Who Isn’t Using AI in Marketing Yet? (And Why Not?)

With all the talk around artificial intelligence (AI) today, it’s easy to think everybody’s on board with this new technology. But is this true? Just how many marketers are using AI? 

At Brafton, we decided to find out. We asked 127 marketing professionals a series of questions regarding their relationship with AI. The responses we received paint a fairly clear picture.

How Many Marketers Use AI?

The answer: most.

Of our 127 respondents, 101 said their company uses AI in its marketing processes. That’s 79.5% of respondents — basically 4 out of 5. This suggests AI has achieved widespread adoption. 

Will This Number Grow?

Not only will it grow, it’s probably growing as we speak. 

We asked those who said “No” if their companies have plans to adopt AI marketing processes in 2025. Of the 25 who responded, 28% said yes. Furthermore, 52% were unsure, so their companies might well integrate AI solutions and functionalities into their marketing this year, too. 

These responses are in line with other research on the AI market. McKinsey found that 92% of companies plan on increasing their AI investments, but only 1% felt they had fully integrated AI into their workflows. Findings such as these suggest that AI is already very popular and important, and its significance will very likely increase.

Those Who Said “No.”

The other 20% said “No.” We’ll get into the reasons for their responses in a bit, but it’s worth discussing the technology adoption curve.

We all adopt new technologies at our own pace. Maybe you bought the first-generation iPhone in 2007, or maybe you were still taking 10 minutes to write a 3-sentence text message on your awesome flip phone until 2013. In this case, the smartphones clearly won out (or did they?), but there were perfectly legitimate reasons to not buy a smartphone in the 2000s.

Unless you were an innovator or early adopter, you may have been scared off by the cost of smartphones, or maybe you didn’t want to learn how to use them. Or perhaps you just didn’t see their utility. The same can be said of how many of us felt about AI a few years ago.

At this point, the respondents who said they had plans to start using AI in their marketing would be “late majority” adopters. While there’s a cachet to being an innovator or early adopter of a new technology — if that technology turns out to be widely popular — there’s a lot to be said for being cautious.

Some potential benefits to being in the late majority include:

• The costs of new technologies often come down after the early stages.
• There’s value in seeing how others use and benefit (or don’t) from a new technology.
• It allows you to get the most out of legacy systems before they become obsolete — provided you don’t reinvest in a dying technology.
• It’s easier to justify an investment in new technology to both yourself and stakeholders when the advantages of that technology are evident.

6 Reasons Companies Shy Away From AI

We asked the 5 firm “No” respondents why they didn’t have plans to implement AI. Their reasons echoed many of the questions and criticisms of AI that exist beyond marketing. 

Here’s what they mentioned:

Obstacle #1: Data Privacy Concerns

One big worry around AI is data privacy. People don’t want the data they feed to the AI to be publicly available or vulnerable to potential threat actors. Cybersecurity‌ is a major concern for corporations, so it makes sense that this aspect of AI worries company leaders.

However, there may be some misconceptions about this. Take this response:

“If you use an LLM [large language model], any data accessed will be used to train the LLM further. We don’t want the LLM to have access to ANY of our data.”

This sentiment likely stems from news stories about how LLMs — which are the technology that underpins generative AI chatbots — take information on the internet and reproduce it. They might reproduce original research or mimic a writing or visual artistic style. Perhaps the most noteworthy example of this conflict is the New York Times’ lawsuit against OpenAI, the creator of ChatGPT.

However, LLMs don’t really use data in the way the respondent is concerned about. It’s a bit complicated, but LLMs don’t store data in a traditional sense, though they can retrieve information from training datasets. Furthermore, there are a lot of AI tools for marketing, and several don’t necessarily use an LLM.

Obstacle #2: Lack Of Training or Expertise

The misconception stated above points to another big hurdle to AI adoption. Learning to use AI tools effectively takes time. Many marketers and marketing companies are hesitant to invest in the resources necessary to get up to speed with AI. 

The same respondent quoted above highlighted this issue quite well. They said, when presented with a potential use case for AI, their manager or marketing director might say, “OK, that’s great, but what does this mean? Why should we spend time on this?” Many decision-makers might not have enough base knowledge of AI to understand how it can help them.

Obstacle #3: AI Tools Aren’t Suitable For Their Needs

One thing to consider about those who can’t understand how AI could help their efforts: They might be right. Maybe there aren’t clear uses for AI in every marketing firm and it may make sense to wait it out until it’s obvious how AI can help.

However, if a marketer isn’t fully aware of all the AI tools and features available, they can’t know if AI truly is unsuitable for them. It’s worth keeping up to date with AI developments, even if one is a skeptic.

Obstacle #4: Job Security Concerns

Significant innovation in automation can eliminate or reduce certain jobs. However, automation can also create other jobs. Whether it creates as many jobs as it replaces, and whether those new jobs can benefit the now-displaced workforce, are open debates. The answers change depending on the specific automation concerned. 

One marketing director with over a decade of experience said their company wasn’t interested in AI, explaining, “We prefer the personal touch. AI takes jobs, and it is very hit and miss, anyway.” 

There’s a lot wrapped up in this short statement. Let’s break it down:

• “We prefer the real touch” — Using AI to draft an email for one specific lead or one partner, and sending it off unedited, is probably a bad idea. But there are many ways to use AI and also give a personal touch to the messaging in the process.
• “AI takes jobs” — This is true, but how significant will this trend be? Only time can tell, but it’s unlikely it will take marketers’ jobs en masse.
• “It’s very hit and miss” — This is also true. But consider this: Some social media posts hit while others miss, too. Does this mean a marketer should stay away from social media? Or should they learn effective social media marketing techniques?

Obstacle #5: Content Quality Concerns

One respondent said their company will use AI eventually, but predicted it “will ultimately be a net negative for everyone when it’s filled with generic slop.” This is probably a reference to a rash of uncreative AI-generated social media posts that have popped up recently. Apart from being poorly made, this content is often associated with scam artists, so it has a very negative perception.

However, not all AI-created content needs to be poor quality or scammy; in fact, we strongly advocate for human intervention throughout the content creation process specifically to address content quality concerns.

Obstacle #6: Environmental Concerns

This is perhaps the thorniest issue. Marketers can learn how to use AI effectively and it doesn’t have to steal jobs. But there’s no question that there’s an environmental impact. Some of our responses reflect this:

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

Training AI models and using them consumes a lot of energy and water (as coolant). A typical ChatGPT query uses nearly 10 times more energy than the average Google search. However, some AI use cases may actually be less taxing on the environment than the human labor equivalent — including applications related to writing and illustrating, reported Snopes, citing several 2024 studies. Maybe the answer here is to use AI judiciously — and perhaps we can cut back on other environmentally harmful operations, too, such as flying for business meetings.

How to Address the Top AI Concerns

Here are some things companies can do to address these concerns:

• Implement AI policies: A thoughtfully crafted AI policy can address data privacy, security and content quality concerns.
• Adopt training and education initiatives: There are clearly misconceptions about AI, so offering training and education can ameliorate worries over a lack of expertise, as well as job security concerns.
• Take a slow approach: If your company hasn’t started using AI yet, don’t worry! Take your time and find AI tools that suit your needs. Also, consider how you can use AI in a more environmentally responsible manner.
• Communicate: Having business leaders or the AI team share their expectations and plans with employees helps create a smoother adoption. This looks like a necessary step, given the 52% of “No” respondents who weren’t sure whether their company had plans to start in 2025 — this shows a lack of communication.

Take a Breath.

AI is super exciting and super scary. Ultimately, you can only control so much; AI will become more prevalent in marketing, and business more generally. And AI will change some job functions, but companies aren’t going to replace their entire marketing departments with AI. Instead, AI will largely supplement the tasks marketers are already doing, and it will likely create new, AI-focussed positions, too.

Keep Exploring Our AI in Marketing Insights

Check out the rest of our survey outcomes series: