What is Artificial Intelligence, How Does It Work and How to Use It
Artificial intelligence is no longer just the subject of technology companies, software developers or science fiction movies. Today, there is artificial intelligence in many systems that we are aware of or not, from the applications that edit the photos on our phones to the search engines we use, from social media streams to customer services, from automobiles to production facilities. With the rapid spread of generative AI tools in the last few years, artificial intelligence has turned into a technology that individual users can directly access. It is now possible for a person to produce visuals without writing code, to summarize a long report in seconds, to practice speaking in a foreign language, to develop an advertising idea for a product, or to complete the first stage of research that could take hours in a few minutes.
But as artificial intelligence enters our daily lives so rapidly, the concept itself is sometimes oversimplified. Artificial intelligence is not just ChatGPT. It is not a chatbot. It is not just a system that creates photographs. The field we call “AI”; It covers a wide world of technology, from machine learning to natural language processing, from image recognition to recommendation systems, from robotics to generative artificial intelligence models.
Therefore, to truly understand artificial intelligence, we need to start with the most basic question: What is artificial intelligence?
What is Artificial Intelligence and What Does It Actually Try to Do?
Artificial intelligence is the general name for methods and technologies that enable computer systems to perform some tasks that we normally associate with human intelligence. Learning, classification, prediction, language understanding, image recognition, problem solving, content production and decision support processes can be counted among these tasks.
The important point here is that artificial intelligence does not have to be a "computer that thinks like a human." Most of the artificial intelligence systems we use today have been developed to be very successful at certain tasks. For example, a system can recognize cats among millions of images, another system can predict which movie people might like based on their viewing habits, and another model can understand the text we write and create an answer in a natural language.
ChatGPT, Gemini, Claude, Midjourney, Runway, Suno or similar tools that have entered our lives in recent years have made the generative AI side of artificial intelligence visible. These systems not only analyze existing data; It can also produce new content such as text, images, video, sound, music or code.
Simply put, artificial intelligence is the field of technology that enables computers to use data to perform certain tasks smarter, faster and often more automatically.
How Does Artificial Intelligence Work?
To understand how artificial intelligence works, it is necessary not to think of it as a magic black box. AI systems are based on data, mathematical models and computing power.
An artificial intelligence model is often trained on very large amounts of data. The system tries to learn the relationships, patterns and repetitions within this data. For example, an image recognition system trained on thousands of photos of cats and dogs could, over time, learn visual features that help distinguish cats from dogs. A language model learns how words, sentences and concepts are related to each other through large collections of text.
In Generative AI systems, this process goes even further. While large language models produce text by probabilistically predicting what the next word or token might be, image models can create new visuals in response to a given prompt. For this reason, the answers given by AI are often not pre-written ready-made information; The model produces a new output based on the patterns it has learned.
This feature also constitutes both the power and one of the most important risks of artificial intelligence. Because the model may produce an answer that sounds very convincing but is not actually true. One of the most well-known examples of this in the AI world is called “hallucination”.
What is the Difference Between Machine Learning, Deep Learning and Generative AI?
Many similar concepts are used when discussing artificial intelligence. Artificial intelligence can be considered as the broadest umbrella of these.
Machine learning is a set of methods that enable computer systems to learn patterns from data without having to program each rule one by one by a human. A bank predicting suspicious transactions or an e-commerce site recommending products to a customer may be examples of machine learning applications.
Deep learning is a more advanced subfield of machine learning. It works on complex data, especially images, speech and natural language, using artificial neural networks.
Generative AI, on the other hand, refers to systems that can create new content such as text, images, audio, video or code. When it comes to AI today, most of the technology that everyday users encounter is now in this field.
Therefore, a language model like ChatGPT, an image generator like Midjourney, or a music production system like Suno are parts of the generative AI family, even though they perform different tasks.
What are the Types of Artificial Intelligence?
Artificial intelligence can be classified in different ways according to its capabilities. One of the most well-known classifications is the distinction between narrow artificial intelligence, general artificial intelligence and super artificial intelligence.
Almost all of the systems we use today are considered in the Narrow Artificial Intelligence (ANI) category. These systems can show high performance on certain tasks. A language model can produce text, a navigation system can calculate a route, or an image model can generate photographs. However, none of these have all the capabilities of human intelligence.
General Artificial Intelligence (AGI) refers to systems that have general abilities similar to the human capacity to learn, reason and solve problems in different areas. Although technology companies and researchers are working intensively on AGI, today we cannot talk about a system with general intelligence at the human level on which there is a consensus.
Super Artificial Intelligence (ASI) is a theoretical system that can surpass human intelligence in almost every field. It is not a practical technology today, but rather the subject of academic and philosophical discussions about the future.
It is important to know this distinction; Because human consciousness or human-like general intelligence can sometimes be attributed to existing AI models on social media. However, even though the systems we use today have extraordinary capabilities, it would be misleading to think of them as exactly the same as the human mind.
How to Use Artificial Intelligence?
The first step in making efficient use of artificial intelligence is choosing the right tool for the right task. Because we are no longer talking about a single artificial intelligence, but hundreds of specialized AI tools.
If you want to write text, develop ideas, analyze or start research, general purpose models such as ChatGPT, Gemini or Claude can be used. For current web research and resource collection, research-oriented systems such as Perplexity may be preferred. Midjourney, Recraft, Ideogram or Adobe Firefly for visual production; Runway, Kling, Luma or Higgsfield in video production; Suno or Udio in music; ElevenLabs in voiceover; Gamma in presentations; There are different tools such as Lovable, v0 or Bolt for website and application production.
The important thing here is not just to give the AI a short order, but to define the task as clearly as possible.
For example:
“Give me an advertising idea.”
Instead of saying:
“Develop an Instagram Reels campaign for a new coffee brand targeting users aged 18-30. The brand should look warm, young and premium. Do not use discount communication. Explain the main idea, slogan, three Reels scenarios and visual world of the campaign.”
A prompt like this can produce much more controlled results.
A good AI prompt should generally include purpose, context, target audience, constraints, and desired output format.
It is not necessary to accept the first answer received from artificial intelligence as the final answer. Follow-up prompts like “critique these ideas,” “make them more original,” “remove clichés,” “compare the three best options,” or “find the weak points in this answer” make using AI much more professional.
What Can Be Done with Artificial Intelligence?
Today, it is almost impossible to limit the areas of artificial intelligence usage to a few examples. Because AI can be used in different ways in different sectors.
On the content and marketing side, blog drafts, social media ideas, advertising texts, scenarios, content calendars and campaign analyzes can be created. On the design side, moodboards, concept visuals, product photographs, illustrations, logo drafts, storyboards or social media creatives can be prepared. On the video side, completely artificial images can be produced with text-to-video and image-to-video technologies.
With AI, developers can write code, have existing code analyzed, find bugs or develop prototypes. Students can summarize long documents, explain topics at different levels, and create study questions. Sales teams can conduct prospect research, analyze meeting notes or draft proposals.
E-commerce brands can benefit from a wide range of AI ecosystems, from product descriptions to product photos, from customer segmentation to chatbots. Human resources teams can use AI in their CV processes, manufacturing companies in their quality control systems, and logistics companies in demand and route forecasting.
For this reason, the "area of use" of artificial intelligence is no longer a sector on its own. AI is increasingly turning into a technology layer that works across industries.
Artificial Intelligence We Use in Daily Life Without Realizing
Artificial intelligence was actually in our daily lives long before ChatGPT emerged.
AI-based systems can be used to help Netflix or Spotify suggest what you should watch or listen to, social media platforms to decide which posts to show, Google Maps to create routes based on traffic conditions, email services to sort out spam messages, or a phone camera to automatically improve the photo you take.
Banks' detection of fraudulent transactions, e-commerce sites' creation of product recommendations, or automatic referral systems in customer services have long been examples of daily use of artificial intelligence.
The difference of Generative AI is that it transfers the user from the passive side to the active side. Now, in addition to being a system that makes decisions for us in the background, artificial intelligence has turned into a working tool with which we directly talk and produce content together.
How is Artificial Intelligence Used in the Business World?
One of the most important impacts of AI in the business world is that it changes the boundary between automation and decision support.
In the past, automation generally involved tasks that were repetitive and had clear rules. Today, generative AI can also help with more obscure tasks. Summarizing a report, classifying customer conversations, analyzing hundreds of comments, creating content variations, or extracting action items from a meeting can now be powered by AI.
Marketing teams can find new insights by analyzing consumer comments. Agencies can expedite the first drafts of creative ideas. Sales teams can produce personalized emails. Software teams can use AI coding assistant. Customer services can be supported by chatbot and agent systems.
But there is an important distinction here: Using artificial intelligence is not a business strategy itself.
A company does not complete its “AI transformation” by simply opening a ChatGPT account to its employees. It is necessary to determine which processes will be supported by AI, ensure data security, train employees, measure outputs and define where human control is required.
True AI transformation is less about buying a new tool and more about reimagining the way business is done.
Artificial Intelligence in Design and Advertising
One of the most visible effects of artificial intelligence is experienced in creative industries.
An art director can now produce dozens of visual concepts in a few hours. A storyboard can be made entirely with AI. A product can be visualized in different advertising scenarios before it is physically produced. A video director can create AI animatics of the scene before actual shooting.
However, this does not mean that "there is no need for a designer anymore". On the contrary, the ease of production increases the importance of creative decisions.
AI can create hundreds of beautiful images. But it is still necessary to evaluate which one belongs to the brand, which one serves the right strategy, which typography to use, or whether the idea is truly original.
In the age of artificial intelligence, the value of the creative sector is increasingly shifting from "being able to produce something" to "knowing what is worth producing".
How Can Artificial Intelligence Be Used in Education?
Artificial intelligence offers extraordinary opportunities in terms of education. A student can have a subject he or she cannot understand explained in different ways, have questions prepared according to his or her level, practice speaking a foreign language, or create a personal study guide from his or her own resources.
For example:
“Explain this physics topic as if you were explaining it to a 12-year-old child, not to a university student.”
and then:
"Now ask me five questions. Don't give the answers right away. Explain again what I did wrong."
It is possible to turn AI into an interactive teacher.
However, the correct use of artificial intelligence in education should not consist of directly copying the answers. When AI starts thinking instead of the student, it can weaken the learning process rather than facilitate learning.
The best use of AI is not as a tool that does the homework, but as an assistant that accelerates understanding.
Artificial Intelligence in Healthcare
Health is one of the most promising but also one of the most careful areas of use of artificial intelligence.
AI can be used in many processes, from analysis of medical images to clinical decision support systems, from drug development to hospital operations. Its ability to find patterns that may be difficult for people to notice in large data sets has great potential, especially on the research side.
However, generative AI models on the consumer side should not be used instead of doctors. General-purpose AI models can produce inaccurate information and undervalue medical context.
Artificial intelligence can help you learn about health or prepare for a doctor's appointment; It cannot replace diagnostic and treatment decisions.
The same principle applies to high-risk areas such as law and finance.
Artificial Intelligence in Media, News and Publishing
AI can be used in many different areas in the media world, such as transcription, translation, data analysis, archive scanning, subtitling, content recommendations and content production.
Journalists can use AI to find relevant sections within long documents or examine large data sets. Video teams can benefit from automatic captioning and translation systems. Publishers can classify their content archives.
But media is also where some of the biggest risks of artificial intelligence are seen.
A sentence that a person has never said can be made to be said by AI. A fake image can spread like a real photo. Automatically generated false news can reach thousands of people in a short time.
Therefore, as AI accelerates media production, verification and source control become even more important.
What is Artificial Intelligence Hallucination?
One of the most misunderstood features of artificial intelligence systems is hallucination.
AI hallucination means that the model produces false information as if it were true. He/she may make up the title of a book, cite non-existent research, give the wrong date, or describe an event that did not actually occur.
The reason for this is that language models are not systems that bring precise information from a database in the classical sense. They create answers based on probabilities.
For this reason, especially when it comes to current news, academic research, statistics and important decisions, it is necessary to ask for resources from AI and actually open and check the given resources.
Just because AI sounds confident doesn't mean it's right.
What are the Harms and Risks of Artificial Intelligence?
Artificial intelligence has risks as well as opportunities. Some of these risks come from the technology itself, some from how people use it.
One of the most visible problems is deepfake technologies. A person's image or voice can be imitated very closely to reality. This situation creates a wide risk area, from fraud to disinformation.
Another problem is privacy and data security. Uncontrolled uploading of internal company documents, customer data or personal information to artificial intelligence tools may cause serious security problems.
Copyright is also one of the important discussions. The legal system is still evolving regarding what data AI models are trained on and how to evaluate the rights of created content.
Algorithmic bias is another risk. AI systems can learn social or historical biases in training data and reflect these in the results it produces.
Broader social issues such as workforce transformation, the proliferation of fake content, contamination of the information ecosystem, and people's over-delegation of critical thinking skills to AI are also discussed.
Therefore, the use of artificial intelligence is not only about “what can it do?” not with the question "how should we use it responsibly?" It should be considered together with the question.
Will Artificial Intelligence Take Our Jobs?
This is one of the most asked questions about AI.
It's clear that some tasks will be automated. Throughout history, computers, the internet, industrial robots and different automation technologies have also created serious transformations in certain professions. Artificial intelligence can also replace a significant portion of repetitive digital tasks.
However, the automation of some tasks within a profession does not mean that that profession will disappear completely.
For example, AI can create design alternatives, but human judgment is required on which strategy the brand should follow. One can write code, but it is necessary to decide which problem the product will solve. It can produce text, but editorial perspective, real experience and original perspective are still important.
Probably the biggest change that will occur in many professions will not be that "AI will replace humans", but that the way people who use AI work will differ from those who do not use AI.
Can We Trust Artificial Intelligence?
Neither completely trusting nor distrusting artificial intelligence is the right approach.
AI is a powerful helper. It can quickly process large amounts of information, create hundreds of alternatives, and reduce some tasks that would take people hours to seconds.
But he can be wrong.
Therefore, the right approach is to control the output of artificial intelligence according to the risk of the job.
A small mistake in creating an Instagram caption will not have the same consequences as a mistake in a health tip. Therefore, the level of control in the use of AI should increase according to the importance of the task.
AI can be given more freedom in low-risk creative tasks. In high-risk areas such as health, law, finance or public information, expert and source control is definitely required.
Why is the Ethical Use of Artificial Intelligence Important?
Just because a technology can be done does not always mean it should be done.
Cloning a person's voice without permission may be technically possible, but unethical. It may be possible to manipulate a real photo and share it as a news image, but it may cause social harm.
Establishing ethical AI policies is becoming increasingly important for companies. It should be determined what data can be loaded into AI tools, how AI-generated content will be marked, how customer information will be protected, and at what points human control will be mandatory.
We think that in the long term, trust in artificial intelligence will depend not only on how powerful technology companies develop models, but also on how responsibly these systems are used.
How Can You Protect Your Data When Using Artificial Intelligence?
It is necessary to remember that not all information given to artificial intelligence is shareable data.
The company's unpublished financial report, customer lists, health information, contracts, passwords or personal information should not be uploaded to any AI platform.
It is important for corporate users to review the data policies of the AI services they use and, if necessary, choose enterprise plans. In addition, clear policies should be prepared for employees regarding which data can be used in which systems.
Individual users can also apply the same principle:
Don't give AI information you don't really need to give.
Even this simple rule can reduce many privacy risks.
Is Content Produced with Artificial Intelligence Really Original?
The proliferation of Generative AI has created an interesting paradox in the content world.
Creating content is easier than ever. But since everyone uses the same models, it is becoming increasingly difficult to look original.
To AI:
“Prepare a professional blog post about digital marketing.”
When you say
, it is possible to get correct but extremely generic content.
When the brand's own perspective, experiences from real projects, original observations, data and editorial comments are not added, AI contents begin to resemble each other.
For this reason, using artificial intelligence as a researcher, editor and thought partner, rather than as a writer to whom we hand over the entire content production, can produce stronger results.
AI can speed up production
You still need to add the brand character yourself.
Artificial Intelligence and the Future of Search Engines
One of the biggest impacts of AI is in the way we access information on the internet.
We were typing a few keywords in the classic search engine and choosing among the links. In Generative AI-supported searches, we can ask much longer and more natural questions and receive directly synthesized answers.
This change also affects the SEO world.
Brands now need to think not only about ranking for certain words in Google results, but also about producing reliable and clear information that artificial intelligence systems can understand. The expertise of the content, its source quality, its structure and whether it actually answers user questions may gain more importance.
Therefore, in the SEO approach of the future, simply repeating keywords will not be enough.
It will be necessary to answer the questions that people really ask really well.
What Will the Future of Artificial Intelligence Be Like?
One of the most important changes in the future of artificial intelligence will probably be the transition from chatbots to AI agent systems.
Most of today's models answer when you ask something. Future systems may come closer to achieving certain goals on your behalf.
When you want to plan a trip, instead of just giving hotel recommendations, we may see AI assistants researching options, checking your calendar, and moving forward with your approval. Agent systems that collect weekly performance data, create reports, and notify managers of changes that need attention may become common in a marketing team.
At the same time, AI is becoming more multimodal. The boundaries between text, audio, image and video are rapidly diminishing. A model can understand the world the camera sees, speak to you in a natural voice, and produce images or video within the same conversation.
At this point, artificial intelligence may cease to be a separate application that we use and turn into an invisible layer within the operating systems, business tools, search engines and daily digital services we use.
So Should We Be Afraid of Artificial Intelligence?
Artificial intelligence is a very powerful technology and it is not right to romanticize it without questioning it. There are serious issues such as workforce, privacy, copyright, security, disinformation and power concentration.
But it does not seem realistic to completely reject the technology itself.
Just as the Internet has changed the way we do business, communicate and access information, artificial intelligence has the potential to create a transformation of a similar magnitude.
The people and companies that will have an advantage in this transformation may not only be those who use AI the fastest.
Those who understand where AI should be used, where it should not be used, and where human talent is critical can be in a stronger position.
Because the real value of artificial intelligence is not to take people out of the system completely, but to enable people to do more things in a shorter time.
Artificial Intelligence is Not a Trend, It's a New Layer of Technology
Today, "what is artificial intelligence?" The answer to the question is much bigger than it was a few years ago.
AI is no longer just algorithms that analyze data. A new layer of technology that affects the entire environment in which we write, draw, produce, research, learn and work.
But people are still at the center of this transformation.
Artificial intelligence can generate ideas, but it is necessary to decide which idea is valuable. You can create an image, but it is necessary to evaluate whether that image carries the right brand message. You can do research, but it is necessary to verify the information. You can write code, but you have to decide which problem to solve.
For this reason, in our opinion, one of the most valuable skills of the coming period will not only be "knowing how to use AI".
It will be knowing how to work together with artificial intelligence.
The best start for users starting to learn today is not to try to learn all AI tools at the same time. First, think about the work you do. What tasks take up your time? What processes repeat? At what point do you need more ideas, research or production support?
Then choose the right AI for that problem.
Because in the world of artificial intelligence, the main thing is not to know hundreds of tools.
Being able to use the right tool at the right moment.
Nur Oğuz