AI | UAATEAM

AI Search Optimization: how brands get discovered

Posted on July 15, 2026 by Max Zakhozhiy

If you ask ChatGPT which running shoe will cure flat feet, which VPN really works in Europe, or which project management tool to get the best bang for the buck, you get a confident, specific answer that is being produced by an AI without seeing a single website. No blue links. No 10 results to click through. Maybe two or three names, and a half-formed choice before anyone even writes a follow-up question.

That is the new reality of AI search optimization: 65% of all searches on Google now end with not a single click to any site. In the US, daily AI search usage has jumped from 14% to nearly 30% in just one year. Whatever the term of art the industry prefers, Generative Engine Optimization (GEO), Answer Engine Optimization (AEO), or simple AI SEO, there’s one phrase from a media strategist that captures what was different: The competition is no longer for position number 1; it is to be mentioned within the answer itself. And brands that haven’t prepared for brand visibility in AI answers are already losing customers; they will never know they’ve lost.

How AI-Powered Search Actually Works

Traditional search engines are indexed by page, and you have to pick. Generative engines skip that step. Instead of looking for the entire sentence like with a traditional query, when we ask ChatGPT or Perplexity something, it splits our question into multiple smaller “fan-out” queries, searches each fan-out separately, and assembles the results into one final conversational response. This is why ChatGPT optimization now matters for brands that want to understand how to appear in ChatGPT answer results. If you were to ask “best VPN for streaming Europe” to this assistant, it may be searching separately for “best VPN 2026,” “VPN Netflix streaming,” and “VPN servers Europe” and combining whatever ranks well between all three.

All platforms are reliant on different signals.

ChatGPT Search works by crawling the web via Bing’s indexing as well as its very own OAI-SearchBot, which utilizes a lot of structured data to find sources it can truly trust.

Perplexity gathers a few sources per answer, with footnotes. Google’s AI Overviews integrate with its existing search index and give preference to web pages with valid schema markup found in Search Console.

Gemini is so tightly integrated into Google’s infrastructure that it has a tendency to favor the same sites that naturally do well in organic results.

In contrast, Claude is more of a synthesizer rather than an answering engine, relying on information that is cleaner, well-structured, and concise in logical flow.

A single number encapsulates how this has scrambled the old playbook: the overlap between Google’s top-10 organic results and what AI engines refer to has shrunk from around 75% in mid-2025 to 17%-38% as of early 2026. It is no longer possible to appear in a Google Answer simply because we rank well, and the page that occupies position 15 with structured data cleaned up is already launching ahead of the page that was sitting in position one.

What Brands Are Actually Doing to Be Present

The brands gaining AI search visibility via AI by 2026 aren’t chasing hacks; they’re doubling down on fundamentals and adding a few AI-specific layers.

Structured Content And Schema Markup

JSON-LD is essentially the closest thing that AI crawlers have to a universal language that they can read and understand what a page is about without guessing. The data that will get a product card for your item in ChatGPT is schema, specifically, product schema (name, brand, price, availability, and review data). The FAQ Page schema is what transforms a support article into an answer you can cite. We know that pages with full schema are linked about three times more often in AI Overviews than without, and one controlled experiment showed a 19.72% lift in visibility for AI Overviews simply from the addition of entity-linked structured data. This is where structured content becomes one of the strongest foundations of content optimization for AI.

Conversational, Question-First Content

Pages answering the question right away in the first few lines are rewarded by AI systems over those dropping hints leading up to it. Instead of a keyword-stuffed header like “Running Shoe Benefits,” brands are writing How to find the best running shoe for flat feet. And then addressing that assumption in the first two sentences. This is far more likely to land a skincare brand being listed with an answer in the AI overview for “best moisturizer for sensitive skin” than it is a competitor with their answer three paragraphs down. The same principle that once helped brands win featured snippets is now becoming central to AI answers.

Authoritative, Third-Party-Backed Content

Research from the academic world on citation bias already shows an overwhelming preference for earned media and independent verification in AI engines over altruistic citations of brand-owned claims. Hence, community platforms are just as important to paid companies anymore; Reddit, YouTube, and LinkedIn ranked among the top domains referenced by large language models, and Reddit itself has around 100 million daily active users generating exactly the kind of unfiltered brand discussion these models consume.

Freshness And Original Data

AI engines weigh recency. An article titled “A Guide to 2024” gets outperformed by its 2026 counterpart on the same topic (but with no updates). If the only option is to cite one of 12 near-identical competitors, what reason does an AI engine actually have for citing you instead, unless you publish some proprietary research, benchmarks or a dataset that nobody else has?

Multi-Platform Visibility

Unlike 2004, when Google became the only AI engine that mattered, no single AI rules. A brand’s strategy now needs to cover Google AI Overviews, ChatGPT, Perplexity, Gemini & Copilot all at once and stay on the current crawlable technical foundation too. It begins with the fundamentals that competitors often skip completely: auditing robots. Confirming that txt is not silently blocking AI crawlers (a typical problem for websites using the default Cloudflare protection settings), that content isn’t hidden behind JavaScript rendering or logins, and ensuring pages load as expected for bots as they do for millennial customers.

Why the Payoff Is Bigger Than It Looks

AI search learns from data till October 2023; it never replaces a Google click but converts at totally different rates. ChatGPT visitors convert at about 14%, Claude referrals at over 16.8%, and Perplexity at 10.5%, vs. just about a precipitous Google organic traffic average 1.76%. Someone who gets to your site after an AI assistant has vetted you and recommended you is arriving far more intent than someone scanning ten blue links.

Measuring What Actually Matters

The biggest gaps in many marketing teams start not in strategy, but in measurement. Only about 14–16% of brands currently track AI search performance in any structured way (which is primarily due to our not building SEO dashboards for this yet). An AI answer has no “position 1”; there is no Search Console equivalent, and citations can swing 40–60% month on month. In practice, closing that gap involves asking ChatGPT, Gemini, and Perplexity the precise questions your customers are asking on the regular; who gets mentioned as a brand and by what source (be it ChatGPT or not) is logged; and brand mentions are tracked over time, all in the same kind of discipline SEO teams once used to track keyword rankings.

Conclusion

AI search optimization is not an alternative to SEO; it is the next chapter of SEO. The brands to be cited in 2026 will be the ones that treat structured data, question-first content, third-party credibility, and multi-platform coverage as part of a single system rather than separate checkboxes. Technical fundamentals matter, content quality is a higher bar than ever, and the door to accumulating citation authority before it compounds against late movers remains open. Brands that begin today won’t merely rank; they’ll be the solution.

AI Site Audit: Check Your Website’s Readiness for AI Search

Posted on June 26, 2026June 26, 2026 by Max Zakhozhiy

Two or three years ago, most companies measured website performance by a straightforward set of metrics: Google rankings, organic traffic, and the number of leads. If the numbers were growing, things were moving in the right direction.

Today, website owners are noticing a different picture. A company holds strong search positions, publishes content regularly, but when someone searches via ChatGPT or similar services, the brand barely comes up. It feels like the website exists in two separate realities: visible in Google, invisible in the new search platforms.

What’s happening? Your site needs AI optimization — and before that, a proper audit.

What Is an AI Site Audit

Unlike a classic SEO audit that focuses on rankings and traffic, an AI audit evaluates how clearly a website communicates to artificial intelligence systems. That’s why the review often goes beyond technical parameters and covers content, expertise, brand reputation, and its presence in the broader information landscape.

The problems can vary. After a site redesign, some pages may have quietly dropped out of the index. Sometimes critical information is buried so deep that users only find it after a long search. And sometimes the issue has nothing to do with the site itself — the company has a solid website but is barely mentioned anywhere else online.

Because of this, many businesses spend months making changes that don’t move the needle. An audit pinpoints the bottleneck before you invest in large-scale improvements.

Checking Technical Accessibility

Website owners often assume the technical side is fine. Pages load, forms work, no visible errors. But an audit regularly uncovers things that have been hiding in plain sight for years.

First, verify that your key pages are actually being indexed. After a redesign, structural changes, or a site migration, sections can accidentally fall out of indexation. Externally they look normal, but they’ve effectively stopped participating in search.

Technical files that govern how search crawlers behave need a separate check. The robots.txt may contain outdated restrictions, and sitemap.xml might not have been updated in a long time and no longer reflects the real structure of the site. As a result, search engines get an incomplete picture.

There’s also the question of crawler accessibility. Some content may be hidden inside complex interactive elements or loaded via scripts. A person sees it without any issue, but search and AI services don’t always process it the same way.

The audit also looks at duplicate pages, canonical tags, and other technical settings. If the same content is available at multiple URLs, search engines may interpret differently which version is the authoritative one.

Website Content Audit

Much of the content written a few years ago was created with classic SEO logic in mind: cover the topic broadly, include keywords, capture rankings. For today’s search platforms, that’s no longer enough.

Think of two articles on the same subject. The first has a lot of text but buries the answer at the very end. The second delivers the key information in the opening paragraphs, then digs deeper from there. The second approach is what gets traction in AI search today.

When reviewing content, look at each page through the eyes of someone searching for a specific answer. Does the page actually satisfy the user’s query? Are there clear, direct answers to the main questions? Is the reader forced to dig through secondary information to find what they need?

Tables, comparisons, and lists help readers find data faster. When information is well-organized, it’s easier to process — for people and for search services alike.

Many sites have articles that still attract visitors even though the underlying data is outdated. During the audit — especially when optimizing for ChatGPT — it’s worth checking facts, statistics, dates, research references, and examples.

Another important factor is original expertise. Content that reflects real company experience, project outcomes, specialist commentary, or firsthand observations is far more compelling than a generic rewrite of publicly available information. This type of content is what most consistently drives visibility in AI search.

Trust and Reputation Check

Technical soundness and good content still aren’t enough on their own. Search services need to understand who stands behind the site and whether the information published there can be trusted.

The mere fact that a brand is mentioned online tells you very little. Make sure the site includes basic information about the company, content authors, case studies, testimonials, or contact details. A privacy policy, business details, terms of use, and other official information also play a role in establishing site credibility.

It’s also worth reviewing structured data. It helps search systems correctly interpret information about the company, authors, products, and services.

Another critical dimension is external brand presence. When industry media, sector portals, or expert platforms mention your company, they create additional trust signals that reinforce the site’s authority.

This stage often makes it clear why two sites of similar quality can end up with very different levels of visibility. One brand is actively present in the information landscape; the other exists only within its own domain.

How to Check Your Brand’s Real Visibility

After analyzing the site itself, it’s worth stepping back and looking at things from the outside: does the company even get mentioned in modern search services, and what sources do those services rely on when generating answers?

To analyze visibility in AI systems, start with a simple list of queries: the company name, core services, products, and a handful of topic-based searches where the business wants to be discoverable by potential clients.

Then run those queries through AI services. What matters isn’t just whether the brand is mentioned. It’s far more useful to see which sites are being used as sources, which companies appear alongside yours, and who is actually shaping the information landscape in your niche.

These checks often produce surprises. A company may have consistent organic traffic from Google but almost no presence in AI-generated answers. The reverse also happens: a brand gets mentioned regularly thanks to strong reputation and external publications, even without high keyword rankings.

During the analysis, document all brand mentions, source sites, and the resources the system treats as authoritative. This clarifies who you’re actually competing with for audience attention.

To track the results of GEO optimization over time, set up referral tracking in Google Analytics 4. This lets you see the share of visitors arriving from next-generation search platforms and measure how brand visibility shifts after implementing your recommendations.

What to do After the Audit: Optimizing for AI Search

Many people expect a long list of errors and dozens of pages of recommendations on how to appear in ChatGPT answers. But after the audit, the picture becomes clear: which changes are likely to have an impact in the near term and deserve priority, and which ones don’t matter much right now.

Technical issues come first. If important pages aren’t indexed, are inaccessible to crawlers, or contain critical errors, other improvements may not produce the expected results.

The next step depends on the state of your content. In some cases, updating older material is enough. In others, the page structure needs simplifying or the way information is presented needs rethinking. Audits also regularly surface topic gaps — subjects the site simply isn’t covering.

Trust signals deserve separate attention. Many sites are missing author information, case studies, testimonials, or company overview pages. Sometimes the core problem turns out to be an absence of expert content: the company talks extensively about its services but rarely shares its own experience and perspective.

Once changes are implemented, define the metrics you’ll use to measure results. The typical ones to track: page indexation, new brand mentions, organic traffic, referrals from next-generation search platforms, and visibility trends across key topics.

Conclusion

A good website today means more than just technical soundness and well-structured pages. What matters equally is how clearly a company explains its services, how consistently it updates its content, and whether it’s present in the professional information ecosystem.

That’s why an audit is best thought of not as a one-time check, but as a way to see your site from a new angle. It frequently surfaces issues the website owner never suspected were there.

The Ai website audit covers:

indexation and technical accessibility of pages;
content quality and freshness;
expertise and trust signals;
brand mentions across external platforms;
current visibility in modern AI search services;
pages and topics that need improvement.

After the review, it becomes clear which changes to prioritize and where they’re most likely to make a difference.

Examples of using ChatGPT for SEO

Posted on October 30, 2025 by Max Zakhozhiy

Tasks such as clustering a semantic core, creating meta tags, finding keywords, and preparing structures for new articles are routine processes that take a considerable amount of time. However, they can be easily automated by integrating AI-based tools into your workflow.

In this article, we’ll discuss the use of ChatGPT in SEO work. We’ll go through examples and explain how it works. In other posts on our blog, we’ve already covered some AI-based services that can be useful for SEO professionals. So we invite you to check them out – while here, we’ll focus on how ChatGPT can become an assistant to an SEO specialist.

Creating optimized titles and meta tags

Page titles (Title) and descriptions (Description) have a strong impact on CTR in search results and on how pages rank in Google. Google’s algorithms require not only unique phrasing but also consistency with the page’s actual content. By using ChatGPT for SEO optimization, you can quickly generate dozens of versions of titles and descriptions for each page.

What you need for generation:

Add the page text into the chat window.
Specify the type of page – blog, product, category. For example: “A blog article about houseplant care.”
Give the task: “Generate 3 versions of Title (up to 60 characters) and Description (up to 160) for SEO, using keywords.”

This is especially convenient when you need to test variations quickly, adapt tags for different pages, and ensure style consistency.

Checking text for errors and translating to other languages at the native level

Today, most websites in Ukraine use two or even three languages. Translation is also relevant when working with technical documentation or specialized niches where information is mostly available in English. In such cases, it’s important not just to translate the text, but to adapt it to the cultural context. As a language model, ChatGPT handles this task far better than standard translators.

Simple guide:

Add the text to the chat and specify which language to translate it into.
Write a prompt like: “Translate as a native speaker, tone – formal/friendly/informative, text for a landing page.”
Once the translation is ready, review the terminology and stylistic adaptation, as ChatGPT can sometimes make mistakes.

As a result, you get text that sounds natural and requires minimal post-editing.

Researching information for content preparation

If there’s one thing ChatGPT excels at, it’s generating content structures quickly, selecting key points, and finding relevant information.

How it works:

You provide the topic of the article.
Specify the style, target audience, and approximate content length.
ChatGPT generates a content plan with subheadings, key ideas, and examples.

Example prompt:

“Create an outline for an article about how to choose a laptop for designers. Style – expert, for an online store blog.”

You can also use ChatGPT to draft a preliminary version of an article, saving up to 70% of the time usually spent on content preparation.

Technical SEO suggestions

AI tools can also assist with the technical side of SEO. Below are several examples of how ChatGPT can speed up and simplify a specialist’s workflow:

Generate short, logical, and SEO-friendly URLs based on page titles or keywords. Such URLs improve search engine indexing. If a URL includes a keyword, it increases relevance and clarity for users.
Create a heading hierarchy (H1, H2, H3) for better text structure. This improves readability, helps search engines understand content, and positively affects rankings.
Generate descriptive and relevant alt texts that fit the context of the page and include keywords. This is especially useful for product images, infographics, or blog visuals. Proper alt texts improve accessibility (especially for visually impaired users) and image search rankings.
Rename files before uploading to match the page topic and keywords. This improves SEO visibility in image search, clarifies file structure within the CMS, and prevents duplicates.
Assist in generating files such as robots.txt and llms.txt.

ChatGPT can also generate templates for robots.txt, sitemap.xml, or check page content for duplicate tags and incorrect HTML structure.

Keyword research with AI

While many aspects of website promotion have evolved, keywords remain the foundation of SEO. ChatGPT can help by assembling an initial semantic set, which you can later refine using professional tools.

How to structure your request:

Specify the topic and page type.
Ask for 10 – 15 keyword phrases.
Define the tone – conversational, informative, technical.

Example prompt:

“Find keyword ideas for a page about wireless headphones. Tone – consumer-friendly.”

Automating FAQs and structured data

ChatGPT greatly speeds up the creation of FAQ sections, which are important for EEAT (Experience, Expertise, Authoritativeness, Trustworthiness) and expanding the semantic core.

What AI tools like ChatGPT can do:

Generate informative answers considering synonyms and LSI keywords.
Adapt the tone of voice to the brand and target audience.
Build FAQ structures that improve user experience and indexing efficiency.
Automatically create Schema.org microdata in JSON-LD or Microdata format.

How it works:

Specify the page or product topic.
Ask: “Generate 5 frequently asked questions and short answers.”
Optionally, request the code in JSON-LD format.

Result:
Higher chances of appearing in SERP rich results, reduced time spent on manual writing, and improved productivity.

Competitor analysis

ChatGPT won’t replace in-depth analytics, but it can help build a basic understanding of the competitive landscape.

Quick guide:

Formulate the request and provide a brief description of your niche or a few competitor websites.

Example: “I work in the eco-products niche. Competitors – ecoshop.ua, ekoline.com, zerowaste.market. Provide a short overview of strengths and weaknesses for each.”
The model analyzes available information such as titles, site structure, positioning, product range, USP, client communication, UX, CTA, and visual style.
The result is a block summary or comparison table with main takeaways for SWOT analysis, USP definition, or positioning.

This information helps you understand what your site lacks compared to competitors and develop a stronger value proposition. Of course, such analysis does not replace SEO tools like Ahrefs, SimilarWeb, or Semrush, but it can be a useful starting point during the planning or initial audit stages.

ChatGPT for SEO automation

ChatGPT can help automate routine SEO tasks related to idea generation, text optimization, large-scale data analysis, and the creation of meta tags and headings.

Any AI tool for SEO is a helpful assistant – not a replacement for human expertise or the functionality of professional software. Artificial intelligence can enhance an SEO specialist’s skills, simplify their workflow, and significantly speed up their results.

What are the types of Artificial Intelligence systems?

Posted on August 5, 2025July 30, 2025 by Max Zakhozhiy

The pace of artificial intelligence implementation is growing rapidly, and this is only the beginning. AI is fundamentally changing the approach to developing digital solutions, as well as how companies interact with their customers, grow their business, and implement innovations.

In this article, we’ll look at the main types of artificial intelligence systems that can bring real benefits to business development.

What is artificial intelligence?

Artificial intelligence is a technology that enables computer systems to imitate human thinking: analyze information, learn from experience, make informed decisions, and forecast. AI operates based on algorithms capable of processing large volumes of data, identifying patterns, and constantly improving their own performance.

Key components of AI

Machine learning (ML) – a technology that helps systems identify patterns in data, generate insights, and learn from obtained information.
Deep learning is a subtype of ML that mimics the structure of human brain neural networks and allows complex, multi-layered data structures to be processed.
Neural networks – the foundation of deep learning. Consists of interconnected layers – input, hidden, and output – through which information passes, constantly improving through feedback.
Generative AI – a separate category that creates new texts, images, sounds, code, and other data based on existing information. Popular tools like ChatGPT showcase the potential of this technology, though its application scope is much broader.

Top 10 AI systems and their features

The artificial intelligence market changes daily – new tools appear, and existing ones become more accurate, flexible, and multifunctional. We’ve compiled the most popular AI systems, their features, and use cases in business.

ChatGPT – next-gen text generator

ChatGPT is a language model focused on text generation and processing. Its main task is to create responses in a dialogue format. Thanks to multi-level training on large volumes of text data, ChatGPT can generate logically structured texts based on context.

Capabilities:

automating customer support;
generating marketing content;
writing texts, scripts, resumes;
preparing training programs and interactive sessions.

ChatGPT easily adapts to tone, style, and subject matter, making it a universal tool for most text-based tasks.

Gemini – multimodal model with visual intelligence

Gemini is an AI system that combines text, image, video, and other data processing within a single model.

Capabilities:

multimedia content analysis;
generating descriptions for videos and images;
working with presentations, reports, and complex graphics.

Gemini stands out for its ability to process multiple types of information simultaneously, making it ideal for complex informational projects.

Copilot – developer’s assistant

Copilot is a tool for programmers integrated into code editors. Its main purpose is to assist in writing software. AI can suggest, complete, optimize code, and detect errors.

Capabilities:

speeding up software development;
training programming beginners;
auto-generating code fragments.

Copilot works well with various programming languages and adapts to the user’s coding style.

LLaMA – open architecture AI from META

LLaMA is a series of language models developed for research and educational purposes. It’s open to the community, enabling experimentation and custom product creation.

Used for:

academic research;
building custom language models;
developing internal company tools.

Its main advantage is the availability of code and models for modification, offering extensive customization options.

Mistral – compact and powerful AI for agents

Mistral is a language model focused on speed and computational efficiency. Despite its relatively small size, it delivers high-quality text generation.

Used for:

embedded systems and applications;
building lightweight language agents;
projects with limited computing resources.

Mistral offers a great balance between performance and resource usage, making it suitable for local deployment.

Midjourney – image generation AI

Midjourney is a generative model specializing in image creation. The user provides a textual prompt, and the system generates a visual result.

Capabilities:

concept art;
design, illustration, visualization;
character and scene development.

Midjourney demonstrates a unique artistic style and the ability to produce high-quality, detailed images.

DALL·E – turning text into images

DALL·E is a model that converts text prompts into images. It can interpret complex requests, blend abstract ideas, and visualize them.

Used for:

generating article illustrations;
creating marketing materials;
creative visual experiments.

Among its advantages are flexible interpretation and the ability to create surreal compositions.

Stable Diffusion – open-source image generator

Stable Diffusion is another powerful image and illustration generator available for local use and customization.

Capabilities:

artistic generation;
deep-tuned image creation;
integration into development environments.

With Stable Diffusion, you can control every part of the generation process — from style to quality.

Leonardo.ai – design-centric AI graphics

Leonardo.ai is a tool tailored for designers. It helps create unique graphical elements, fonts, covers, textures, and more.

Used for:

graphic design;
creating visual content for products and brands;
generating ideas and concepts.

It offers a wide range of styles, settings, and themes for generating high-quality graphics.

Runway ML – video generation and multimedia transformations

Runway ML is a platform for generating video, processing images and sound, and applying effects with AI tools.

Capabilities:

video editing;
creating visual content without complex software;
speeding up processes in film, advertising, SMM.

Its advantage is the combination of video and graphic tools in one intuitive system.

Promoting your business with AI

Effective marketing involves working with data, accurate insights, and dynamic strategies. That’s where AI becomes an indispensable tool. It not only automates routine tasks but also helps create a personalized approach for each client, increase campaign efficiency, and optimize spending.

Let’s explore AI’s benefits for business promotion in more detail.

Audience analysis and segmentation

AI can process large amounts of customer data. It analyzes demographics, purchase history, social media activity, preferences, and engagement. Algorithms form accurate target groups and identify the most promising segments for ad targeting. This helps focus resources on high-potential customers instead of uninterested audiences.

Personalized marketing and dynamic offers

AI can create individual messages based on previous user behavior. For example, if a customer viewed a product, AI can send a reminder, a special discount, or similar suggestions. This boosts conversion and brand loyalty.

Advertising campaign optimization

AI can manage ad campaigns automatically:

test multiple creative versions;
identify the most effective combinations of headlines, text, and images;
allocate budget across platforms (Google Ads, social media, email) based on performance.

It analyzes results in real time and adjusts strategies without human input.

Predicting outcomes and customer behavior

AI analyzes past campaign data, combines it with current trends, and models likely outcomes – expected conversion, average check, time to purchase, churn rate. This helps plan budgets, choose communication channels, and adjust content before launching a campaign.

Data-driven content marketing

AI helps create texts, posts, product descriptions, video scripts, and even graphics.

It can:

analyze which topics work best for your target audience;
select keywords for SEO;
build a publishing calendar;
evaluate content performance via engagement and feedback.

AI doesn’t replace creativity but enhances it with data, enabling more relevant and appealing content.

Competitor and market analysis

AI automates competitor monitoring – their promotions, messaging, pricing, and audience reactions. It reveals which approaches work in your industry, reduces risks, and helps pivot your strategy. AI also tracks trends and forecasts which products/services will grow in popularity.

Customer experience and feedback

AI tools gather and process feedback, transcribe calls, and analyze social mentions. This helps identify weaknesses in service, fix issues, and improve brand interaction. AI can even predict customer churn and trigger retention actions – offers, bonuses, personalized support.

The value of AI as a tool

Artificial intelligence empowers modern businesses to rethink marketing strategy, promotion, customer acquisition, and retention.

AI provides tools for personalization and marketing optimization. It boosts operational efficiency and enables deeper understanding of consumer behavior, helping inspire new products or services.

AI enhances, simplifies, and automates – allowing professionals to focus on strategy, creativity, and emotional connection with their audience.

How to use AI in digital marketing

Posted on March 20, 2024April 2, 2026 by Max Zakhozhiy

The utilization of artificial intelligence-based tools has experienced a surge in popularity in recent years. Increasingly, businesses, particularly small and medium-sized enterprises, are turning to these tools for the creation of marketing content.

In this article, we will delve into the landscape of AI services and programs tailored for generating graphic and video content. We will explore their benefits and drawbacks, as well as assess their efficacy. Additionally, we will examine several examples of how different brands have successfully employed these tools. Keep reading to discover how modern neural networks can elevate your marketing campaigns.

The role of AI in digital marketing today

Artificial intelligence holds a pivotal role in contemporary digital marketing, ushering in new possibilities with its speed and accessibility. AI facilitates the swift and automated generation of content for marketing campaigns, enabling the creation of banners for Google advertising campaigns or creatives for Facebook ads from the comfort of your own home.

Today, a plethora of services exist that allow for the creation of graphics and videos within minutes. This not only boosts the productivity of marketers but also enhances the effectiveness of their efforts.

In the following sections of this article, we will explore various services that can be effectively utilized for crafting graphics and videos. We’ll delve into their features, and pricing policies, and showcase examples of how different brands have successfully leveraged these tools. Continue reading to discover how you can revolutionize your marketing strategy with cutting-edge techniques.

Harnessing AI for Graphic and Video Content Creation

Through neural networks, you can now effortlessly generate illustrations, logos, banners, and various graphic assets. Additionally, AI can convert text into video content or generate video clips based on textual queries, presenting novel avenues for crafting marketing campaigns.

The array of AI-based services and programs available today is truly astounding. With their popularity soaring, new tools of this nature are continuously emerging. In this article, we will explore the most popular and top-performing options in the market.

The most popular AI services for creating graphic content

MidJourney

It’s rare to come across a marketer unfamiliar with this tool. It stands as one of the most renowned neural networks for generating graphic content, widely recognized and utilized across the globe. Launched in 2022, it sparked a significant revolution in the realm of graphic content creation for marketing endeavors.

This AI-powered tool excels in producing images based on text queries.

Pros:

The service yields four image options per request, providing ample choices.
Users can access additional variations of graphic materials on the same topic if desired.
Customization options allow users to specify details and preferred image styles for optimal results.
Further enhancements to generated images are possible with the aid of additional tips and instructions.
Operates at high speed (though reduced image generation time is exclusive to paid subscriptions).

Cons:

Lacks support for corporate branding.
Integration with social networks is unavailable.
Service functionality is limited to English.
Quality of images depicting full-length people may occasionally fall short (e.g., incorrect number of fingers on hands).

Pricing:

Free trial: 25 images
Basic plan (3.3 hours of rapid graphic content generation per month): $10/month
Standard package (15 hours): $30/month
Professional tier (30 hours): $60/month

Designs.ai

This versatile tool caters to a broad spectrum of tasks. Unlike MidJourney, Designs.ai isn’t limited to illustrations; it extends its capabilities to create graphic materials of various types, including logos, banners, site mockups, and more specialized designs.

Pros:

Extensive library of ready-made design templates, comprising 20,000 templates and 10,000 icons for versatile usage.
AI-driven creation of thousands of designs.
Font pair selection feature for harmonious typography.
Option for vector graphics.
Functionality for selecting color combinations that complement each other within a design.

Cons:

Initial results may not always meet expectations, requiring iteration.
Absence of technical support could hinder the learning curve for mastering all features.
PSD format files are saved as a single layer, limiting editing capabilities on individual layers.

Prices:

Free trial version available for 7 days.
Basic plan: $19/month.
Pro plan: $49/month.
Enterprise plan: $169/month.

DALL-E

This robust tool from OpenAI is a powerhouse for image creation and editing through artificial intelligence. Leveraging deep learning techniques, it crafts illustrations based on textual and visual inputs, ensuring top-notch content tailored to user preferences.

Pros:

Precision in interpreting every word within prompts, thanks to advanced neural network algorithms, resulting in highly personalized outcomes.
Ability to incorporate text onto images, such as inscriptions on clothing, albeit limited to the Latin alphabet for optimal performance.
Enhanced generation of hand images, addressing a common issue encountered in other services.
Seamless integration of multiple objects into a single image for a realistic composition.
Respectful approach to copyright, refraining from generating images if prompts include the name of a living artist or photographer to avoid copyright infringement. Users retain copyright ownership of uniquely styled images.
API compatibility for streamlined usage.
Flexible pricing model offering packages of requests instead of monthly subscription plans, ideal for occasional AI usage by small businesses.

Cons:

Inability to create vector graphics.
Challenges in rendering Cyrillic text accurately on images.
Occasional shortcomings in detail and naturalness of images, particularly in realistic styles.

Prices:

Free plan includes 50 requests.
115 requests: $15.

Canva AI

Canva, a well-established graphic editor, has recently introduced its AI Image Generator and AI Video Generator. These tools create images and videos based on text queries.

Pros:

Full functionality available in the free version of Canva.
Swift performance.
User-friendly interface, making it accessible even to novices unfamiliar with AI tools.

Cons:

AI exclusively processes text queries; visual prompts are not supported.
Images exhibit a lower level of detail and realism.
Generating quality content may require multiple attempts due to a high error rate.

Prices:

Free version.
Pro plan with advanced features: $119.99 per year.
Team plan: $300 per year for up to 5 users.

The Top AI Services for Video Content Creation

Synthesia

Synthesia offers a video generator that transforms text material into videos featuring an “avatar” delivering the information. This tool is particularly well-suited for crafting video courses.

Pros:

Capability to generate videos from text in over 120 languages.
Customizable avatars and voices for a personalized touch.
Option to incorporate images into the videos.
Highly realistic avatars convincingly delivering the text content.
Extensive library of background images and music tracks.

Cons:

Avatars’ movements and gestures are somewhat limited.
Rendering process may be slow at times.

Prices:

Starter plan: $22/month.
Creator plan: $67/month.
Enterprise plan tailored for large companies, with pricing discussed individually based on specific requirements.

DeepBrain AI

Another option for producing text-based video content operates on a similar principle to its predecessor. Users upload text and select an “avatar” to narrate it in the video.

Pros:

Realistic avatars are modeled after actual individuals.
A selection of over 100 avatars to choose from.
Support for 80 languages.
Pre-designed templates for various content types.
Enjoy a 20% discount with annual payment.

Cons:

Video duration limitations (up to 10 minutes per video for the Starter plan, up to 20 minutes per video for the Pro plan).
Subscription costs are relatively high.
Pricing is based on the minutes of the generated video.

Prices:

Free trial includes 1 video.
Starter plan starts from $30 per month.
Pro plan starts from $225 per month.
Enterprise plan offers individualized pricing.

Pictory AI

This modern AI-powered tool is designed for generating and editing videos, making it an ideal choice for crafting YouTube or Facebook ads.

Users can create clips based on short text prompts, blog articles, or existing videos. The tool utilizes a vast library of 3 million clips, music compositions, and photos to generate videos tailored to user preferences. Voiceover options include both manual recording and AI-generated narration.

Pros:

Automatic adjustment of SEO parameters, such as headings and tags.
Ability to add effects, text, and other elements to videos.
Editing capabilities for fine-tuning created videos.
Option to generate short videos from longer ones.
Enjoy a 15% discount with an annual subscription.

Cons:

Limited video editing features; more complex edits may require additional software.
AI-generated voiceovers may lack realism.
Occasionally, some images used in the video may not align perfectly with niche requirements.

Prices:

Free trial includes 3 videos.
Starter plan: $23/month.
Professional plan: $47/month.
Teams plan: $119/month.

InVideo

This versatile tool facilitates the creation of educational videos featuring talking “avatars,” as well as slideshows and clips, making it suitable for YouTube and social media content creation.

Pros:

Built-in script generator powered by AI streamlines the video creation process.
Over 5000 ready-made templates for various video types.
Realistic voices narrate the videos.
Comprehensive instructional videos on how to use the service, making it accessible even to beginners.
Mobile compatibility for both Android and iOS devices.

Cons:

Lack of direct video upload feature for YouTube or Facebook.
Limited video editing capabilities compared to other platforms.
Subscriptions are available only on an annual basis, without monthly payment options.

Prices:

Free version includes watermarked videos.
Business plan: $180 per year.
Unlimited plan: $360 per year.

Examples of content created by brands using AI

San Francisco Ballet used an image generated by the MidJourney neural network to illustrate a promotional post on social media. Instagram networks:
The well-known alcoholic beverage brand Martini used 9 images created in MidJourney during the creation of a marketing video:

The IT company in the field of cyber security Cyber Inc creates its video courses in various languages with the help of artificial intelligence Synthesia:

Advantages and Disadvantages of Utilizing AI for Small and Medium-Sized Businesses

Advantages:

Optimization and Streamlining of Processes: AI can provide several design or video options within minutes, significantly reducing the time it takes for manual creation.
Enhanced Creativity and Innovation: By automating routine tasks, AI allows marketers to focus on strategic planning and brainstorming for new ideas, fostering a more innovative marketing approach.
Cost Reduction in Marketing Campaigns: Small businesses can avoid purchasing stock images or hiring freelance designers by leveraging AI. Medium-sized businesses can expedite the work of in-house designers, reducing the cost per material produced.
Source of Inspiration: AI can assist designers in overcoming creative blocks by generating initial content and offering diverse ideas, which designers can then refine to meet brand requirements.

Disadvantages:

Limited Consideration of Corporate Style: AI may not fully comprehend all aspects of a company’s corporate style, necessitating human intervention for complex tasks requiring high personalization.
Learning Curve: Mastering AI tools for image creation requires time and effort. Alternatively, businesses may need to hire experienced designers proficient in AI tools to expedite the process.
Inconsistent Quality: AI-generated content may not always meet expectations, especially for inexperienced users. Additionally, some images may lack realism compared to manually created content.
Language Barrier: Many AI services have English interfaces, potentially posing challenges for non-English speakers and requiring the use of translation tools.

Best Suited Tasks for AI:

Simple Routine and Monotonous Tasks: AI excels at handling repetitive tasks efficiently, freeing up human resources for more complex projects.
Illustrations Without Complex Details: AI-generated illustrations are cost-effective alternatives to purchasing individual stock images, particularly for content not requiring intricate details.

Conclusions:

AI tools offer significant benefits for certain tasks, enabling faster and more cost-effective content creation. They empower businesses to allocate resources efficiently, allowing designers to focus on strategic initiatives and creative endeavors. While AI-generated content may not always match human quality, its speed and affordability make it a valuable asset for small and medium-sized businesses seeking to elevate their marketing efforts.