Chatgpt and Google Bard have entered the chat. If you have not joined the conversation about artificial intelligence (AI) in digital marketing, miss the party.
Perhaps you explore Ki herself or your boss asked you to report on opportunities to implement AI in your work (Welp!). Regardless of your motivation, I am here to help.
I will break down what AI is in digital marketing, how to use it, examples, advantages and disadvantages and marketing strategies that benefit from AI.
Table of contents
What is AI in digital marketing?
AI in digital marketing is the use of artificial intelligence to plan, carry out or optimize the marketing efforts of a company. AI Marketing aims to improve marketing performance, efficiency and cost savings of the company.
AI can even interact with customers who carry out certain behavior on their website, e.g. B. click on a button or a social media contribution.
What does that mean for you? With AI you can Analyze customer behaviorAutomate results, automate marketing tasks and create and personalize marketing content.
New AI tools come onto the market every day. They promise to help marketers to do their work faster, more intelligently and easier to do. Since these tools still appear, not everyone is a homerun, and the number of research tools is overwhelming.
We asked over 1,000 marketers how they use AI in their workplaces and where they affect them.
Pro tip: If you are a lifting spot user, read ours New AI tools. We have a new content assistant, Ai Blog Topic GeneratorAnd chat pot tools to optimize your everyday life. Our functions use AI, including SEO, call records, social media, Data managementand more.
Start with Drift Kings Media Content Assistant.
How do digital marketers use AI?
How do you use it? Our research from 2025 showed that text-based content creates is the way, whereby 55% of consumer marketers for blogs, emails and social contributions are relating to it. In 47%, the examinations follow, including market research and article overview, while 41% AI use direct reports and conversation marketing.
Let’s take a closer look at the potential use of AI in digital marketing.
Opportunities to use AI in digital marketing
1. Data analysis
Difficulties to understand large data records? Most digital marketing tools offer you analyzes, but marketers often have to export and put together data from various platforms such as puzzle ropes to take the large picture.
AI can collect and search large amounts of data from several marketing platforms and summarize the results. 36% of the marketers who use AI rely on data analysis and reporting and make it a significant application for improving marketing knowledge.
In this way you can save time if you develop marketing assets for your campaign strategy and development of marketing assets.
Pro tip: Drift Kings Media Sales Hub Has functions for discussion information to understand how your team appears at customer calls through data -controlled knowledge.
Learn how to use Contino -based marketing places Driven by AI.
2. Creation of content
Digital marketers can instruct AI to write marketing content, including captures. Social media contributionsE -mail copy and even blog copy. AI for Multimedia can use how to use it via marketers PicturesPresent audioand evenly video.
The creation of content remains a Killer application of AI, 55% of the AU-UNE marketers for text-based content creation on it. In addition, 38% Ai use for multimedia, including videos, pictures and audio.
It is important to note that most of the content of AI-generated are not ready for publication immediately. Most marketers today use generative AI as the starting point – be it ideas, an overview or a few paragraphs to ignite creativity.
Only 4% of the marketers who use AI indicate that they use it to write entire content, and only 7% publish AI-generated content without changes. Most make considerable changes to AI-generated text (56%) or minor improvements (38%) before publication.
Pro tip: Lifting spots AI-operated content assistant Helps you generate blog ideas, create outline and write blogs or marketing -e emails.
3 .. Reduction of administrator work
Like every professional role, digital marketers spend a lot of time to sit in meetings and do administrative tasks.
The Drift Kings Media 2025 State of Artificial Intelligence report has found that 78% of the marketers believe that AI reduces time for manual tasks such as data entry and planning. In fact, 26% of AU-UNE marketers use AI to take notes and summarize meetings.
Ki tools can tackle manual tasks such as planning reviews, summaries of articles and research as well as notes and notes. These functions are not sexy, but they free the time of a marketer for more important, creative parts of their work.
Take SuperhumanThe e -mail known for your speed. The AI ​​functions save hours in their inbox by summarizing entire email threads, preparing draft files in their voice, and an AI search 2-3x faster than Mails or Outlooks.
4 .. Content personalization
AI analyzes users online and offers you a more personal experience with marketing assets, including websites, social media posts and e -mails. Our studies show that 60% of the marketers believe that AI helps them personalize the customer experience.
This means that AI’s experience of the customer, depending on the online behavior or the question of whether you have filled out a form for your company or not.
For example, dynamic content changes, depending on the name, profession of the user, online behavior, etc.
6Sense is an example of a tool that uses AI to seven to seven. If you understand who wants to buy in your audience, you can personalize the marketing experience.
5. Media purchase
Another way to use AI in marketing is the media purchase. Gone are the days when junior media buyers have selected websites or advertising boards to advertise.
Instead, AdTech platforms use AI to select the most effective ad and media placements to reach a target group and maximize the ROI.
If you use Google ads, you have already pushed the AI ​​function that helps the auction process.
Other independent AI tools like Sample89 Enter recommendations for your advertising expenses and make it possible to address the right target group to increase performance.
Pro tip: You can also use AI to help you write an appealing account copy in a fraction of the time.
Campaign assistant is a free AI-powered app with which you can easily generate for Google, Facebook and LinkedIn with just a few simple inputs for Google, Facebook and LinkedIn.
6. Chatbots
Use of AI in marketing we have seen for years are chatbots. Chatbots, created with natural language processing (NLP), can answer joint questions, maintain leads, plan demo calls and more.
A chatbot can personalize customer trip during the stage if you consume marketing content. This tool can also answer customer questions. Our data show that 31% of the marketers of KI use for brand chatbots on social media or your website.
Let’s take a look at driftFor example. The company has trained its chatbot to answer questions outside of a pre -programmed path. If a person has a question that is not loaded into the system, the user continues to receive an answer.
Pro tip: Would you like to better understand how AI-driven chatbots can answer customer questions? The Drift Kings Media Academy can help. This course describes The difference between rule-based and AI-powered chatbots.
7. Automated E -Mail marketing campaigns
Automatic e -mail marketing has also been around for years. However, AI tools can help create more appealing e -mail content and learn about the behavior of your e -mail list.
The aim is that their marketers spend less time for researching and brainstorming so that they can concentrate on successful campaigns. E -Mail marketing is the TOP -INSTALT type in which AI is used. 51% of the marketers advertise AI on e -mail marketing and newsletter platforms.
When AI is expanded and improved, the automated e -mail marketing software becomes even more important in your marketing stack.
Drift Kings Media Content Assistant Can help you create marketing -e emails. Write a request for what you want to apply – from a discount on a webinar to a blog post – and AI can generate a message with the right tone.
8. Prediction of customer behavior
Another great commitment of AI in digital marketing is to predict customer behavior and sales of customers.
AI can predict the result of marketing campaigns by using historical data such as consumer engagement metrics, purchases, time on the page, email openings and much more.
AI helps marketers to understand the predicted result of their campaigns, marketing assets and forecast results. These findings help marketers to develop better, more dynamic campaigns, increase sales and ROI.
9. Improve customer experience
With digital marketing, everything revolves around the customer experience, and AI can help marketing experts to offer their visitors the best experience to convert them into leads.
AI can help increase customer loyalty and loyalty, to inspire customers with personalized content and to improve assets. Our investigations showed that 66% of the marketers agree that AI will help them spend more time for creative aspects of their work, which ultimately leads to better customer experiences.
Which AI tools use marketers?
The AI ​​marketing landscape is large and grows quickly. You can find comprehensive instructions on the TOP -KI marketing tools available today in our detailed KI marketing tools guide.
Here is a sample of popular KI tools marketers who are currently using:
All purposes of chatbots dominate the landscape, whereby Chatgpt is used by 88% of the marketers who use chatbots, followed by Google Gemini at 52% use and Microsoft Copilot at 44%.
For the creation of content, image generators such as Dall-E and Midjourney are used by 40% of the AU-UNE marketers, while video editing AI tools with automatic functions see 36% use and used language and narrative generators such as Sprees and Murf of 33% of the marketers.
Specialized marketing tools also gain traction, including HubSpot contents assistant for blog and e -mail creation, Jasper for copywriting and copy.ai for the generation of content.
The data show that 71% of the marketers use two or more chatbots, the average marketer uses 2.41 different chatbots. This indicates that not a single AI tool meets every marketing requirement, and successful marketers build various AI toolkits.
KI marketing -Vor- and -Kons
While AI has many great advantages, it is still an emerging technology and has some disadvantages. Let us examine some of the advantages and disadvantages of AI in digital marketing.
Professions of AI in digital marketing
1. Increased ROI
Companies see strong returns for their AI investments. Accordingly Our research, 75% of companies, indicate a positive ROI of AI and automation investments. 34% stated that the return was “very positive”. In addition, 67% of companies plan to increase their AI expenses in 2025.
Instead of making an ineffective display for an entire campaign, you can use data analyzes and insights to create better marketing assets in real time.
This saves your marketing team time and money and enables you to work more efficiently and increase the profit. Cutting time and production costs also increases your ROI.
2. Speed ​​and efficiency
Efficiency gains are the main measure for the success of AI, and 64% of the marketers pursue productivity and 55% measuring time savings as key results. Our investigations show that 78% of the marketers agree that AI contributes to shortening the time for manual tasks.
This promotes your time and capacity to do more and invest your time where it is most important, but it also helps your brand.
All marketers know that it is a great advantage to be the first on a market.
Regardless of whether you have a social media campaigns based on moments of pop culture or the start of digital campaigns is the ability to shoot and start campaigns in days or even hours, and is pure gold.
3 .. better customer experience
Another advantage for the use of AI in marketing is that she can improve her relationship with her customers. Our data show that 74% of the marketers say that AI enables them to concentrate more on the most important parts of their role, while 66% of compliance with AI agree that they spend more time for creative aspects of their work.
The more personalized your recommendations and the deeper your relationships, the more likely you become repeated buyers.
AI can also identify customers at the risk of emigration and bring them into an automated marketing campaign to get them to get involved again with their company.
4. Data -based marketing decisions
AI can make it easier to scale your company and to analyze marketing goods that are sold, analyze, predict and create with data for analysis, prediction and creation of marketing goods. Our research showed that 66% of the marketers believe that AI draws insights from data that they could not find otherwise. See how your team can use artificial intelligence and automation in this course from the Drift Kings Media Academy.
Disadvantages of AI in digital marketing
1. Quality and accuracy in terms of content
Although generative AI has put a long way, the content is not flawless. Factual errors are a specific problem: 43% of the marketers say that generative AI sometimes provides inaccurate information, which is the best challenge.
In addition, 34% of the marketers have to struggle with the production of AI producers of biased content, and 30% say that the results of AI are often irrelevant for their needs or is free of surface and vague.
If you want to use AI to generate content without a human edit editing it, you can see a decline in quality. AI’s success depends on high -quality data that is precisely and promptly.
Without a human editor, KI can produce content with objective inaccuracies, bias or a different tone of your brand. The use of AI requires a human supervision so that this type of error does not occur.
2. Privacy
Since marketing assets have become more personalized over the years, customers are beginning to appreciate privacy.
At AI, some of these techniques require the use of a customer and previous internet behavior cookies to predict future purchases. Our investigations show that 41% of the marketer data protection concerns instruct the main obstacle to the introduction of AI.
If your marketing team download and use AI software, you have to make sure that you comply with the data protection laws such as the GDPR.
3. Copyright concerns
As a new technology, the legal framework for AI is still built. Generative KI tools are trained in public content of thousands of companies so that it is possible to generate content that is a little to Near your competitor.
Copyright laws are written around human authorship. It is therefore unclear whether you actually have content with AI-generated content in the same way. In addition, 19% of the marketers fear that generative AI sometimes creates plagued information.
4. Integration and training problems
Our research shows significant obstacles for the introduction of AI beyond the quality of content quality. Training and time investment problems affect 39% of the marketers, while 34% struggle with the integration problems with existing or old systems.
In addition, 34% of the marketers say that too many tools do similar things, but are not connected and create a fragmented landscape that can be more frustrating than helpful.
It could be difficult to get a buy-in to invest in your company in AI because KPIs are not quantifiable.
Certain key figures will be easy to pursue, but others – such as improving the customer experience, increasing the brand awareness or improving the call – are much more difficult. Therefore it is important to have the right measuring tools, such as Hubpot marketing analytics platformin place.
With the platform you can track KPIs over all of your marketing channels under Unified Dashboards – from website data traffic and page views to the number of leads generated by advertising campaigns and more.
Examples of AI in digital marketing
At this point you may be wondering that you are wondering “Okay, but what does that look like in practice?” Let us check some examples in real life how large media companies AI have used in your digital marketing.
1. Netflix
If you are in marketing, you know that you have to send the right message to the right person at the right time. Netflix uses AI to do this. How?
On A Netflix tech blogThe company explains how it uses previous view of view to determine the work of art for recommended films or television programs.
For example, if you have seen many films of an actor, you may recommend another film in which you are in. If the work of art does not show the actor, you may click away.
When the film is recommended to this special viewer, the artwork shows this actor.
Or maybe a viewer tends to see more comedies than romances. If Netflix recommends a film, you can change the work of art to show comedic scenes compared to romantic moments from the film.
Let’s take a look at how Netflix would recommend the film Good will hunt Someone who sees romantic films compared to the works of art with whom he would recommend the film to someone who sees comedies.
Why does Netflix do that? The aim is to increase the conversion rates and to improve the customer experience on your platform.
2. Spotify
Spotify uses a similar approach to Netflix. The company will use AI to understand the music interests of a user, the Podcast favorites, the purchase historical, the location, the brand interactions and much more.
Then individual playlists and recommendations are curated for each user.
This type of personalization of content has contributed to large media companies such as Spotify to become TOP streaming platforms. But personalization does not end there.
Spotify also sends automated e -mail marketing messages with personalized recommendations.
The goal? Create automated marketing messages and assets that convert a user because the message is specific to this customer.
3. Amazon
Two important applications for AI in marketing forecast sales and analysis of data. Amazon uses AI to do exactly that.
When you go in Amazon, there is a section “recommended products” in which predictive analytics are used to determine whether a customer will probably make a purchase.
This helps the Amazon marketing teams know which products should place in front of which customers. You can also predict how well a product is sold based on its recommended product campaigns.
This type of AI helps increase conversions, improve customer satisfaction and measure the overall success and the ROI of different marketing campaigns.
4. Dreamhost
Dreamhost’s company name generator Use AI to offer custom company name ideas. Simply enter keywords regarding your company, and it suggests clear names in real time and also checks the availability of domains to start your online presence.
5. Ki marketing agent of Storychief: William
Stork fox AI marketing agentWilliam, generates a custom content strategy that is tailored to your brand by simply entering your website -URL. He proposes content columns, defines its branded voice, identifies your target group and even fills your content calendar.
But it doesn’t stop here. William continuously monitors content performance, offers traffic audits and offers new content ideas to be ahead of the trends. In addition, they keep the control – curate, approve and publish content as you think it is right.
How to use AI in digital marketing
If you haven’t started yet Provision of AI in their digital marketing strategiesThis is your year. However, successful AI implementation requires more than just new tools – it requires a strategic, systematic approach that takes into account both opportunities and risks.
The best way to make a great organizational change is a strategic, systematic and sensitive approach that deals both the technical and human elements of the transformation.
1. Define your goals and metrics.
Before starting, determine which goal or goal you want to achieve. Would you like to make your campaigns more effective? Would you like to save your team time or money? Would you like to improve personalization or improve data views?
Our investigations show that marketing experts measure the effectiveness of AI primarily through increased productivity (64%), time savings (55%) and a better overall performance of the roles (43%). However, you should also consider how the AI ​​affects customer -oriented metrics such as personalization improvements (39%) and extended data knowledge (39%).
Do not skip this step – you cannot determine success without defining your goals and quantifiable KPIs. Taking into account both quantitative metrics such as ROI, time -saving as well as productivity gains as well as qualitative results such as the satisfaction of the employees, the quality of the creative production and the improvement of customer experience.
The strategic considerations include the orientation of the AI ​​goals with wider business goals, the definition of realistic expectations of AI skills and restrictions, the determination of basic measurements before implementing and creating feedback loops for continuous improvements.
Potential challenges include difficulties in measuring non -quantifiable advantages such as creativity or innovation, overestimating the immediate effects of the AI ​​on complex marketing challenges and the resistance of team members who fear for the survey.
2. Check your infrastructure and willingness to data.
First put together a small team to analyze your current tools and infrastructure and find opportunities for acceptance. This exam should examine both your technical functions and your data quality, since the AI ​​success depends heavily on clean, accessible and relevant data.
Write a report with all possible implementation areas, potential results and what resources you would need to achieve this. Our data show that 34% of the marketers have to deal with the integration problems with existing or old systems. This step is therefore of crucial importance.
Rate the quality, quantity and accessibility of your data to determine how suitable you are suitable for AI applications. Do not forget to determine potential challenges or negative results together with the positive.
You cannot throw out your marketing playbook and replace it with AI strategies overnight. Therefore, identify your two to three areas in which you want to test first.
Strategic considerations:
- Rate data protection and security standards (75% of the marketers take this factor into account strong)
- Rate the requirements for the technical infrastructure for the integration of AI tools
- Identify data silos that could restrict the effectiveness of the AI
- Take into account the scalability requirements for future expansion
Possible risks:
- Violations of data protection if there are no proper security measures
- Integration error with legacy systems
- Data quality problems that lead to bad AI outputs
- Over complication of existing successful workflows
This does not have to be all big initiatives such as the revision of your e -mail marketing -small things can add up. For example, the use of AI tools for recording meetings and the transcription of interview recordings can offer an immediate value and at the same time create trust in the AI ​​functions.
3 .. Test staff functions and address change management.
Another critical area that you should evaluate is whether your employees have the training and knowledge in order to effectively implement these programs. Our research shows that training and time investments affect 39% of the marketers, which makes this a significant obstacle to overcoming.
You will probably have to invest in training courses for your current staff, hire a consultant or create a new position to advance your AI initiatives. Keep in mind that the employees are largely willing to take over AI – 51% strive to use AI tools – but explicitly hesitate or resistance.
A strategic approach to change management is to position the AI ​​as an opportunity for your team in order to become better marketers, to provide dedicated learning resources (56% of marketers learning through educational videos, 48% through companies provided by companies) to create internal champions that can be used for the introduction of AI and proactively and transparent for concerns about the concerns Can deal with job security.
For training and development, consider that 37% of companies offer course grants for AI-related training, offer 42% subscriptions for AI tools or platforms, 39% internal AI training programs and 34% weekly hours for AI experiments.
4. Select the correct AI marketing tools strategically.
As soon as you have identified your goals and top areas for implementation, it is time to strategically create your toolbox. Your current tools may already offer AI functions. 89% of AI users report increased use because AI is added to existing tools such as Microsoft Copilot or Google Docs AI suggestions.
Our research results show that marketers are strongly dependent on peer reviews (48%) and free attempts (47%) when evaluating new AI tools. This indicates a practical, test -driven approach to select the tools.
The selection criteria for tool selection should focus on data protection and safety standards (priority of 75% of the marketers), legal terms and ethical guidelines (of 73% or 67%), integration skills with existing systems and cost effectiveness with clear ROI potential.
The popular tool categories include general chatbots such as Chatgpt (88%use), Google Gemini (52%) and Copilot (44%), tools for creating content such as image generators (40%use), video processing of AI (36%) and language generators (33%) as well as special marketing tools and analyzes.
The strategic considerations include Build vs. Business (66% of companies develop internal AI tools for better control and adaptation), a multi-tool approach (71% of the marketers use several chatbots instead of relying on one), use a free test strategy to test paid plans before the tasting, and by carrying out a thorough provider, including Case studies, and direct sales talks.
Potential pitfalls include the fragmentation of tools (34% say that too many tools do similar things, but do not integrate), in tools without proper training or change management, the selection of tools based on hype and not on the actual business requirements, and the insufficient security reviews can be selected, which can lead to questions of the data privacy.
First, decide whether you use an out-of-the-box Ki solution or a custom solution. Examples of out-of-the-box-AI solutions are Jasper, Chatgpt or Google Bard.
A custom solution that you can create with APIs for an open source AI like Lama 2 can be a powerful solution for long-term success. You can connect and train AI to your proprietary data or train a GPT with your own voice and your own style.
This approach requires additional specialist knowledge, so that you have to work closely with a consultant or your IT department.
5. Test, analyze and ittery strategically.
It is finally time to systematically test the water. Take your two to three implementation areas and start controlled pilot programs. Set a time frame and some targets so that you can compare the results with your basic measurements.
Your test framework should begin with low risk, carry out parallel tests in which AI-generated and humanly generated content, document processes, challenges and results meticulously compare and determine certain time frames (e.g. 30-90-day pilots) with clear success criteria.
The most important monitoring metrics include productivity gains (64% of marketers increase productivity), time savings (55% measurement time in the teams), quality indicators such as accuracy, brand orientation and customer loyalty as well as ROI indicators such as cost savings, campaign performance and lead generation.
Use findings from pilot programs for iteration and scaling to refine your approach, to scale successful application cases, while ineffective influences are canceled, continuously monitor the challenges (bias, accuracy, accuracy, relevance) determined in our research and build feedback loops with both internal teams as well as customers.
Risk reduction strategies should maintain human surveillance for all content of AI-generated (only 7% publish without changes), the implementation of facts test processes to answer the accuracy concerns (43% cite this as a challenge), monitoring problems of distortions and brand orientation as well as rollback plans for present implementations.
For example, if you want to test AI-placed social media ads, for example, take a trial period of a month. Monitor and edit the content in the course of the month and document the process.
When you are done, compare the performance of AI-generated, people generated and supported by people to see how he did it and create a plan for the future.
6. Build a sustainable culture of the AI ​​innovation.
As already mentioned, the structure of your team on board is the key to creating a permanent culture of AI innovation in every new change in technology, requires continuous commitment and strategic thinking.
One of the cultural development strategies includes that you ask your team for regular feedback and bring them in this process, assure you that the AI ​​do it better, do not replace, celebrate victories and learn openly from mistakes and create communities in practice for AI applications.
Organizational support structures should take into account that 66% of companies increase AI expenses in 2025, which has long-term commitment. You can also consider dedicated AI roles or responsibility within marketing teams, go out ongoing learning opportunities beyond the first training, set governance frames for ethical AI use and plan regulatory changes in AI government and data protection.
Long-term strategic considerations include the stay of AI developments and new applications, the development of internal specialist knowledge, instead of relying exclusively on external providers, developing AI-specific guidelines and guidelines and planning a higher AI integration when the technology falls.
When coping with continuous challenges, combating AI fatigue through the concentration on clear value creation, the management of the complexity of several AI tools and integrations, the balance of automation by maintaining creative creativity and the judgment of people and the preparation for regulatory changes in AI government and data protection models.
Remember that building an AI-capable marketing organization is a marathon, not a sprint. The 75% of companies that reported a positive ROI from AI investment did not achieve through careful planning, strategic implementation and continuous optimization – through transformations overnight.
Use of the power of the AI
Marketing teams can scale their business with AI and it doesn’t have to break the bank. Our latest studies show that 67% of companies want to increase their AI investment in 2025. 75% already report on positive ROI of their AI and automation tools.
However, it is important to take the limits of the AI ​​into account, even if the technology improves over time in the changing marketing landscape. The most important challenges that the marketers face – recognition questions, prejudices and relevance problems – remind us that human supervision is still essential.
While you can use it to support (and should) several marketing campaigns, AI works best as an intelligent assistant and not as a replacement. The most successful marketers use AI to improve their creativity, productivity and strategic thinking and at the same time maintain human touch that really swings a big marketing for customers.
The future of marketing is not to choose between human creativity and artificial intelligence, but also to create both effective, more efficient and appealing marketing experiences.
Note from the publisher: This article was originally published in March 2024 and has been updated for completeness since then.