Generative AI in Creative Marketing: Opportunity or Threat to Agencies?

Have you noticed a recent social media trend in which people are creating their 3D figurines from photos? Or posting their AI pictures in sarees? It is the popular Google Gemini Nano Banana or AI Saree trend. And let’s not forget the highly popular Ghibli trend, which even melted the GPUs of OpenAI. 

Trends like these are prime examples of using generative AI in creative marketing. These companies have smartly marketed features of their AI tool amongst the masses and made it highly popular, which in turn created a strong brand or product visibility in the market. 

Such trends remind us of how deeply generative AI has made its way in our social, professional, and personal lives. Like all domains, marketing is no exception. Gen AI has hugely influenced the approach of modern agencies for creative tasks.  

For instance, content generation, design, video production, copywriting, and even marketing have been transformed by generative AI. This changing environment in the marketing space raises the critical question: Is AI an opportunity or a threat to marketing agencies?

The article aims to answer the question and help you understand the implications of generative AI in creative marketing. First, let’s take a brief look at what caused  a  rise in the use of  generative AI, or Gen AI in short, in creative marketing. 

What Sparked Generative AI in Creative Marketing 

In recent years, you can easily notice the growing use of gen AI in creative marketing. Stanford University’s 2025 AI Index Report highlights that 78% of organizations reported using AI in 2024, up from 55% in 2023. All thanks to technological advancements. Traditionally, AI was limited to prediction, analysis, and rule-based decision making.. 

However, advancements in machine learning, natural language processing, neural networks, and big data processing led to modern AI or generative AI, which can create high-quality content. 

Now, AI is being extensively used for creativity and innovation. But the gray area is that modern AI is being trained to mimic human creativity. Although it can allow marketers to explore their valuable potential, there are some dark areas that will be discussed in later parts of this blog.

Some other major factors behind the rise of generative AI are: 

• Curiosity behind ChatGPT: The platform was publicly released on 30th November 2022 and immediately made a breakthrough. For the first time, Gen AI was made accessible to the masses. ChatGPT has an intuitive and conversational interface. This led to its widespread adoption among curious people. As per Social Samosa, the platform observes 800 million users weekly.
• Productivity Gains: Businesses quickly realised that using generative AI can drastically improve their efficiency. They realised that content creation, copywriting, and ideation for campaigns can be quickly done on a large scale. This led to the rapid adoption of gen AI in creative industries.
• Interest and Investment: The growing interest in generative AI was further fuelled by heavy investments in the AI ecosystem. Stanford University’s 2025 AI Index Report mentions that gen AI attracted $33.9 billion in private investment globally, an 18.7% increase from 2023. This has allowed rapid innovation and competition in the market, bringing advanced AI creative tools to market faster than ever before.

List of Generative AI Tools used in Creative Marketing

Gen AI tools have many applications in creative marketing. Here’s a list of some AI tools that are commonly used to improve creative thinking and marketing processes. 

The Bright Side: Opportunities Generative AI Brings to Creative Marketing

Generative AI has opened new doors for creative processes and presented many opportunities for marketers. That is why the global market for Gen AI is rising and attracting heavy investments from businesses. As per Grand View Research, the global generative AI market was valued at USD 16.87 billion in 2024 and is projected to reach USD 109.37 billion by 2030, with a 37.6% CAGR.  

Now, let’s look at the bright side of Generative AI and what it brings to the creative marketing process.

Faster Ideation & Scalability

Generative AI tools are super fast. Instead of spending hours, these tools can generate many creative concepts in a few seconds. Whether it's ad copy, visuals, taglines, or video scripts, these tools have got your back.

With the help of generative AI tools, marketers can explore more creative directions and test different tones or styles at the same time. Hence, they can scale their campaigns quickly. These tools help you with: 

• Reduce time spent on manual work.
• Better brainstorming.

For instance, SimCorp enhanced its explainer videos using Synthesia to attract and convert customers. The result was that they created more than 300 videos at 5x speed. The team was able to save a lot of time and enhance their strategy. Here’s what their videos look like:  

Similarly, Bamboo Rose doubled its content output by using the Writer AI platform. It accelerated their content creation process and allowed the organization to focus more on distribution.

The current era is the AI era, where manual reporting is no longer useful, and repetitive work will slow you down. Using AI will make marketers work faster and smarter.  In fact, using AI-powered performance marketing systems like CM Galaxy can double your ROAS. By using these systems, teams can quickly identify which campaigns, ad sets, and creatives are performing well and which ones are draining budgets.

Creative Innovation

Generative AI models are trained on huge and diverse datasets. They can blend concepts and styles that you may never think of. These tools introduce a new layer of imaginative exploration in creative marketing processes. 

To cite a real-life example, Heinz launched the first-ever ad campaign with visuals generated entirely by AI. The company urged people to share their suggestions for ketchup image prompts, and the best ones were turned into social posts and print ads. The campaign was largely successful. 

Another successful campaign was launched by Coca-Cola. The brand launched its own AI platform, called “Create Real Magic”. The result was artists creating their own digital artwork based on dozens of branded assets, such as the distinctive contour bottle and script logo of Coca-Cola. 

Marketers can use generative AI to break away from repetitive templates and create something fresh. When prompts are refined, these tools produce higher-quality content and allow you to experiment with new formats. With the help of generative AI, marketers can avoid creative blocks and maximise their creative potential.

Cost-effective

One of the strongest aspects of generative AI is cost reduction. According to reports, 71% marketing & sales companies saw a 67% increase in revenue and a 34% decrease in cost. Agencies can automate repetitive creative tasks and save on operational costs. 

For instance, a task that would require a team of designers, writers, or video editors can be automated. This allows companies to produce more content in less time at a fraction of the cost. It lowers production costs and allows agencies to invest more in other areas to boost ROI. 

To give you an example, Zoom used Grammarly to speed up the writing and editing process through recommendations tailored to its brand voice. The result was that Zoom saved approximately 7,000+ hours on written communication, which is around $210,000.

Personalized Customer Experience

McKinsey states that 71% of consumers expect companies to offer personalized interactions, and 76% get frustrated when this doesn’t happen. Deloitte also mentions in its 2024 study that 80% consumers prefer brands that offer personalized experiences and spend 50% more with such brands.

Using AI-generated marketing content helps marketers move from mass marketing to micro-personalization. For example, we know that generative AI models analyse large amounts of user data like preferences, browsing history, and behavior. By using this data, these models can generate dozens of personalized messages and creatives in less time.

Tools like Gemini, ChatGPT, or Jasper AI can change and modify tone, language, and content format for different audiences automatically. It will improve engagement as customers will feel that brands “understand” them. Hence, ultimately increasing the conversion rates as well. 

For example, Unilever uses a generative AI platform called Alex for consumer engagement and support. Another brand called Gobi Cashmere used an AI platform called Algolia to create personalized experiences. The company saw an amazing conversion increase of 300 – 400% as they delivered more relevant search results and product recommendations.

Available 24/7

Generative AI systems don’t need breaks. They’re always active, producing and managing content continuously. Now imagine how valuable it can be for global marketing operations where time zones are different. In such a scenario, campaigns need to stay relevant and responsive across multiple time zones

Generative AI tools can help agencies create new and context-aware content in real time. Marketers can quickly update campaign visuals or create localized ad variations using these tools. These tools help in maintaining consistent engagement and quickly adapting to trends. Without using generative AI, staying up to date in the market is difficult.

The Dark Side: Challenges and Risks of AI-Generated Marketing Content

Like every coin has two sides, so does generative AI. It has its challenges and risks, which should be considered by businesses. Let’s look at the dark side of generative AI in creative marketing.

Loss of Originality / Sameness

One must not forget that AI-generated content is built on existing data and patterns from the internet. It gets inspiration from what already exists. There is a high chance that the model will start giving repetitive or formulaic content after some time. Generative AI tools often struggle to produce something truly original. 

It is critical to train generative AI models on new data; otherwise, they will start to replicate commonly used phrases, visual styles, or ad concepts. It will result in marketing materials that look or sound alike. If multiple agencies start using similar AI tools, you will notice that their campaigns look similar and do not hold the ‘unique’ factor. This is called ‘brand dilution’. 

Customer Distrust of AI-Generated Content

The use of generative AI in creative marketing is increasing, but users are not particularly fond of AI-generated images and content. As per a Journal published in the International Journal of Information Management, customers tend to avoid services advertised with AI-generated images as opposed to real ones.

According to the research, this rejection is even stronger for hedonic services and high-involvement decisions. Customers are wary of artificially generated content and don’t trust the authenticity of the service. They perceive such content as less accurate. 

CX Today mentions that many users reject AI for customer service and want a human touch. They don’t want companies to use AI in their services and have major concerns about using it.

Ethical and Legal Concerns

Agencies that use generative AI might have to deal with authenticity, ownership, and accountability issues. For instance, generative AI models may unknowingly reproduce parts of copyrighted text, music, or visuals found in their training data, which can cause copyright infringement.

Sometimes, these models are trained on data without permission, which makes the matter worse.  The most popular example is the Ghibli-like style image generator trend, in which OpenAI trained its models on copyrighted Ghibli works without permission. This sparked widespread copyright infringement and ethical debates over AI-generated art.

Then there is the risk of deepfakes and misinformation. Generative AI tools are capable of producing realistic faces, voices, or videos. These can be misused to create deceptive content and false marketing. Recently, it's getting more and more difficult to differentiate an AI-generated video from a real one. Social media is filled with fake AI-generated videos, eroding user trust.

According to data, deepfake fraud attempts have surged by 3,000% and cost businesses nearly $500,000 on average. The major question still remains: who owns AI-generated content? The brand that used gen AI content, the company that created the tool, or the data given by the company, which was used to train the AI model?

Financial Loses

Many organisations have faced financial consequences after neglecting responsible AI practices. The Responsible AI Pulse Survey highlights the following findings: 

• Almost all companies (99%) reported financial losses due to AI-related risks.
• The average financial loss for organizations that faced AI-related risks was estimated at US$4.4 million.
• Some companies experienced losses exceeding US$1 million.

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Furthermore, the survey also mentions that the most common risks include: 

• Non-compliance with AI regulations (57%)
• Negative impacts on sustainability goals (55%)
• Bias in AI outputs (53%)

One small mistake can cause huge losses and reputational damage. Nevertheless, the survey also mentions that those who have already defined a clear set of responsible AI principles have experienced 30% fewer risks compared to those who haven’t. Hence, the agencies have to be careful while using generative AI content in their marketing strategies. 

Creative Job Displacement

Automation of creative work is increasing workforce anxiety in marketing and advertising. Content writers, copywriters, designers, reporters, video editors, artists, and other professionals engaged in creative work find themselves at a crossroads. Many have switched their careers, while many are struggling to cope with the increasing use of AI in creative marketing.

In 2023, the USA witnessed a nationwide strike by the Writers’ Guild of America (WGA) over unfair practices in the television and online streaming industry, including the use of AI in creative work. Similar strikes and protests are frequent all over the world as AI leads to a loss of revenue for creative professionals.

Since using gen AI is cost-effective, in recent years, many agencies, like Dentsu, have laid off their teams to cut operational costs. These large-scale agency layoffs signal a shift in demand for professionals engaged in marketing, advertising, and other domains. 

Over-reliance on Automated Tools

Using AI is like using a double-edged sword. Too much dependence on generative AI tools will limit or erode human creativity. AI can certainly handle repetitive tasks and make some things easier for marketers, but it lacks intuition, empathy, and real-world experience. These qualities are important for emotionally connected storytelling.

Agencies that rely solely on AI prompts often end up creating campaigns without a “human spark” that connects with audiences. These tools can help you with optimizing ad headlines for better CTRs, but they miss subtle emotional cues that make content memorable.

Over-reliance on automated tools will result in creative stagnation across the industry and a loss of personal touch in marketing campaigns.

AI Bias & Inequality

As previously mentioned, AI models learn from existing human data, and they can unintentionally reproduce and amplify societal biases. It can show certain professions, race, demographics, and gender in biased ways.

Here’s an example below: 

As you can see, the prompt was simply to create an image of a person working in the kitchen, but ChatGPT Plus gave the image of a woman. This represents the historical stereotype that a woman should be the one working in a kitchen. A similar incident happened in 2024 when Gemini wrongly showed pictures of people of colour, creating outrage on social media.

Blindly using generative AI content can lead to biased or insensitive content that will quickly damage a brand’s reputation, especially in diverse global markets. Additionally, currently, AI models are trained heavily on the English language, which can lead to biases, less accurate performance in other languages, and cultural hegemony.

AI is also infamous for hallucinating when it doesn’t have answers. There are many instances where AI has generated false content and fabricated words. In fact, Google's parent company, Alphabet, even lost $100 billion in market value after its AI chatbot Bard provided fake information in a promotional video.

Similarly, an Associated Press investigation showed that OpenAI’s Whisper invents false content in transcriptions. It also inserts fabricated words or entire phrases not present in the audio. The errors were attributing race, violent rhetoric, and nonexistent medical treatments.

Combined, these dark sides of using generative AI are the reasons why agencies are still hesitant to adopt it in creative marketing. Let’s look at some other factors that further contribute to this fear.

Why Agencies Are Still Hesitant to Adopt Generative AI in Creative Marketing

According to MIT’s Media Lab findings, despite $30–40 billion in generative artificial intelligence, 95% of AI pilot projects in companies fail. They show zero return. Only about 5% of pilots make it to production with measurable value. Many agencies remain hesitant to integrate AI into their creative processes, and the main challenges are: 

• Lack of Expertise: Many agencies still lack the technical knowledge and expertise to integrate AI effectively into their creative processes. It results in inefficiencies and a lack of measurable results.
• Quality Control: There is a high chance that even agencies that integrate AI into their workflows are not working properly. It could become a challenge to ensure that AI-generated content is accurate and up to the quality mark. 
• Other Ethical Concerns: Agencies fear the potential ethical and legal risks associated with using AI. They are wary about dealing with copyright infringement, bias, data privacy, data availability, and transparency concerns.
• High Initial Investment:  Generative AI can save money in the long run, but it also requires significant initial investment to implement it. This can be difficult for smaller agencies to take the leap. 

The Way Forward for Agencies in Creative Marketing

It is all right to be afraid of using creative generative AI content in marketing. However, a middle way can be found and adopted by agencies to gain a competitive edge. Here are some ways that agencies can use to address risks and fears created by AI-generated content: 

• Embrace AI as a Co-Creator, Not a Competitor: Agencies must view AI as a tool to support human creativity rather than replace it. They should focus on combining the strengths of AI with the EQ of humans.
• Upskill Employees: Agencies should invest in training their teams to effectively use AI tools. Professionals should also understand that AI is the future and will have to learn it to remain relevant in the future. 
• Implement Quality Control Measures: Agencies should establish clear guidelines and processes for reviewing AI-generated content. They must check for accuracy, alignment with the brand's voice, and overall quality. Human oversight can not be neglected at any cost. 
• Prioritize Ethical AI Use: Agencies must adopt ethical practices for using AI and ensure transparency, fairness, and accountability in their marketing efforts. They should check contractual terms with the AI service provider and maintain user privacy. Currently, the first-party data strategy is the new marketing gold, and agencies should mine it effectively. 
• Start Small, Scale Gradually: For dealing with significant upfront investment, agencies can start by piloting small, low-risk projects that demonstrate clear ROI. First, test the technology and understand its value without committing to large-scale investments. 

Rounding Up

The uncertainty and fears about the use of generative AI in creative marketing are understandable. However, humans have always faced unpredictable situations and worries and adapted to them. 

Similarly, generative AI presents both opportunities and challenges for marketing agencies. The middle way lies in merging its strong features with the EQ and IQ of humans for maximum output. Agencies must accept generative AI as a co-creator, not a replacement for human creativity.