AI Advertising: Types, Tools, and Real-World Applications

Key takeaways

Artificial intelligence (AI) is increasingly common in advertising for content creation, data analysis, audience targeting, and campaign optimization. 

• In the marketing industry, 99 percent of surveyed marketers and business leaders report using AI and expect to use it more frequently over time, according to the 2024 State of Marketing AI Report from the Marketing AI Institute [1].

• Some benefits of using AI in advertising include increased productivity and efficiency, stronger customer relationships, personalized audience targeting, higher return on investment (ROI), and continuous optimization.

• You can start building your experience in AI advertising by learning how AI works, practicing with AI tools, and implementing AI into your current campaigns. 

Explore how advertisers are using AI today, what AI advertising tools you can use, and AI advertising pros and cons. If you’re ready to build your AI knowledge, consider enrolling in the IBM AI Foundations for Everyone Specialization. In as little as four weeks, you can gain hands-on experience with several AI environments and applications and build job-ready AI skills to enhance your career.

What is AI advertising?

AI in advertising refers to the use of artificial intelligence technologies, such as machine learning, automation, and data analytics, to develop, optimize, and enhance digital advertising campaigns. From managing and analyzing large amounts of data to targeting audiences and personalizing brand messaging, marketers use AI to optimize ad efforts, improve outcomes, and reduce campaign budgets. 

The adoption of AI across various industries is rapidly growing, and the advertising sector is no exception. As of 2025, 88 percent of organizations reported using AI in at least one business function, according to a survey by McKinsey & Company [2]. In the marketing industry alone, 99 percent of surveyed marketers and business leaders reported using AI. They also reported that they expect to use it more frequently over time, according to the 2024 State of Marketing AI Report from the Marketing AI Institute [1]. 

For many businesses, AI-powered advertising has become the norm and default for functions such as bidding, audience targeting, data analytics, ad placement, creative testing, and more. As AI use in advertising becomes more common and essential, it will be crucial for marketers to familiarize themselves with AI tools and tactics to remain efficient.

Types of AI in advertising

AI has multifaceted uses and roles in the advertising industry. From targeting audiences to optimizing campaigns, the range is vast and ever-evolving. However, some of the most common use cases and types of AI in advertising today are: 

• Personalized audience targeting and segmentation: AI algorithms can help advertisers target key audiences by utilizing large amounts of behavioral, intent, and demographic data to segment audiences. This process enables marketers to create more effective and personalized campaigns, targeting niche audiences and matching them with ads that are more likely to result in conversions. With personalization, ads can adjust within moments to tailor content to an individual user’s needs and desires. For example, someone who has been searching online for travel supplies is more likely to see ads for backpacks and suitcases based on their browsing history and personal data. 

• Programmatic and predictive ad buying: AI can look ahead to determine which variables will drive optimal results, such as platforms, times of day, and placement locations. For example, if a restaurant is trying to attract more customers, AI can determine that ads featured on Thursday at dinner time are likely to yield the best results and purchase space during that time. AI uses analyzed data to optimize ad buying to be more efficient with spending and increase impressions and conversions. Furthermore, AI can also buy ad exchanges in real time online, constantly updating to buy and sell ad space based on the ads most likely to convert. Programs can adjust these bids automatically, allowing advertisers to optimize ROI, scale reach, and maintain a reasonable cost per conversion.

• Ad creation: Though AI will never fully replace human creativity, tools can speed the creative process along. Generative AI can create visuals and copy within moments, all aligned with data and user behavior to be more efficient. Whether these are entirely new ads or simply repurposed ad content to create multiple variations for testing, these technologies can generate and multiply content with the click of a button, all while saving human time and effort. 

• Campaign forecasting and real-time adjustments: Using simulation, AI models can use past data to forecast and estimate conversions, allowing advertisers to adjust their budgets accordingly. Plus, algorithms can see how ads are performing in the moment, analyze the data, and make real-time adjustments to improve ROI. By monitoring past and present performance, these tools can provide insights and recommendations that allow advertisers to make the best decisions for maximum success. 

• Chatbots and virtual assistants: AI agents and advanced chatbots can have live conversations with a business’s audience, providing personalized shopping experiences and recommending products or content that appeal to them. These virtual assistants can facilitate ad placements, creating an interactive experience for consumers that points them directly to their needs. 

AI advertising tools

You can discover thousands of AI advertising tools, each with its own unique solutions and capabilities. Explore some examples of AI tools that businesses are using to optimize their marketing efforts.

• ChatGPT: As a generative AI technology, ChatGPT has many practical functions, including creating copy, building social campaign templates, and generating data-driven and personalized email campaigns. ChatGPT can also design chatbots to communicate with customers online and guide them through their purchasing processes. 

• Persado: Using personalized and language-based AI content, Persado generates ads for social media platforms and more to maximize conversion rates. Persado uses machine learning, large language models, and data analysis to choose and tailor copy to target consumers on an individual basis. 

• Copilot: Made by Microsoft, Copilot can generate marketing plans, track campaign performance, draft full article copy, brainstorm, optimize market research, and create social media copy. 

• Emotiva: Through computer vision and machine learning, Emotiva uses predictive emotion AI to measure emotional responses to advertisements by analyzing facial expressions. Using the data gathered, the technology can optimize ads based on consumers’ attention levels and emotional responses, adjusting campaigns accordingly. 

• Gemini: Google’s Gemini technology can analyze large amounts of data, summarizing it into actionable documentation. Beyond that, it can brainstorm; create copy, images, and videos; and simplify and automate basic responsibilities. 

Who uses AI in advertising?

Marketers and businesses use AI in advertising to analyze data for actionable insights, reduce time on repetitive or inefficient tasks, optimize spending and budgets for greater ROI, and create more opportunities and greater reach for their brands. 

More and more modern companies are switching to AI practices as they try to stay relevant and revolutionize their tactics to be more strategic. Through AI, advertisers are reaching consumers in new, more personalized ways, reducing time spent on crafting copy and visuals, and making data-informed decisions that lead to higher results. 

Beyond marketers themselves, the industries they serve also effectively use AI to boost their platforms. For example: 

• Retailers use AI to improve customer interactions, synthesizing product descriptions to use language that appeals to specific customers, as well as providing dynamic e-commerce recommendations based on a consumer’s past data. 

• Streaming services like Netflix and Amazon Prime use AI to provide viewers with targeted movie and TV show recommendations based on their past viewing data, enticing consumers to keep watching. 

• Social media platforms use AI algorithms to display specific content and ads to users who are most likely to interact with them. In addition, each platform utilizes AI in unique ways. LinkedIn allows users to take a conversational approach to job searching, where job seekers can enter their desired position in their own words into a search box, and AI algorithms display relevant roles based on their profile and intent. Snapchat, on the other hand, uses computer vision and AI for its AI lens features, allowing you to write out prompts to alter your image based on the description you provide.

Read more: Augmented Reality Advertising: How Marketers Use AR to Engage Customers

What is the 30 percent rule in AI? 

The 30 percent rule in AI is a framework that suggests AI should complete no more than 30 percent of a project or job responsibility, with human effort and thought completing the remaining 70 percent. The rule is meant to help students and employees use AI responsibly as a helpful tool without replacing learning and professional growth. 

AI in advertising: Real-world examples and case studies

AI advertising is revolutionizing how businesses reach their audiences and promote their brands effectively. As companies adapt and creatively implement AI into their marketing practices, more success stories arise. Consider two real-world examples of how AI has impacted campaigns in recent years:

• Coca-Cola: In partnership with OpenAI and Bain & Company, Coca-Cola’s “Create Real Magic” campaign allowed fans and digital creatives to generate original artwork with archives of past Coca-Cola-branded elements for a contest, and billboards in New York's Times Square and London's Piccadilly Circus displayed the winners. Using DALL-E, an AI image generator, and GPT-4, which can create copy from search engine queries, Coca-Cola leveraged AI to creatively engage its audience in a new way. Thousands of fans submitted content, and the campaign garnered social media traction.

• Lexus: Lexus’s “Driven by Intuition” campaign revolutionized AI by being one of the first TV advertisements to be entirely scripted by AI. Using IBM Watson technology, the script was created by analyzing past Lexus marketing campaigns and data on human emotional responses to make content that was “award worthy” [3]. The commercial featured Lexus’s ES, a vehicle with AI-driven features, and creatively highlighted the car's technology, utilizing AI to craft the commercial script. The ad reached 60 million people, and the vehicle earned 40 percent above the expected sales target [4].

Benefits and limitations of AI marketing

When it comes to AI marketing and advertising, you can find many benefits, from enhanced efficiency to a more targeted consumer base. However, some limitations can also arise, many of which you can overcome with proper management and established data procedures. Consider some of the benefits and limitations of using AI in advertising efforts.

Benefits

• Increased productivity and efficiency: Marketing teams can build new campaigns much faster and more efficiently, using data analysis and content generation to expedite the planning process. 

• Stronger customer relationships and personalization: Because AI can personalize ads to their targeted audience based on past data and interactions, brands can more effectively form relationships with their customers and build loyalty. Additionally, marketers can achieve higher conversion rates by tailoring their content in real-time to users’ preferences, needs, and behaviors. 

• Higher ROI: Through data analytics based on user intent and behavior, AI helps marketers target audiences more efficiently by using model-driven segments, thereby reducing the money wasted on ineffective ad spends. In addition, AI can adjust ad buying in real-time to be the most strategic and cost-effective. 

• Continuous optimization: AI systems optimize 24/7. As performance changes positively or negatively, AI automation dynamically adjusts settings to achieve the best and most strategic outcomes. That way, depending on the time of day, location, and more, AI will always target your audience in the most effective way.

Limitations

• Lack of AI education: In order to use AI effectively, advertisers must first have proper training. This means businesses need to invest in education, provide time and financial resources, and prioritize awareness and understanding so that employees use AI strategically and not just as a replacement for day-to-day tasks.

• Quality concerns: Though AI can create images and copy, it doesn’t necessarily create perfect content. Sometimes automated content can seem ingenuous or have low data quality. It’s important that a business still incorporates human review and brand guidelines. Also, if your AI tool does not follow your organization’s brand and style, you may face inconsistencies that can confuse your customers. 

• Ethical considerations and privacy regulations: AI thrives on personal and behavioral data to function; however, not all data is available or usable. Marketers must be cautious of data protection regulations and be aware of how to legally and responsibly collect data. Risks include fines and damage to your brand reputation and customer relationships.

Is it legal to use AI in advertising?

Yes, it is legal to use AI in advertising efforts; however, risks and limitations are associated with this approach. For example, ads that are entirely created by AI don’t have copyright protection, so you will need an element of human involvement and documentation to prove it. Furthermore, you’ll have to ensure that all claims gathered by AI are accurate, as false advertising can lead to fines, cease-and-desist orders, and other consequences. Some states have legal limitations on AI ads, including New York, which requires advertisements to disclose the use of AI-generated performers (people who appear real but are actually AI-generated).

How to get started with AI advertising

Getting started in AI advertising can be as straightforward as doing your own research, getting experience, and building your portfolio. You can follow these steps to kick off your learning journey:

Get familiar with the fundamentals of AI.

To be effective using AI in the advertising industry, you first have to have basic knowledge of how AI works. Learn about machine learning, how it functions, and industries that use AI today. As you get more in-depth, it may be helpful to study how audience targeting works, how to understand data analysis, how to automate, and what ethical limitations you need to be aware of as you implement AI in your workplace.

Try out some small-scale projects.

Gain some hands-on experience by experimenting with AI use in your day-to-day responsibilities. Specifically, seek out projects that use AI tools and data analysis to get familiar with managing large amounts of data and using AI in content and campaign creation. You can also practice by auditing your current campaign: Where is time being used inefficiently, what can you automate, and how can AI help with the creative process?

Select your tools.

Try out different AI tools to determine which are right for you and your brand. Do you need content creation, ad spend optimization, or targeted audience data analysis? Knowing your needs will help you decide what tools to invest in.

Practice a real campaign.

Now, it’s time to implement. Start a campaign with clear goals, using AI optimization tactics to refine and adjust as needed. Measure your ROI, and expand as you get more comfortable and familiar with your AI-generated knowledge. 

Explore our free AI resources to learn more

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