The current stage of media and communications development is characterized by an exponential increase in data volumes, acceleration of communication cycles, and complexity of consumer patterns. In this context, marketing communications professionals (advertising specialists, PR managers, and marketers) face the challenge of maintaining the quality of creative solutions while dealing with strict time and budget constraints and a competitive environment. Artificial intelligence technologies, particularly generative neural networks (GPT-4, Midjourney, DALL-E, and Sora), offer innovative solutions to this dilemma.

However, there is still an ambivalent attitude towards AI in the professional community, ranging from euphoria («AI will replace copywriters and designers») to complete denial («machines are incapable of true creativity»). The purpose of this article is to provide a balanced and scientifically grounded forecast of the use of AI in creative industries, emphasizing the importance of collaboration rather than replacement between human and artificial intelligence. The article also highlights the need for regulatory oversight from both the industry and the government.

Let’s explore the main aspects related to the use of neural networks in creative industries and marketing communications:

1. The utilitarian (applied, instrumental) aspect of using AI is related to tasks that require processing large amounts of data, recognizing patterns, and automating routine processes. This is where neural networks demonstrate their greatest effectiveness. Traditional campaign analytics required a specialist to manually collect data from multiple sources (CRM, web analytics, social media, and media mentions). AI systems (such as Brand24 and YouScan) process millions of messages in real-time, identifying sentiment, semantic clusters, and emerging trends. Marketers don’t get «raw numbers,» but ready-made insights: «In the 25-34 age segment, negativity is associated with issue X.» AI-based predictive models allow you to predict the ROI of a campaign with an accuracy of up to 85-90% before it’s launched.

Neural networks help professionals today with personalization of communications and audience segmentation. Deep learning (deep learning) gives the opportunity to build micro-segments of the audience by hundreds of parameters, including psychographics and contextual behavior.

AI also helps with the automation of routine communications. ChatGPT, Midjourney, and YandexGPT are tools that can save up to 80% of time on routine tasks. In Russia, according to Yandex.Research, 67% of marketers in the country already use AI tools at least once a week, and 23% use them daily [2]. Chatbots and voice assistants based on LLM (Large Language Models) handle initial customer inquiries, provide answers to common questions, and moderate comments. A specialist is freed up to work with complex, conflict-ridden, or non-standard cases. This is not a «dehumanization» of communication, but rather a reallocation of human resources to areas where empathy and creativity are critically needed. The time previously spent by the communicator on routine tasks can now be transformed into targeted emotional and human actions that AI cannot perform.

The most controversial area is the ability of AI to be creative, the creative aspect. Creativity in marketing communications refers to the creation of new, original, and relevant messages, images, scenarios, and concepts. We often hear the phrase that only humans can come up with something new that doesn’t exist in nature, while a neural network merely aggregates previously collected information into predefined frameworks. However, this does not refer to high-level art or the generation of profound meanings and forms. However, understanding the specifics of developing the same advertising creatives and their almost immediate obsolescence, which leads to the creation of more and more new forms, we can conclude that neural networks can also help with quick and budget-friendly solutions.

Generative neural networks (Midjourney, Runway, Kling) allow you to create photorealistic images, video fragments, and 3D objects based on text descriptions. For advertisers and PR specialists, this means reducing the time it takes to create visuals from days to minutes, and allowing for instant A/B testing of different visual concepts. However, the key challenge is the loss of unique brand style and authorial touch if the neural network is used without proper control.

Neural networks can generate hundreds of title, slogan, post script, and article topic ideas in seconds. It’s important to understand that AI doesn’t create from nothing; it recombines elements from the training set. However, this «divergent search» during the initial phase of the creative process is highly valuable. «Effective integration requires collaboration between AI developers and experts to ensure that the algorithmic results can be properly interpreted and verified. This emphasizes that epistemic autonomy in the AI era is not a personal trait, but a practice that relies on institutional support» [1].

Modern language models (Claude 3, Gemini 1.5) are capable of imitating the styles of specific authors, brands, and publications. They take into account storytelling structures (such as «hero’s journey»), rhythm, metaphors, and rhetorical devices. However, final editing always requires human intervention, as AI lacks intentionality and understanding of deep context and corporate culture. The best practice is to use AI as a «literary servant» for drafting, which is then transformed into a final text by a professional. Accordingly, the value of true human labor (its creativity, criticality, and generation) will increase.

Let’s summarize the strengths and weaknesses of implementing AI in marketing communications.

Достоинства:

1. Super-linear speed. Tasks that took three-person team two days to complete (trend analysis + 30 concept generation + 10 visual creation), the neural network completes in 2-3 hours.
2. Scalability. AI provides personalization of millions of messages without increasing the staff.
3. Reduced cognitive load. Automation of routine (reports, summaries, transcription, primary monitoring) allows a specialist to focus on strategic and emotional intelligence.
4. Democratization of creativity. Small companies and agencies gain access to tools previously available only to large players with large budgets.
5. Hyper-personalization of communication messages and advertising creatives. «Hyper-personalization is based on the integration of artificial intelligence, machine learning, and big data processing» [3].

Disadvantages and risks:

1. Neural network «hallucinations» — generation of factually incorrect but outwardly convincing information. For PR, this is fraught with public dissemination of false data and reputational losses.
2. Loss of a unique brand voice. If the entire industry uses the same models (for example, GPT-4), the content is unified, originality, irony, understatement disappear.
3. Ethical and legal risks. Copyright issues for generated content, the ability to create deepfakes, and the opacity of recommendation algorithms.
4. Deformation of professional skills. Excessive reliance on AI can lead to atrophy of young professionals’ own creative thinking.

AI is not a competitor or a substitute for humans in the creative industries. It is a powerful tool that is comparable in historical significance to the invention of writing, the printing press, or digital photography. None of these tools has destroyed creativity; instead, they have transformed its forms and requirements for professionals. The current effective model is a critical collaboration, where humans set goals, formulate problems, define ethical and aesthetic frameworks, interpret contexts, make final decisions, and take responsibility.

AI performs rapid analysis of gigantic data sets, generates thousands of options (from which a human chooses), automates technical production stages, and tests hypotheses.

An experienced marketer, advertiser, PR specialist uses AI as an assistant, capable of “thinking about twenty options for a headline” in a fraction of a second. At the same time, strategic vision, a sense of brand, emotional intelligence and ethical reflection remain the prerogative of a human. In the next 5-7 years, the following scenarios can be predicted: the integration of AI into all stages of communication design, from the brief to post-campaign analysis, the emergence of a new role of «prompt engineer» or «neuro-creative director» as a full-time position, and the standardization of AI content quality metrics for creative industries.

However, technological development is outpacing the formation of a regulatory framework. The lack of regulation leads to three negative scenarios: 1) unfair competition (passing off AI content as human content, and hidden manipulation), 2) loss of audience trust in any media (the inability to distinguish between reality and simulation), and 3) devaluation of the creative profession.

Therefore, it is necessary to implement a three-tiered regulatory system:

1. Self-regulation by industry associations (RAMU, AKOS, RACO, AKAR) — development of codes for the use of AI in advertising and PR, including mandatory labeling of generated content, and standards for fact-checking.
2. State regulation — amendments to the laws “On Advertising”, “On the Media”, “On Personal Data” regarding liability for harm caused by AI communications, regulation of deepfakes, and licensing of generative models for mass distribution.
3. International cooperation: harmonization of norms within the BRICS and EAEU frameworks, taking into account national cultural characteristics.

The competition between humans and neural networks is a false dilemma. Collaboration is critical, where human intelligence provides goal-setting, context, and responsibility, while artificial intelligence provides speed, volume, and computational power. To realize this potential, the creative industries must work with governments and associations to establish ethical and legal frameworks. Only then can AI become a catalyst for a new renaissance in marketing communications and advertising, rather than a threat.