28 AI marketing statistics you need to know in 2025

Artificial intelligence (AI) in marketing is skyrocketing. AI is helping enhance marketing processes and improve data analysis. 

So, how can savvy marketers stay ahead of the AI curve in 2025? And how can you leverage AI to launch successful campaigns?

Read on for 28 AI in marketing statistics and how to leverage AI in your marketing strategy.

The marketing landscape has done a 180 since the onset of the COVID-19 pandemic. Is the rise of AI in marketing a new shiny toy, or is it here to stay? To uncover the answers, we conducted an AI marketing trends study and an AI in the customer experience study. Keep reading for our findings and other industry reports.

Related reading: International perspectives on AI

AI in marketing is the use of artificial intelligence tools to streamline the duties of a marketer. Marketing teams can leverage AI to enhance brainstorming, content writing, and personalization efforts. Equally, AI tools can offer machine learning, which can help improve data analysis and empower data-driven decision-making.

Optimizing content is the leading use case for artificial intelligence tools, according to SurveyMonkey research. This broad topic encompasses everything from adding SEO keywords to copy and reworking content for different audiences.

Over half (51%) of marketing teams use AI to optimize content. 

The second most popular use of AI in marketing is content creation. When feeding an AI tool a writing prompt, marketing teams can create content quickly. 

Some marketing teams use AI to produce marketing materials like brochures, website designs, campaign plans, and written content. The extent to which marketers edit generated content varies depending on their trust and faith in AI content.

Customer demographics, interactions, and behaviors—like reading a blog or clicking a link—can help marketers accurately predict and respond to customers.

For example, AI personalization can suggest related blogs on your website based on users' reading history.

One of the most useful deployments of artificial intelligence tools in marketing is brainstorming content. By creating a short brief or proposal and including a handful of ideas, marketing teams can ask generative AI tools to aid brainstorming sessions by providing new ideas.

Artificial intelligence tools draw from public data, so they can generate fairly basic ideas. However, their rapid generation can be valuable for teams seeking quick inspiration.

Automation is the fourth most popular use case of AI in marketing. Artificial intelligence tools can train on datasets and use machine learning to replicate these processes.

For monotonous tasks, AI's automation of repetitive actions is a powerful time-saving tool. It allows marketing teams to focus on higher-priority activities and be more productive.

Forty-three percent of marketers think AI is important to their social media strategy—and 48% think it's somewhat important. Marketers use AI for social media monitoring to efficiently track and analyze many online conversations, providing real-time insights into customer sentiment and trends.

AI tools can identify patterns, detect potential issues early, and highlight brand mentions, enabling marketers to respond proactively. This helps improve brand reputation, customer engagement, and strategic decision-making.

Data analysis is a vital part of marketing. Artificial intelligence tools can expedite collecting data and identifying patterns in datasets.

Marketing teams can deploy AI to help them analyze data on a larger scale, providing them the insight they need to develop and launch campaigns effectively. For example, businesses can use AI-powered market research tools to streamline market research datasets, providing more rapid insight.

Forty percent of marketers use artificial intelligence to conduct research. AI tools, like SurveyMonkey Genius®, help marketers gain product, market, brand, and customer insights.

AI enhances response rates and data quality by offering question suggestions and ensuring an optimal survey length and format.

AI also helps marketers analyze insights like data scientists. Response Quality uses machine learning to identify poor-quality responses and clean data so you can focus on high-quality survey data. Sentiment Analysis helps you further analyze text responses to pinpoint feedback sentiment.

Marketers use AI for customer journey mapping. 

AI analyzes behavioral data to uncover patterns and predict customer needs, leading to more targeted and timely interactions. This enhances customer satisfaction and loyalty by ensuring seamless and relevant experiences throughout their journey.

AI chatbots and virtual assistants can provide instant, 24/7 customer support.

These chatbots can also gather valuable data on customer preferences, which marketers can analyze to refine strategies and personalize future interactions.

Related webinar: AI in Marketing: How to cut through the hype and harness AI’s potential

Here are some of the most important advantages of AI in marketing:

These advantages provide cost savings to marketing teams, helping them improve the bottom line and produce campaigns faster.

Although AI in marketing has several advantages, there are also disadvantages to be aware of.

Businesses should understand and take steps to adapt to the following disadvantages of AI in marketing:

The first step toward successful AI integration is to understand why you want to use these tools in the first place. A core goal or actionable plan for AI will provide a roadmap to successful onboarding.

Before you select tools or start testing AI platforms, list goals or tasks on which you’d like to use AI, such as automating tasks or improving keyword targeting. By starting with the result you’d like to gain, you can make a clear strategy that will get you from A to B.

Before defining your AI goals, evaluate your current resources and identify areas where AI can add the most value. For example, if your marketing team excels at content marketing, you may not need a content AI developer. However, if you're struggling to scale personalization efforts, AI could be a perfect solution to improve efficiency and reach.

By assessing your team's strengths and weaknesses, you can pinpoint where AI integration will have the greatest impact. Gathering employee feedback is a great way to understand where AI could be most beneficial in your workforce.

Once your marketing team has established what use cases you want to focus on, it’s time to look for AI tools.

To find the one that’s best for your team, consider:

Based on your response to these questions, you can rule out certain tools. A platform may be too expensive, too complex, or simply incompatible with your current data architecture.

One of the disadvantages of artificial intelligence in marketing is that AI data is prone to bias and hallucinations. Don't allow these factors to hinder progress. Regularly collect, test, and analyze AI data to pinpoint and remove these biases.

Businesses should review any AI-generated content. While this step will slow down your team, it ensures copy and designs meet your brand standards.

Related reading: Turn feedback into actionable insights with survey analysis

Your AI marketing strategy will naturally evolve. As with all new projects, it’s important to set benchmarks, measure progress, and look for areas for optimization.

When it comes to AI in marketing, your staff will be the primary people who will have contact with the tools.

Pro-tip: Ask for feedback by sending out an employee engagement survey. You can do this periodically to trace how the uses of AI in your business evolve.

Using AI in your marketing could help improve processes and generate more ROI from your campaigns.

SurveyMonkey Genius® helps marketers do just that. Marketers can build highly responsive surveys to collect customer insights that inform successful marketing efforts. Discover how you can use SurveyMonkey Genius to enhance your marketing strategy or sign up for an account.