Branding and AI: how AI changes brand development in 2026
Neural networks (Midjourney, DALL·E, Runway) accelerate the generation of ideas and visuals, but the final decision remains with the strategist. The article reviews the latest AI tools for branding, compares their quality to that of a designer, makes forecasts for 2026 year, and offers tips on how to integrate neural networks into the process without compromising quality. Let's explore where AI is truly useful and where human involvement is indispensable.
How AI is Changing Brand Development
Neural networks are no longer exotic. Today they automate routine tasks: generating dozens of logo variants, selecting color schemes, and creating mockups. The stage of reference searching and prototyping, which used to take days, now fits into hours. This is especially noticeable at the initial stages when it's necessary to quickly present several visual directions to the client. In the branding agency Gromov Branding, AI is used for generating moodboards and primary visual concepts. When working on projects for airlines or FMCG brands, neural networks help gather references based on facts, color palettes, and mood within minutes. This allows faster entry into strategy discussions and reduces the number of iterations before finalizing the direction. Neural networks do not understand business context, audience, or the competitive environment. Without strategy and a brand platform, AI produces visually pleasing but meaningless images — beautiful form without substance. The key principle here is simple: AI is a tool, not a replacement for expertise. In Gromov Branding, each AI-generated variant passes through a strategist's filter: it is checked for alignment with positioning, target audience, and legal clarity. Only after this does the concept proceed to development.
What AI Tools Are Used in Branding
On the market, there are several popular solutions, each with their own strengths. The choice depends on the task: generating illustrations, identity elements, animations, or prototypes. Midjourney is the leader in quality of stylistic direction and illustration generation. Designers use it for finding the visual language of a brand: textures, mood, color palettes. In Gromov Branding, Midjourney is applied at the creative search stage — for example, to visualize a brand archetype or the atmosphere a client wants to convey. The downside is that it's difficult to control exact compliance with guidelines, so the result requires manual refinement. DALL·E 3 from OpenAI performs better in generating identity elements and patterns. Its strength lies in understanding textual requests, but the result often requires manual editing. If you need to create a pattern for packaging, DALL·E can offer several options, but final vectorization and adaptation for media still remain with the designer. Runway ML specializes in motion design: logo animation, dynamic backgrounds, video effects. Useful when creating presentation materials and brand videos. The agency uses Runway for rapid animation prototyping to show the client how the logo will look in motion. Adobe Firefly integrates into designers' familiar tools — Photoshop, Illustrator. It allows generating backgrounds, textures, and objects directly in the workflow. This is convenient when you need to quickly supplement a layout with elements without diverting attention to stock image searches. Stable Diffusion is an open-source solution that gives more control over generation.
AI vs designer: quality, speed, cost
Speed is the main advantage of neural networks. AI generates dozens of variants per minute, whereas a designer spends hours on a few concepts. This is especially useful at the 'warm-up' stage, when it's necessary to show the client a wide range of possibilities. When developing a logo for a startup, you can get 50–70 variants in different styles within an hour and immediately filter out unsuitable ones. Quality is the area where AI still lags behind. The neural network does not take into account marketing goals, target audience profile, competitor positioning. It produces visually attractive variants, but without a strategic basis (and here it should be clarified: even the most accurate generation cannot replace an interview with the client, where the true motives for engaging branding are revealed). The final decision always remains with the human. AI-generated content often contains errors: incorrect proportions, extra elements, distorted fonts — all of this requires manual correction. Cost: AI reduces expenses for initial generation, but strategy, refinement, and verification for registrability remain labor-intensive stages. A logo created by a neural network must be checked for uniqueness and the possibility of trademark registration. AI cannot guarantee that the generated image does not infringe on others' copyrights — the training dataset of the neural network uses millions of images, and fragments may be borrowed without the user's knowledge. Gromov Branding guarantees trademark registration: in the event of refusal, the agency will develop a new logo at its own expense and pay for registration. No AI service can offer such a guarantee.
Forecasts: how AI will develop in branding
By 2026, neural networks will learn to better take into account brand platforms and guidelines. AI assistants are already appearing that offer options based on uploaded strategies — generating logos that correspond to the brand archetype and color code. Such tools will likely become the standard: a designer will be able to upload a brand book, and the AI will only suggest solutions that do not contradict the visual system. Another direction is personalizing identity. AI will be able to adapt the corporate style for different channels and audiences while maintaining recognizability. For social networks — more vivid and dynamic versions, for business documents — strict and minimalist. The role of the designer and strategist will shift toward quality control, refinement, and strategic thinking. Agencies that have already implemented AI in their processes — such as Gromov Branding, which has AI designers on staff — will gain an advantage due to speed and efficiency. Those who ignore the technology risk falling behind the market. AI will not replace expertise, but it will make it more accessible. Branding is gradually ceasing to be the prerogative of only large budgets — with the help of neural networks, small businesses can obtain quality identity faster and more cheaply. However, without professional oversight, the result remains risky: a logo may look good visually but fail during trademark registration. Therefore, agencies that combine AI with deep strategy and legal support will be most in demand in the coming years.
Will AI fully replace designers? No. AI automates routine tasks, but strategy, meanings, and legal clarity remain with humans. A neural network will not conduct a brand audit, develop positioning, or register a trademark. Which neural networks are best suited for logo development? For generating concepts — Midjourney, for identity elements — DALL·E 3, for animation — Runway ML. A designer is still needed for the final design, who will adapt the result for media and check its uniqueness. Can a trademark be registered for a logo created by a neural network? Yes, if the logo is unique and does not infringe on the copyrights of third parties. AI-generated content often contains fragments of other images, so patent search is required. Gromov Branding performs such checks as part of the development process and guarantees registration. How much time does AI save at the design stage? During the idea-search phase — significantly, sometimes up to 70% of time. At the final development stage, savings are smaller, as manual refinement, vectorization, and adaptation to the brand book are required. How to check that an AI-generated output does not violate copyright? Use plagiarism-checking services — for example, TinEye, Google Images — and consult with a patent agent. In Gromov Branding, every AI-generated element undergoes legal review before inclusion in the final project. If you want to understand how neural networks can accelerate your brand or logo development, seek consultation. Specialists from Gromov Branding will tell you which tools they use in real projects and help select a collaboration format — logo development with integration of AI tools.
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