Modern artificial intelligence technologies are developing so rapidly that they have become one of the most impressive areas for investment. And of course, the reason for this boom was generative AI. The data on the growth of the generative AI market is an indisputable confirmation of this. So, over the past 4 years, the market has grown from 5.51 billion USD in 2020 to 36.06 billion USD in 2024, and by 2030 the projection increase will hit 356.10 billion USD, which is almost 65 times more than in 2020.
The secret lies in its ability to create unique content, automate routine processes, and find non-standard solutions in various fields. Simply put, it reduces the cost of goods and services, freeing up human and financial resources for other tasks. Generative AI is already used in marketing, journalism, design, and even programming, opening up new opportunities for business and creative industries.
What is Generative AI?
Generative artificial intelligence is a branch of artificial intelligence that can produce new data based on trained models. Unlike traditional algorithms that only allow data analysis and classification, generative AI can produce text, images, audio, videos, and code.
Generative AI technology relies on such neural networks as GPT for text processing and DALL E for image generation. The actuators for these kinds of applications are trained on large amounts of data, from which they identify patterns and relationships that can subsequently generate new, meaningful results.
It can independently create content, including texts, images, videos, and music. Thanks to training on large volumes of data, its results become increasingly high-quality as the more information is used for training, the more accurate and meaningful the generated content.
Such models have the advantage of flexibility and adaptability and can therefore be applied to a number of domains, ranging from marketing to programming. Finally, generative AI engages actively with the user since many generative AI-based tools allow programmatic refining and personalization of generated content in real-time. For the time being, marketing, journalism, software development, design, and media already massively harnessed this technology. In marketing, generative models further help companies automate content generation, refine communications for audiences, and hugely increase advertising campaign effectiveness.
What is the Role of Generative AI in Marketing?
Generative AI allows marketers to produce content more rapidly, thus saving time in preparing advertising campaigns and making them more focused towards the audience.
One of the greatest benefits is the automation of routine tasks. And since using AI to create texts, images, and videos frees up resources, teams immediately free up a lot of time, which will allow them to focus on more strategic initiatives. Speaking about the results, companies that have implemented these technologies are seeing an increase in efficiency. For example, retailers are recording an increase in return on advertising investments by 10-25%.
In general, generative AI has taken root very well in marketing operations. Creating marketing communications via email, push notifications, or SMS is now faster. There is also a decrease in the number of errors and a decrease in the time and costs of quality assurance since AI helps with this in many ways.
Examples of Generative AI in Marketing
Examples of successful use of generative AI already exist in various industries and their number continues to grow every day. Those industries that are directly related to online marketing were the first to master this direction. Thus, Etsy introduced a “gift mode” that analyzes user preferences and offers personalized recommendations, improving the user experience and stimulating sales. Booking.com uses AI to simplify travel planning, select the best accommodation options and helping to analyze reviews. At the same time, Procter & Gamble uses artificial intelligence to process data from smart products, such as the Oral-B iO toothbrush, which allows it to better understand consumer needs and adapt products to them.
To summarize, it can be unequivocally stated that these changes accelerate marketing processes, reducing the time it takes to bring campaigns to market by almost half and reducing content creation costs by 30–50%. As a result, companies that actively follow trends and are not shy about integrating generative AI into their internal processes gain not only a competitive advantage but also the opportunity to build deeper connections with customers by offering them personalized and relevant content.
7 Steps to Effectively Using Generative AI in Marketing
The analysis by leading marketers shows that seven practical steps can help businesses move toward the next phase of generative AI maturity.
Step 1: Create a strategy for integrating generative AI into marketing
To effectively incorporate generative AI in marketing, there is a necessity to create a clear strategy for its implementation into the work processes of teams within organizations. Companies must define the rules for using the technology, standardize its application, and create a methodology for evaluating its effectiveness. For example, those who build a clear policy for working with AI scale its use faster and achieve stable results.
Step 2: Train your team to use AI effectively
After that, training becomes a key task. It is necessary not only to give them access to the tools, but also to show them best practices for using AI in their daily tasks.
Regular trainings, workshops, and internal research help teams find new ways to use the technology. For example, one media company included a discussion of successes in working with AI in weekly meetings, which allowed employees to adapt to new tools faster.
Step 3. Define goals and success metrics
Another not less important thing is to define challenging and quantifiable goals. This can be shortening the time to market campaigns, individualized messages, or improving ROI. We suggest using the SMART technique to make sure all goals are measurable and realistic. For example, an international financial institution reduced the time to market for campaigns by 50% through the active implementation of AI.
Step 4. Focus on scalable initiatives
Companies should sharpen their focus and aim it on large initiatives, rather than scattering themselves across many small pilot projects. Launching a small number of scalable solutions allows you to see the real effect faster. For example, a bank implemented an AI assistant for creating personalized content, which reduced production time by 75% and increased the number of new accounts by 20-25%.
Step 5. Adapt AI to real user needs
It is also important to take into account the real needs of users. Tools need to be integrated into marketers' workflows, not imposed on them. For example, one bank employed "superusers" within its organization to create an AI assistant, which increased adoption within the organization.
Step 6: Integrate AI into daily workflows
The sixth phase is to begin applying the daily practice of AI utilization. It should not be applied for exceptional experiments but as an integral part of ordinary work of marketers, analysts, and creative specialists. One has to encourage creative thinking by allowing teams to experiment with new ideas. For example, a media company integrated AI into daily workflows, making workers more efficient.
Step 7: Follow trends and innovations in generative AI
Finally, companies should monitor changes in the industry and expand their partner ecosystem. Constantly monitoring new solutions, testing AI vendors (for example, Adobe, Jasper, Synthesia, and Typeface), and tracking successful cases of other companies allow you to remain competitive. Those who quickly adapt new technologies gain a significant advantage through more effective marketing.
Generative AI marketing tools
In search of better solutions, marketers are increasingly immersed in the abyss of thousands of different marketing AI assistants, but such an abundance of offers simply does not allow for adequate analysis. That is why my team and I decided to make the 5 most relevant tools at the moment that every marketer should be able to use.
M1 Project – AI for developing ICP and optimizing marketing strategies
The standout among the tools is M1 Project – a revolutionary solution designed to build and perfect the ideal customer profile (ICP), improve marketing strategies and produce effective content.
Unlike other AI tools that focus only on content generation, M1 Project uses data analysis, audience segmentation and positioning to help companies maximize the results of their marketing efforts. Thanks to its capabilities, businesses increase conversion, more accurately target their audience and optimize advertising budgets, which leads to an increase in ROI. Jasper AI – Text Content Generation for Marketing and Advertising
Jasper AI - creating text content
Another popular tool is Jasper AI, which is used intensively for producing marketing and advertising content. It allows you to create articles, ads, newsletters, and product descriptions in no time, with a uniform brand style and SEO optimization. Thanks to this, companies reduce the time spent on content creation by more than half without losing quality.
Copy.ai – AI copywriting for high-conversion campaigns
Copy.ai is great for conversion campaigns, helping to create compelling advertising texts, landing pages, and product descriptions. Its technologies allow you to produce content with contextual variations for different audiences and market spaces, leading to greater user engagement and improved conversion rates.
Synthesia - AI video creator
Video content is also becoming a requirement for marketing strategies, and Synthesia makes it easier to create personalized videos, ad pitches, and learning content. The system allows you to generate videos with avatars and voiceovers in different languages, which makes it a convenient tool for brands operating in international markets. Companies using Synthesia note a decrease in video production costs and an increase in audience engagement.
MidJourney – Creating visual content for marketing and branding
Visual solutions in marketing are no less important, and MidJourney allows you to create unique images for branding, advertising campaigns, and social networks. Using text prompts, you can quickly generate professional graphic materials, which is especially valuable for digital marketing campaigns. This allows businesses to create creative content without the need for expensive designer services.
Case Studies: How Companies Use Generative AI in Marketing
Marketing teams face huge amounts of work, the need to personalize content, and optimize advertising costs. Generative AI helps solve these problems by increasing the speed, accuracy, and effectiveness of marketing campaigns. Here are five real-life examples of the successful implementation of AI in marketing.
1. Bayer – Predicting Market Trends with AI
Bayer wanted to move from reactive marketing to a predictive strategy that allows them to understand audience needs in advance. To achieve this, the team combined data from Google Trends, climate information, and Google Cloud ML predictive models. The system allowed them to predict the increase in flu cases during certain periods, which helped them to adapt marketing messages in a timely manner.
Results:
- CTR increased by 85% year-over-year.
- Click cost decreased by 33%.
- Website traffic increased by 2.6 times.
2. Sage Publishing – Content Marketing Automation with AI
Sage Publishing creates over 100 textbooks each year that require marketing copy. Manually developing texts was time-consuming and expensive, so the team implemented Jasper AI for automated text generation. Now, a book description is created in a few seconds based on the title, author name, and abstract.
Results:
- Reduced content writing time by 99%.
- Reduced marketing costs by 50%.
- Accelerated the preparation of textbook descriptions by 99%.
Buzz Radar – Real-Time Digital Campaign Performance Analysis
Buzz Radar built the cognitive command center platform based on IBM Watson technology to enable marketers to analyze campaign effectiveness in real time. Agencies now can have an immediate glimpse and take real-time intervention on the campaign, enhancing the ROI.
Results:
- Saving millions of dollars by optimizing digital campaigns.
- Increasing the efficiency of advertising agencies compared to large competitors.
- Reducing staff turnover by automating routine analytics.
Envidual – Optimizing Marketing Strategy with M1-Project
Marcel, UX designer and digital project manager at Envidual, is in charge of designing marketing strategies for his company. Among his key tasks is ongoing updating and refining the ICP (ideal customer profile). But this was costing too much time: 10 hours a month were lost looking for the right segments and selecting good strategies.
Marcel automated this with M1-Project. The AI ICP generator allowed him to create an optimal customer profile in minutes, providing in-depth segmentation and promotion strategy suggestions. This helped Envidual not only to improve targeting but also save time on creating marketing content.
Results:
- Optimized landing page, adapted to the key pain points of the target audience
- Launched an advertising campaign on LinkedIn, providing 0.75% CTR, which is 1.7 times higher than the industry standard (0.43%)
- Automated the ICP creation process, which saved hours of work for the marketing team
24Sales - Automation of the ICP creation process and time savings
Rotterdam-based marketing agency 24Sales specializes in sales automation, building marketing strategies and using AI. Previously, the process of creating an ideal customer profile (ICP) took 4 hours, requiring many interviews and data analysis. After implementing M1-Project, this task now takes only 30 minutes, while the platform automatically generates 80% of the necessary information, which the team then supplements manually.
Using M1-Project, 24Sales can develop more accurate marketing strategies, targeted campaigns and personalized advertising messages. This resulted in significant time savings and increased efficiency in working with clients.
Results:
- Reduction in time to create ICP from 40 hours to 5 hours per month
- Ability to produce 8 times more client reports
- Saving $1,000 per month, which is $12,000 per year
- Completion of ICP in a 1-hour meeting instead of a week of correspondence
The Future of Generative AI in Marketing
Our specialists observe how technology is progressing, and AI-driven marketing methods become more individualized, data-driven, and efficient, allowing brands to reach their audiences in ways never seen before.
Most likely the most significant change that we will observe will be hyper-personalization of content. AI will generate text, images, and videos, dynamically personalize them for every user depending on real-time behavioral data, that, obviously will accelerate and affect advertisement, email, and social media content generation process in the way that they will be optimized automatically to cater to the interests and needs of particular consumers, leading to increased engagement and conversion rates.
The second significant trend we can't afford to miss is the marketing strategy creation going mainstream. AI programs will move well beyond content creation and instead contribute to actually designing marketing roadmaps, predicting market trends, and identifying high-value customer segments. At M1-Project we are already blazing the trail using AI to drive Ideal Customer Profile and go-to-market strategies optimization.
AI will also revolutionize multichannel campaign delivery. Instead of having to change campaigns on various platforms manually, AI will pre-optimize social media, search engine, and paid-ad content, providing messaging that is consistent and powerful across all channels. This will eliminate human effort and significantly enhance campaign performance.
Also, conversational AI and virtual assistants' growth will transform customer interactions. Chatbots and voice assistants that are powered by AI will become smarter, giving real-time, context-driven answers and guiding potential customers through the buyer journey with minimal or no human intervention.
And the final thing we want to emphasize is ethical AI and transparency of the AI processes will be a top priority. Firms that employ responsible AI will be able to build stronger customer trust and long-term brand loyalty.
.svg)
