AI in Marketing: What Marketers Really Think

To say that AI would be the future of marketing might’ve been true about five years ago. But now, AI has surpassed the visionary phase on the adoption curve, and marketers are more deliberately implementing it into their daily workflows. 

We wanted to know how our fellow marketers traverse this space, so we asked them. The survey received 127 responses from our audience around the globe. We learned that well and truly beyond its seedling phase, AI is consolidating its place in marketers’ turf — but not always in the ways you’d expect.

Who Took This Survey?

Company HQ Location

Responses: 121

We managed to rustle up insights from all around the world and across industries ranging from Tech and Construction to Wellness and Finance.

Industry

Responses: 120

• Marketing & media: 25
• Professional & business services: 14
• Manufacturing & industrial: 11
• Construction & architecture: 9
• Nonprofit & social services: 8
• Software & SaaS: 8
• Technology & IT: 8
• Education: 7
• Finance & insurance: 6
• Health & wellness: 6
• Ecommerce & online services: 3
• Hospitality, travel & events: 3
• Real estate: 3
• Agriculture & food: 2
• Beauty & personal care: 2
• Other: 12

Primary Job Function

The majority of responses (60.3%) came from mid-to-high-level marketing management, followed by individual contributors (27.8%). This indicates that most of our insights come from marketing decision-makers and their teams, with a sprinkling of perspectives from high-level management. 

Seniority

Almost three-quarters (72.2%) of respondents have been in the industry for over 6 years. Many of these respondents can offer key insights and sentiments into the foundational changes in marketing practices since the AI boom, circa 2020. 

Work Arrangement

Most respondents are on the move, working in hybrid (44.8%) or remote (36.6%) environments. This points to an increasingly global marketing landscape, where innovation and digital-first uptake (including AI) are firing on all cylinders.

Company Size

Respondents represent companies with between 1 and more than 501 employees.

Key Takeaways From the Survey

AI Adoption Is Nearly Universal

101 out of 127 people surveyed said they were using AI in the workplace in some capacity. Clearly, it’s becoming a standardized tool rather than an experimental novelty. Marketers implementing AI say they use it because:

• AI increases output.
• It enhances what they’re already doing. 
• It can expedite manual tasks. 
• AI is a great brainstorming tool.
• It makes scaling easier.

Who is using AI? The biggest adopters included respondents who:

• Worked at mid-to-large companies: 85% of organizations with 50-500 employees said they were using AI compared to 79% of total respondents.
• Had 6-10 years of experience: 84% of respondents in this camp said they were using AI compared to 76% of those with 11 or more years of experience and 80% of both entry-level (0-2 years) and intermediate employees (3-5 years).
• Held marketing management roles: 83% of respondents who said they were a marketing manager or director said they were using AI compared to 73% of CEOs and executives, and 74% of individual contributors.
• Either worked fully remote or hybrid: 80% and 82%, respectively, said they were using AI compared to 74% of fully in-person employees who said the same.
• Worked for an American company: While the majority of our respondents overall were from the United States, a greater proportion of Americans (83%) said they were using AI compared to other countries. In the UK, our second-most common country in the study, just 74% of respondents said they were using AI.

Notably, of the 127 respondents, 20.5% do not currently use AI in the workplace, which we’ll get to later on. The following data summarizes responses from those who do:

AI’s Sweet Spot Is Content Creation

It’s no shocker that content drives AI in marketing. The highest responses received for AI usage are as follows: 

• Research and planning (77.2%).
• Outlining (67.3%).
• Creating metadata and headlines (66.3%).
• Main copy production (60.4%).

This shows that marketers are using AI to automate manual or repetitive tasks, employing generative AI tools as content assistants. These are all good uses for AI — and some of the most natural ones that marketers gravitate towards. However, while implementing AI for these purposes, it’s necessary to keep quality standards in mind and make space for human reviews. Just 1% of respondents use AI for editing or proofing work. 

Surprisingly, there is a remarkably low uptake for image generation, with just over a third of respondents creating visual marketing assets with AI tools. This indicates that marketers may still be traumatized by the early-day seven-fingered outputs of Generative AI. Less surprising is the 96% of respondents who don’t use AI for video and audio assets, reflecting nascent capabilities in the space. 

Data Analysis? Not So Much

Under the sheath of creativity and productivity, marketers want to automate. But they’re also concerned about feeding proprietary information to the beast, which, for many, represents the winning argument in the data analysis dichotomy.

We learned that 35.6% of respondents analyze data by compiling and loading it into ChatGPT or another AI tool. A further 16.8% use integrated capabilities within applications, such as Hubspot or Salesforce. 

When doing this, it’s crucial to understand data security and privacy as it relates to company policies and platform capabilities to ensure you’re not compromising sensitive or private information. This may be particularly important in industries including, but not limited to, health care, financial services, education and government. 

Free vs. Paid AI: The Divide

Marketers love a good deal, but when they pay, they go all in. Most respondents either use free tools (37%) or have invested in dedicated AI tools (44%). We were surprised to see only a small number of people relying on AI tools baked into existing software.

AI Output Handling and Challenges

Most People Review AI-Generated Content (Thankfully)

Most people review and revise AI-generated content outputs before publishing — and we’re happy to see this. Here’s a glimpse into respondents’ review processes:

• Edit generated copy for clarity and tone before publishing (77%).
• Inspire content or develop a jumping-off point for human creatives (72.3%).
• Fact check and proofread all generated copy before publishing (65.3%).
• Use generated copy as-is (1%).

Almost everyone proofreads, fact-checks and revises AI output — except for one lone respondent who lets AI fly as-is. Bold move. We do not recommend unleashing raw AI content into the wild. Granted, this respondent also checked the other boxes for proofing and fact-checking, so it seems they revise their AI-generated content at least some of the time.

Top AI Challenges Are the Usual Suspects

The top 3 challenges for creating high-quality AI content are all too familiar for most marketers. Interestingly, these point to challenges in processes, outputs and a combination of the two. They are:

1. Writing effective prompts (72%).
2. Personalizing content (54%).
3. Producing specific formats (e.g. eBooks vs. social media posts) (24%).

Other challenges, comprising 17% of responses, are related to voice (authenticity, repetition), trustworthiness (misleading or incorrect results, limited understanding of niche markets), copyright concerns and time consumption. One respondent mentioned AI overload, with too many AI tools having unique user interfaces that take time to learn. Some marketers commented that they are developing their own models to help navigate these obstacles. 

Ultimately, these challenges reflect an interdependent relationship between marketing and AI. Tools help marketers respond to existing challenges in the industry, like an increased need for automation and productivity, while simultaneously driving new pain points in the space, such as an increased need for personalization and accuracy. Which brings us to an even bigger concern: The outputs are underwhelming. 

The Big Concern: AI’s Output Is … Meh

Most marketers agree that AI-generated content is bland or generic. Almost half (42.4%) find it thin or irrelevant. Because AI’s data is not necessarily based on the most recent information to hit the web, 26.3% of marketers deal with outdated references or information — all of which detract from productivity gains. So what gives? 

One insightful respondent noted that using generative AI for content creation didn’t introduce any concerns that they wouldn’t already need to address with a human writer — i.e., being clear about expectations, providing examples and through project briefing.

“It’s all about the prompt/brief, giving clear tone of voice and brand guidelines, with previous examples of content I’ve created. AI does a much better job of achieving a consistent tone of voice than using more than one copywriter for a large project/campaign.”

Marketers also worry about hallucinations — AI confidently spurting off what is effectively gibberish — something we’re less likely to see among decent writing hires. But ultimately, we’re seeing that standalone AI content still doesn’t address Experience, Expertise, Authoritativeness and Trustworthiness (E-E-A-T) principles, personalization or depth. It’s off-center with current marketing expectations and still requires invaluable human input. 

AI Policy

AI Policies? What AI Policies?

Nearly three-quarters of those who were using AI don’t actually have a policy on its usage. This was also surprising, given that marketers expressed concerns surrounding copyright, sharing proprietary information and accuracy. Companies that have implemented AI policies tend to focus on: 

• The type of data that marketers can/cannot feed into AI (59.3%). 
• The type of tasks AI is allowed to handle (55.6%). 
• Whether AI-generated content needs to be disclosed (48.1%). 
• Which AI tools can and cannot be used (40.7%).

Notably, only 3.7% said their AI policy focuses on data security, ethics and consequences.

Having AI policies in place establishes clear boundaries and fair-use guidelines for marketers, encouraging responsible adoption. These policies should be living documents that evolve alongside tech developments and use cases, rather than a one-and-done deal.

AI Policies Impact on AI Adoption

According to respondents who had AI policies, the positive impacts of adopting AI policies outweigh the negatives. Some of the positive impacts mentioned include:

• Encourages AI adoption: Some policies have encouraged experimentation with AI within corporate structures.
• Increases security: Policies help establish security measures, making AI usage safer.
• Sets expectations: AI-related expectations with clients and partners are better aligned.
• Improves visibility: Policies provide transparency about AI’s role in business processes.
• Enhances best practices: They guide AI usage through structured frameworks and responsible adoption.
• Reduces production time: AI helps streamline content creation, though human input is still necessary.

On the other hand, a handful of respondents mentioned negative impacts of enacting AI policies, including:

• Limits AI usage: Some policies restrict AI-generated content in specific formats.
• Minimal or no impact: Many respondents reported little to no direct effect from AI policies.
• Too soon to tell: Some organizations are still assessing the impact of AI policies.

This unveils a key tension in AI adoption: structure versus flexibility. While policies create guardrails that encourage security and transparency, they can also stifle innovation by limiting AI’s full potential. The fact that some respondents report no impact suggests policies may be more performative than practical — or that AI adoption is moving faster than regulation. As marketers refine AI strategies, the challenge lies in balancing governance with innovation, so that policies can facilitate progress rather than hinder it.

Who Isn’t Using AI (Yet)?

Out of 127 respondents, 26 said they aren’t using AI at all. Respondents not using AI were more likely to work in:

• Nonprofit & social services: 3-in-8 respondents said they were not using AI.
• Manufacturing & Industrial: 4-in-11 respondents said they were not using AI.
• Beauty & personal care: Both respondents in this category were not using AI.

We asked them why:

• Data privacy concerns.
• Lack of AI training.
• Available tools don’t suit company needs.
• No AI budget.

Two respondents who do not use AI noted environmental concerns and ecological impact, indicating individual and company-wide preferences for not adopting AI are highly nuanced, and can be influenced by broader company goals and values. 

“We don’t need to sacrifice the planet using that much electricity just to come up with a way to talk to our clients.”

Among the same group of those not using AI, 28% are planning to adopt it this year. Another 52% are unsure if their company will adopt AI in 2025. This indicates that there’s potentially a lack of communication between company leaders and employees.

Differing Perspectives on the Future of AI in Marketing

We were fortunate enough to receive a diverse spread of commentaries and thought-provoking insights from respondents. Here, we see a clear division in perspectives that highlight enthusiasm, skepticism, caution and all-in regarding the future of AI. 

Here’s what people had to say: 

“AI is only going to grow, so my outlook is to learn how to use it and embrace it.”

“It can only grow but it can’t replace human ability to make context-specific judgments.”

“I think people vastly overrate its importance and it’s a bubble that’s going to burst soon.”

“I think a decade from now, people will look at company artwork from the mid-20’s and it’ll look very identifiable just because of the AI adoption trends related to images.”

“Right now, there’s a wild west approach to adoption (and the sheriff and deputy are nowhere to be found).”

Conclusion

AI in marketing is not a speculative future. Many marketers are grabbing the bull by the horns — albeit some more readily than others. While marketers embrace AI to polish their workflows and boost productivity, challenges surrounding content quality, data security and governance concerns remain.

The divide between AI’s potential and its limitations is clear, and marketers must balance these factors carefully. Looking ahead, the key to AI’s sustained impact lies in its ability to adapt to marketing demands while integrating with human creativity. As AI continues to shape the marketing landscape, how professionals refine their use of these tools, keeping innovation and integrity at the forefront, is likely to define the next chapter.

Keep Exploring Our AI in Marketing Insights

Check out the rest of our survey outcomes series:

• Marketing in the Age of AI: Who’s Leading the Charge?
• Who Isn’t Using AI in Marketing Yet? (And Why Not?)
• Marketers’ Outlook on AI: From Optimism to Skepticism
• The 4 Biggest Challenges in AI Content Creation (+ How To Solve Them)
• AI Policies? Here’s What Companies Are (and Aren’t) Doing in 2025

Note: This article was originally published on brafton.com.