubSpot’s 2025 survey found that 52% of marketers used generative AI for text-based content creation, including blogs, ebooks, and marketing email copy. The same report found that 53% used it for content quality assurance such as spellcheck, accessibility review, or writing recommendations, while 48% used it for research such as market research, finding datasets, and summarizing articles.
The figures suggest that assistance is more common than full automation. In the same HubSpot data, 50% said they were writing copy for marketing content with generative AI, 48% were creating images with AI art tools, and only 4% were using AI to write entire pieces of content for them. Forty-one percent used generative AI to automate direct brand messaging and conversational marketing.
| Content or workflow use | Share reported | Source and period |
|---|---|---|
| Text-based content creation | 52% | HubSpot, 2025 AI Trends for Marketers |
| Content quality assurance | 53% | HubSpot, 2025 AI Trends for Marketers |
| Research and summarization | 48% | HubSpot, 2025 AI Trends for Marketers |
| Marketing copywriting | 50% | HubSpot, 2025 AI Trends for Marketers |
| AI image creation | 48% | HubSpot, 2025 AI Trends for Marketers |
| Entire pieces written by AI | 4% | HubSpot, 2025 AI Trends for Marketers |
Tool categories show a similar mix of creative and conversational work. Forty percent of marketers chose image and design generators as their top AI tool category, while 39% used chatbot tools such as ChatGPT, Gemini, or Copilot. HubSpot also reported that 50.77% used AI for email marketing and newsletter platforms, 50% used AI for text-based social media content, and 47% used it to create blog posts, articles, and other long-form content.
The 2023 HubSpot research recorded narrower use cases: 39% used generative AI to write copy, 31% used AI to create social media posts, 25% used AI to create emails by expanding a few paragraphs, and 18% used it to create outlines. In that same historical survey, 35% used AI to create an SEO-driven content strategy.
Productivity, quality, and return on investment
The strongest case for AI content tools is often time recovered for higher-value work. HubSpot’s 2025 figures show that 79% of marketers agreed AI and automation tools helped them spend less time on manual tasks. Seventy-three percent said the tools helped them spend more time on the most important parts of their role, and 66% said they helped them spend more time on creative aspects of their jobs.
Among marketers using generative AI to make content, HubSpot’s 2023 research found average savings of more than three hours per piece. That group also reported favorable quality and performance perceptions: 89% said generative AI improved content quality, and 63% said AI-assisted content performed better than content made without it.
ROI results were positive but not uniform. HubSpot’s 2025 survey found that 75% of leaders whose organizations invested in AI said the investment produced a positive ROI, while 4% said it produced a negative ROI. By content type, 63% saw at least somewhat positive ROI from AI-generated email content, 67% from AI-generated social media content, and 68% from AI-generated blog or long-form content.
Deloitte Digital’s generative AI transformation research reported that generative AI users saved an average of 11.4 hours per week, while early adopters reported a 12% return on generative AI investments. Deloitte also found that the volume of content needed to be produced had increased by 54% in the previous year. These figures describe the surveyed populations and reported outcomes; they do not establish a universal return for every organization.
Review, accuracy, and operational barriers
AI assistance does not remove the need for editorial judgment. HubSpot’s 2023 survey found that AI content was not complete enough to publish on its own 96% of the time. Among marketers using generative AI to make content, 53% made minor edits before publishing, 45% made major edits, 20% changed the generated text completely, and 5% made no edits whatsoever.
Accuracy is a persistent concern. In HubSpot’s 2025 research, 46% of marketers said they were only somewhat confident they would know if generative AI information was inaccurate. The same percentage appears in a separate HubSpot item measuring confidence in detecting inaccurate GenAI output.
Adoption barriers extend beyond factual accuracy. Forty-two percent of marketers said data privacy concerns had prevented their team from adopting new AI tools in the past year. Thirty-nine percent said the time and training required for new AI tools created a barrier, and 35% said there were too many similar AI tools that did not connect to one another.
Deloitte Digital found that 65% of companies were very or extremely concerned about intellectual property or legal risks from generative AI. Adobe’s 2024 Digital Trends Content Creation and Management in Focus reported that 57% saw ensuring quality and customer trust as a significant challenge in managing AI-generated content. Another 54% cited workflow issues, and 50% cited team readiness or skills.
Creators and the expanding content workflow
Adobe’s Creators’ Toolkit Report 2025 shows especially high adoption among creators: 86% actively used creative generative AI. Seventy-six percent said it had accelerated the growth of their business or follower base, 81% said it helped them create content they otherwise could not have made, and 85% believed it had positively affected the creator economy.
Creators use these tools across the production cycle. Adobe reported that 55% used creative generative AI for editing, upscaling, and enhancement; 52% used it to generate new assets such as images and video; and 48% used it for ideation and brainstorming. Sixty percent had used more than one creative generative AI tool in the previous three months.
The creator workflow is also becoming more mobile. Adobe found that 72% of creators frequently created content on mobile at the time of the survey, while 75% expected to produce more content on mobile in the following year. Seventy percent were optimistic or excited about agentic AI, and 85% would consider using AI that learned their creative style. Fifty-one percent wanted AI to automate repetitive tasks, 50% wanted help brainstorming content ideas, and 44% wanted AI to surface content performance insights.
Trust and access remain important limits. Sixty-nine percent of creators were concerned about their content being used to train AI without permission. High cost was a barrier for 38%, unreliable output quality for 34%, and uncertainty about how the AI model was trained for 28%. Creators most often found new creative AI tools through personal research at 58%, social media trends at 57%, and recommendations from other creators at 41%.
Audience experience and content management
AI content production is connected to a broader problem: making content useful and timely for audiences. Adobe’s AI and Digital Trends in Content Creation and Management reported that two-thirds of brands were not giving customers the right content at the right moment. At the same time, 78% of consumers expected a seamless experience at every touchpoint, and 80% said seamless interactions across digital channels were important or critically important.
Personalization must be relevant rather than merely observant. Adobe’s 2024 research found that 60% of consumers became frustrated with brands that knew a lot about them but did not take their preferences into account. Among senior executives, 46% prioritized customizing content for different customer segments in 2024.
The operational priorities are measurable. Adobe reported that 52% of practitioners sought better use of analytics and insights for content performance, 38% wanted to consolidate or integrate content and marketing tools, and 31% wanted to increase the pace and volume of production. Seventy percent believed a key generative AI use case would be optimizing campaign performance through testing and analysis; 45% planned to use it to streamline creative workflows and asset production, and 61% anticipated using it for metadata enhancement such as tagging assets and enriching alt text.
Future outlook and market scale
The adoption gap is visible across regions and organizational maturity. Microsoft’s AI Diffusion Report measured generative AI use by 17.8% of the world’s working-age population in Q1 2026, up from 16.3% in Q4 2025. Switzerland was at 37.8% in Q1 2026, up from 34.8% in Q4 2025. The Global North measured 24.7%, compared with 14.1% in the Global South.
McKinsey’s State of Marketing Europe 2026 reported that 94% of European marketing organizations had yet to advance their generative AI maturity. The 6% of mature organizations reported 22% efficiency gains and expected those gains to reach 28% within two years. In McKinsey’s State of AI 2025, 71% of organizations used generative AI in at least one business function, 63% of organizations using it created text outputs, and more than one-third generated images. Only 27% said employees reviewed all generative-AI-created content before it was used, while 47% had experienced at least one gen-AI-related consequence.
Longer-range estimates are larger than current adoption figures. McKinsey estimated that generative AI could contribute up to $4.4 trillion in annual global productivity, with marketing and sales among four functions that could capture an estimated 75% of that value. Marketing productivity alone could increase by 5% to 15% of total marketing spend, an uplift McKinsey valued at about $463 billion annually.
McKinsey also estimated that generative AI may power as much as two-thirds of current marketing activities. Its agentic AI analysis projected 10% to 30% revenue growth from hyperpersonalized marketing and suggested that agentic systems could accelerate campaign creation and execution by 10 to 15 times. These are estimates and forecasts, not measured outcomes for every content team.
The practical direction is clear in the available statistics: AI is expanding research, drafting, editing, production, and analysis, while effective content operations still depend on review, integrated tools, reliable outputs, privacy safeguards, and a clear understanding of audience needs.