ChatGPT Became the Face of AI—But the Real Battle Is Building Ecosystems, Not Single Models

Written by hacker53037367 | Published 2025/09/17
Tech Story Tags: ai | artificial-intelligence | artificial-intelligence-(ai) | chatgpt | ai-tools | ai-tools-for-business | automation | test-automation

TLDRChatGPT made AI mainstream, but real transformation comes from ecosystems that embed AI across business, not from relying on a single model.via the TL;DR App

Why do you think that when we say the words ‘artificial intelligence,’ the first thing that comes to mind for most people is ChatGPT? Not MidJourney, not Copilot, not Gemini, or dozens of other models already in use in business, but ChatGPT. The answer is very simple: OpenAI was the first to turn AI into a mass product rather than an academic toy. They didn't just build a model — they created a phenomenon.


In an era where speed is everything, OpenAI has clearly shown entrepreneurs and companies that launching a product and making a name for yourself should not be done ‘sometime in the future,’ but yesterday. That is why ChatGPT has become not so much a technology as a symbol. A symbol of the accessibility of AI, a symbol of ‘start here’ and proof that new business tools are indeed being born outside of laboratories and start-up incubators.


And this is where it gets interesting. Because ChatGPT is just one tool. Yes, it is powerful. Yes, it has changed the landscape. Yes, we recently got an excellent version of ChatGPT 5 and a £200 ‘Pro’ subscription. But it is still a limited model, with its own constraints, blind spots and weaknesses. The real power of AI lies in the ecosystem, in the integration of multiple solutions that can not only help write texts and create viral reels (something like a cute kangaroo detained at the airport), but also manage business processes, forecast demand, automate sales, and build new business models. That's why if you only look at ChatGPT, you can easily fall into a trap. It's like judging the music industry after hearing one hit on TikTok. It may be bright, memorable, and even catchy, but the real depth and power lie beyond the hype.




Why ChatGPT has become a symbol of the AI revolution


ChatGPT has become a kind of ‘Google’ in the world of artificial intelligence. Not because it is the only one or the best, but because it was the first to break through the sound barrier of mass consciousness. Millions of people started using it literally ‘off the street’ — without instructions, without a PhD in machine learning, without fear of code. And this simple ‘come in and try it’ approach was OpenAI's genius marketing move. 


Let's be honest: no one discusses complex climate prediction models in the kitchen. Even MidJourney, with all its visual ‘wows,’ remains in the niche of designers and creators. But ChatGPT has become part of everyday conversation. It has turned into a meme, a universal answer to any question, and even a joke along the lines of ‘can't you ask GPT?’ That's real popularity. But it's important not to get confused here. ChatGPT is not the whole of AI. It is just one model: useful, but limited; inspiring, but with distortions and hallucinations. It confidently invents sources and confuses facts. And if an entrepreneur or company thinks that AI = ChatGPT, then they are, to put it mildly, underestimating the scale. 


The main lesson is different: ChatGPT has become a symbol because it has shown that speed and simplicity are everything. OpenAI rolled out the product at a time when others were still arguing about risks and regulations. They presented the market with a fait accompli: ‘AI is already here, and either you start using it or you'll be playing catch-up in a couple of years.’ In business, this is lesson number one: speed is more important than perfectionism. 


And here it is worth remembering how Google screwed up. Sorry, Google. The company, which for decades held the title of ‘search king’ and set the standards in AI research, launched Bard (later Gemini) in such a way that it looked like a poorly prepared sprint: errors in the demonstration, inaccurate answers, and a drop in shares worth billions. It became a public spectacle of how even giants lose if they don't know how to launch a product properly. This isn't the first time Google has missed the mark, by the way. Remember Glass or their endless experiments with messengers — from Hangouts to Allo. The technology was there, but it didn't become a mass-market product. That's the key difference between ‘technological superiority’ and ‘market leadership.’ That's why ChatGPT is not just a tool, but also a signal. A signal that the era of ‘let's wait until the technology matures’ is over. Today, it is not the one with the most perfect model who wins, but the one who is quickest to integrate it into the everyday lives of millions.



Number of monthly ChatGPT and Gemini mobile app downloads worldwide from May 2023 to March 2025


Beyond ChatGPT: where AI is truly transforming business


If we reduce artificial intelligence to ChatGPT, we are making the same mistake as companies that once decided, ‘We don't need the internet, we have the telephone.’ Yes, ChatGPT is convenient and has become a symbol of a new era, but fixating on a single tool is a trap. Real transformation happens when AI is embedded at all levels of business, from marketing to analytics and strategic decision-making.


AI is not a single model, but an entire ecosystem that automates routine tasks, empowers teams and creates competitive advantages. And we're not just talking about start-ups. Major corporations, banks, retailers, and educational platforms are already restructuring their processes so that soon, ‘working without AI’ will be as absurd as doing accounting manually on paper today. To understand the scale, just imagine a company where AI is integrated not just in specific areas, but systemically. Not an intern entrusted with writing captions for posts, but a full-fledged operational framework: algorithms collect data, predict trends, generate creative content, purchase media, and prepare reports faster than your CFO can open Excel. Such structures cease to be ‘contractors’ and become hybrid AI companies that work not on deadlines, but on the speed of algorithms.


And here I can speak not only as an observer, but also as a practitioner. My first experience with a marketing agency in Ukraine was more of an anti-case study: without automation, the business turned out to be difficult and slow. This lesson showed me that without the right infrastructure, you cannot survive. That is why when I talk about the ‘marketing agency of the future,’ I am not describing a fantasy, but what I am building today.


Let's imagine the marketing agency of the future together. Not a dreary office in WeWork with coffee from a capsule machine and endless layout revisions, but a company where artificial intelligence is built into every process. Here, AI is not a sidekick, but a full-fledged ‘business engine’: it collects data, predicts trends, generates creative ideas, and buys media. Such an agency can no longer be called an ‘advertising contractor.’ It is a hybrid AI company that works not with human hands on deadlines, but at the speed of algorithms. And it is precisely such structures that will set the rules of the game in a few years: how brands build communication and how advertising budgets are distributed in a world where speed is more important than perfection.


Starting a business in 2025 without AI is like launching an airline without planes. Theoretically, it's possible, but you won't get very far. Artificial intelligence is no longer an ‘add-on’ but is becoming the basic infrastructure on which a company is built: from how resources are allocated to how strategic decisions are made. And if before a start-up began with an Excel spreadsheet, a couple of designers and endless briefs for copywriters, the agency of the future starts with AI tools that cover key business functions even before the first employee is hired.


That's why, when I launched Global Tech & AI Publishing House in London, I consciously chose a different path. From day one, AI became the basic infrastructure — from content and analytics to audience engagement. This allowed us to build a system faster and more flexibly than was previously possible. For me, this is not theory, but practice: the agency of the future is what I am creating right now.



AI in automation. The healthcare, finance, and manufacturing sectors have the biggest AI market share


How to kill Excel before your first meeting with investors: internal processes


In any business, chaos begins internally. Before coming up with a slogan for a client or building a media plan, the team is drowning in tasks, files, and endless approvals. Startups live in Slack, agencies live in Excel, and corporations live in endless ‘final versions’ of presentations. Time wasted on internal organisation can easily eat up to 30% of a project's budget before the client even sees the first result.


In the agency of the future, this is remedied immediately. We launch Notion AI as the company's single brain. Instead of dozens of documents scattered around, there is a single knowledge base: from contract templates to workflows. AI automatically structures notes, creates checklists, and helps employees find the information they need in seconds. We connect Zapier AI or Make.com for routine automation. Any repetitive task (from creating a brief to reminding someone to pay a bill) flies through the chain automatically. This is not a makeshift solution, but a bundle of services that works flawlessly and saves hours every week. If we need to write code for internal tools, we connect to GitHub Copilot. It turns a business idea into a working prototype: it generates code, suggests optimal solutions, and completes technical tasks faster than they can be discussed in a meeting.


The result:

The agency starts with a clean system, not chaos. There are no unnecessary approvals, no lost files, and no missed deadlines. The team works cohesively, clients receive quick responses, and internal processes become fuel for growth rather than a hindrance. And this is not just theory — this is exactly how I build processes at Global Tech & AI Publishing House.


The social economy: Unlocking value and productivity through social technologies


A strategy based on data, not intuition: analytics and forecasting


In my practice, this is no longer theory: AI analytics is really changing how we make decisions. Most agencies still build their strategy ‘by eye’. Analytics turns into 100 PowerPoint slides that no one reads, and forecasts are based on one magic word: ‘experience.’ The problem is that experience often means ‘we did it this way last year and everything was fine.’ In an era when markets change in a matter of weeks, this logic is a one-way ticket to failure.


In the agency of the future, analytics is not a separate ‘department of people with dark circles under their eyes,’ but an AI system that works 24/7 and digests terabytes of data faster than an analyst can build the first graph in Excel.


We connect Power BI Copilot: it not only visualises data, but also suggests why demand is changing, which segments are growing and which channels are no longer working. Not graphs for the sake of graphs, but real-time recommendations for business. We use Tableau AI: instead of manually digging through reports, it builds predictive models. For example: ‘the probability that TikTok campaigns will stop working in three months’ or ‘which product will take off by the next quarter.’ We add SimilarWeb AI and Crayon for competitive analysis. No more guessing what competitors are doing — AI immediately shows which channels they are spending their budgets on, which keywords they are testing, and how their strategy is changing.


The result:

The strategy is built not on shouting during conference calls, but on forecasts that can be verified with numbers. The client doesn't get a fancy presentation in a month, but a working model of the market ‘here and now.’ The agency ceases to be a ‘creative service’ and becomes a strategic partner that predicts the market and keeps the client two steps ahead.


Where brainstorming ends and AI creativity begins: creativity and content


Traditional creativity in agencies looks like this: endless brainstorming sessions, a wall covered in yellow sticky notes, and arguments about which slogan will ‘resonate with the audience.’ More often than not, it's not the best idea that wins, but the one with the loudest presentation. In my agency of the future, this ritual is consigned to the museum.


We use Jasper and Copy.ai for texts: they create dozens of options for slogans, descriptions, and email campaigns in minutes. Copywriters no longer get stuck on the word ‘perfect’ but immediately work with a pool of ideas and adapt them to the desired brand tone. We have a whole arsenal of visuals. MidJourney turns a brief into atmospheric images, Runway Gen-2 generates videos for campaigns, and Leonardo AI goes even further — it allows you to build entire settings and concepts for advertising campaigns, creating stylised worlds and ready-made branding elements. Whereas such a level of detail used to take weeks and tens of thousands of dollars, it is now available in a day and for the price of a cup of coffee.


The result:

Creativity is no longer a bottleneck that slows down the campaign. The client receives dozens of ideas at once, and the agency team works not on ‘what to come up with’ but on ‘what will actually work.’ Speed increases, quality increases, and subjective disputes decrease — because data and AI don't have a favourite slogan, they have metrics.


AI as a salesperson who never sleeps and is always polite: sales and customer service


The classic sales and support department is a mixture of heroism and chaos. Someone forgets to call a customer back, someone responds to a message a day late, and someone writes a support email that makes you want to print it out and burn it. The agency of the future starts differently.


We connect HubSpot AI as the CRM core. It analyses customers, segments the audience, and suggests when and how best to contact them. Instead of the manager manually remembering who wanted what a month ago, the system reminds them in advance: ‘this customer is ready for an upsell’ or ‘it's time to renew the contract.’ For live communication, we use Intercom AI or Ada. These chatbots don't just answer standard questions; they engage in full-fledged dialogue, collect data, and solve 80% of routine tasks without human intervention. If the conversation becomes complicated, it is automatically transferred to a manager, but with full context. No ‘repeat your order number’ required. For larger clients, you can connect Salesforce AI: it forecasts sales, calculates the probability of closing a deal, and helps build a negotiation strategy. This is no longer an assistant, but in fact a ‘second brain’ for the sales department.


The result:

Sales and service cease to be a chaotic quest and turn into a predictable system. Customers receive quick and accurate responses, employees experience less burnout, and the agency spends fewer resources on ‘manual work.’ In a world where speed is everything, having an AI salesperson and AI support is not a ‘nice bonus’ but a matter of survival.


The end of PowerPoint zombies: metrics that explain themselves


If there is one thing that both clients and agencies hate equally, it is reports. Clients hate reading them, agencies hate compiling them. Every week, someone manually copies numbers from Google Ads, pastes them into PowerPoint, and decorates them with graphs that no one really looks at anyway. As a result, all the ‘analytical work’ boils down to pretty pictures with captions like ‘+3% growth.’


In the agency of the future, this ritual is no longer necessary. We connect Tableau AI or Power BI Copilot, and reports are compiled in real time. No more manual data copying: AI aggregates the numbers, builds dashboards, and even formulates key conclusions. For clients, it looks like magic: they open the dashboard and see not just numbers, but an explanation of why CTR has increased, why CPC has fallen, and what this means for their business. If necessary, AI generates a short text report that can be sent to the board of directors without unnecessary edits.


The result:

The agency ceases to be a factory of PowerPoint zombies and becomes a true business partner. Clients get transparency and speed, the team saves dozens of hours per month, and decision-making no longer depends on who managed to make ‘yet another version of the report.’


And let's face it: ChatGPT is just the front door to the world of AI. But if your business is stuck in that hallway and is still playing ‘make me a LinkedIn post,’ then congratulations — in a year, your competitors will be treating you to coffee in their new office. And they may discuss you in the same way that the entire market discussed Google after their failed launch of Bard: ‘Well, it happens, they didn't make it in time.’


A real AI business is built not on a single model, but on an ecosystem. Those who assemble tools into a system — from Notion and Zapier to Salesforce and Tableau — turn their company into a machine that works faster and smarter than any traditional agency. For decades, Google was considered a symbol of technological superiority, but they were the one that showed the world that ‘being smarter’ is not enough. You have to act faster.


You don't have ten years to ‘wait for everything to settle down.’ In the digital economy, it's not the smartest or even the richest who survive. The most flexible survive. So either you integrate AI today, or tomorrow you'll watch your competitors take your budgets, customers and market share. And, if Google's lesson is anything to go by, believe me: catching up later will be many times more painful.


So are you in this race, or are you going to write a thesis on why you failed?


Written by hacker53037367 | AI Marketing & Digital Transformation Strategist | Google Product Expert | Forbes Web3 | BIMA 100 People UK | Author of
Published by HackerNoon on 2025/09/17