Artificial intelligence has been on the agenda of both individuals and brands more than ever in recent years. This technology stands at the center of digital transformation. From business processes to marketing, from customer experience to content production, it both accelerates and creates a new vision. However, with its widespread use, many questions are also accumulating in people’s minds. Questions such as “How reliable is artificial intelligence?”, “What does it mean for agencies?”, “Will it take away my job?”, “How should brands use this technology?”, “What risks are there?”, “What opportunities await us?” knock on the doors of every sector.
Below, we have addressed the questions that both users, brands and digital agencies are most curious about; in a whole flow. We are here with our article, which is a guide that will make it easier for you to understand artificial intelligence in both technical and practical dimensions.
What is Artificial Intelligence?
Let’s start with the first and simplest question. What is artificial intelligence? In the most basic terms, artificial intelligence is a set of technologies that aim to provide computers with the thinking, problem-solving, decision-making and learning skills of humans. In this respect, it is not a single tool, but an ecosystem.
Artificial intelligence is a critical tool for today’s businesses because it provides speed, accuracy and cost advantages. It offers massive process optimization, especially in data-intensive industries such as energy, finance and manufacturing.
How Does Artificial Intelligence Work?
Let’s come to the indispensable question “How does artificial intelligence work?”. Artificial intelligence systems work in 4 basic stages.
- Data Collection: Preparation of the data needed to train the model.
- Pattern Training: AI learning patterns from data.
- Testing and Validation: Examining the performance of the generated model.
- Feedback: Model continues to evolve with new data
Machine learning, deep learning, natural language processing, image processing, predictive analytics, generative models and much more are all part of this ecosystem. Artificial intelligence does not memorize anything; it learns from examples. The more data it sees, the sharper, faster and more accurate it becomes. Therefore, in recent years, both the data collected by companies has increased and the performance of artificial intelligence has increased exponentially.
Today, an AI can answer customer conversations, generate design recommendations, write ad copy, analyze trends in large data sets. It can also forecast risk, automate an operation from start to finish, personalize the user experience, and even plan complex business processes on its own. What this means is this. AI is not there to replace humans; it is there to make humans work faster, more accurately and more creatively. When used wisely, it can increase an agency’s productivity 3-4 times, reduce a brand’s cost, reduce the margin for error and strengthen decision-making processes.
Most Common Artificial Intelligence Programs
Under this heading, we wanted to write the most common artificial intelligence programs as a category rather than writing them one by one, because any information we write may be outdated or useless after a week. For this reason, if we write according to the functioning and purposes of the programs;
- Text Generation Tools (Text to text): These are programs that generate text with given promtpts. It includes programs such as ChatGPT, which taught us the concept of artificial intelligence and brought it into our lives. Claude and Gemini are also prominent tools in this field.
- Image Generation Tools (Text to image): These models are systems that generate images with the right prompts. Many programs such as Midjourney, Leonardo, Gemini, Adobe firefly, etc. offer services in this regard.
- Video Production Tools (Text to video and Image to video): These systems, which have created the greatest fascination of recent times, produce realistic videos with a photo or text. Especially Sora, VEO 3, Banana, Runway programs attract a lot of attention.
- Audio Production Tools: These systems are tools that read the desired text from sample audio files. Eleven Labs and epidemic Sound are the leaders in this field.
- Machine Learning Libraries: These libraries enable developers to quickly develop AI models using ready-made function sets instead of writing complex algorithms from scratch. Popular examples include deep learning frameworks such as TensorFlow and PyTorch, and general-purpose tools such as Scikit-learn, which streamline the process of model training, validation and deployment. TensorFlow, PyTorch, Scikit-Learn are some examples.
- Data Analytics Tools: Examples include RapidMiner and KNIME. These tools are used to automatically discover and visualize trends, patterns and meaningful insights from large data sets. In addition, platforms such as Tableau, Power BI or Jupyter Notebooks help transform data into insightful reports and interactive dashboards to support business decisions.
Most Frequently Asked Questions About Artificial Intelligence
The most frequently asked questions about artificial intelligence are usually about integration, cost, performance and security. In particular, how AI will be incorporated into existing business processes, which systems it is compatible with and the accuracy rate of the outputs to be obtained are among the frequently asked questions. Other intensive questions about AI include topics such as data privacy, copyright processes, effects on employees and automation rate.
Learning to use artificial intelligence is actually a process of practice and trial and error. However, there are now many YouTube and similar programs that offer tutorials or new feature videos for artificial intelligence models. Before you get started, it’s helpful to check out these videos and look at the prompts on the programs’ own websites.
There are already many artificial intelligence programs, both paid and free. What is important here is what these programs meet the needs. Many artificial intelligence platforms offer limited free models. In general, basic level and open source tools are free or have limited use. Apart from this, different prices are offered to the user with individual and corporate packages. Prices vary according to the tool to be used, capacity, API usage and project scope. At the same time, the pricing of text generators and tools that produce graphics or video are different.
This is really one of the most important questions for today. Because artificial intelligence can optimize your business processes in many ways. First, you can automate routine tasks. This skill saves you time. Then you can use chatbots in customer service. You can analyze the target audience in your marketing campaigns. Sales forecasting and inventory management are also possible.
According to the needs of the sector, the area of use of AI differs. You can use AI in your business, especially in the following areas.
- Process automation: Automating repetitive tasks.
- Reporting Fast reporting of data analysis.
- Customer service: Chatbot and automated response systems.
- Marketing: Audience analysis, advertising optimization.
- Forecasting: Demand, production and energy consumption analysis.
A common concern in the business world is whether AI will eliminate professions. Artificial intelligence will increase automation in certain professions, and this will cause some of them to change shape. However, this is not expected to completely eliminate humans. AI will not eliminate jobs completely. But it will certainly change the way of doing business. Routine and repetitive tasks are at risk with automation. Data entry, simple accounting and call center tasks are examples.
To succeed in the future, it is necessary to learn to collaborate with AI. Creativity, critical thinking and emotional intelligence will be especially important in the future. Therefore, the ability to use AI tools will be a new competency. Therefore, the correct answer to the question is “Artificial intelligence will affect every profession in certain ways. However, professions that reject this development are especially at risk”. However, data entry, call center operations, standard reporting tasks and simple production and control areas seem to be affected by this development.
These three concepts are interrelated. That is why they are often confused, but they are not the same thing. Artificial intelligence is the broadest term to cover them all. It encompasses all systems that mimic human-like decision-making. Any system that mimics human intelligence is included in this concept. Machine learning is a sub-branch of artificial intelligence. It is the process of systems learning with data. Systems that include algorithms that learn from data. Deep learning is both a sub-branch and a more advanced level of machine learning. It uses multi-layered artificial neural networks that resemble the human brain. It can be used for the most comprehensive and complex tasks. Deep learning is especially preferred in image processing, voice recognition and systems that work with large data sets.
Today, we can say that this question has almost lost its meaning. Because artificial intelligence is used at every point from design to medicine, from production to logistics systems. Artificial intelligence is used at every point where there is big and dense data and complex decisions are required. However, to list in general, the main areas where artificial intelligence is used intensively today are as follows:
- Health: Image analysis, early detection, treatment planning.
- Finance: Risk analysis, fraud detection, algorithmic trading.
- E-Commerce: Recommendation engines, user behavior analysis.
- Energy: Consumption forecasting, efficiency analysis, performance optimization.
- Production: Robotic automation, quality control.
- Logistics: Route planning, demand forecasting, cargo classification.
In fact, artificial intelligence works behind many of the technologies we use every day. Although we don’t realize it most of the time, we are now constantly using AI at every point. First of all, camera enhancements on our smartphones use artificial intelligence. These systems automatically enhance, edit or retouch photos. Search engine suggestions, translation tools, social media streaming algorithms all use this system.
Music and movie recommendation systems also make frequent use of artificial intelligence. Your past preferences are analyzed. They recommend new content to you. These systems even design cover images that you will like. Smart NPCs (non-player characters) in games are also AI. Their realistic behavior is ensured by AI. Traffic forecasts in map applications are made thanks to AI. It processes the instant data flow and offers you the fastest way. Artificial intelligence is present in our lives at these and many other points.
Learning artificial intelligence is a very comprehensive process. Because this process can eventually lead to new coding and development. If the goal is just to produce something with artificial intelligence, the steps are clear. Programs need to be completely riddled with holes. With the right coding languages and prompts, you need to dominate every program that will work for you.
However, if you want to be able to write and edit these programs, the first step in this process will be to learn the basic concepts. Points such as which model, algorithm, language is used should be analyzed. The next process should be to learn a common artificial intelligence language. Pyhton is quite common in this field. Also Google Colab is an ideal environment for writing code. You can work with libraries such as TensorFlow and PyTorch. Follow datasets and communities.
The clearest answer to this question is to gain competitive advantage and keep up with the changing system. Advantages such as analyzing customer data in depth, getting fast returns, and reducing costs, especially in production work, are the factors that push agencies to use artificial intelligence.
Artificial intelligence has many direct impacts on digital marketing. These can be generally listed as follows;
- Much faster data analysis
- Accurate targeting
- Automated content generation
- Ad optimization
- Acceleration of A/B tests
- Clearer analysis of customer behavior.
Artificial intelligence has the power to make SEO efforts much more powerful. Keyword research can be done more efficiently with AI. In addition, low competition but high potential words can be found. Artificial intelligence can analyze the readability of your existing content. These systems do not only mean content production. It can also help you make strategic SEO decisions. However, it should not be forgotten that no system gives full performance. It is important to remember that every feature you will use can be used by others and this competition will reduce its value at the end of the process. Therefore, it is inevitable to get professional SEO support.
AI-supported content production (text, images, video) is generally original. However, it should not be forgotten that these systems use existing and previously licensed data while producing. Therefore, the outputs may be imitated, copyrighted and inappropriate. The way to prevent this is to add your own touches to such productions. Also, using programs with commercial production licenses is another important point in this regard.
CRM systems stand out in the use of artificial intelligence primarily with the 24/7 customer support provided by chatbots and virtual assistants. However, AI can analyze customer data. It can predict the risk of customer loss. It can make customer segmentation more precise.
In addition, AI can show sales teams the hottest prospects. In addition, sales opportunities can be more visible and personalized marketing offers can be created. Accordingly, customer satisfaction and loyalty can increase. It can allow personalizing every interaction. It can speed up support processes.
At first, the use of artificial intelligence makes agencies feel like they are cutting costs, but this is actually a false perspective. Yes, there is a cost reduction, but it is a cost reduction that benefits the client, not the agency. Although not for every single work, artificial intelligence enables large production works to be done much cheaper. Because although the way the work is created changes, elements such as the license and training costs of the tools directly affect the agency. Project prices are therefore usually offset by increased productivity. In other words, pricing varies according to the type of project, and labor and operational costs create different dynamics.
As in every business, the success and quality of the work produced with artificial intelligence varies according to the scope of the work. A simple automation project can take a few weeks. Small projects require a few days, medium-sized projects require a few weeks, and large projects require more extensive planning.
Success here is measured differently depending on the purpose of the project. For example, customer satisfaction score is important for a chatbot. Success metrics should be defined at the very beginning of the project. Success in artificial intelligence is the ability to achieve your business goals.
As in every business, data privacy is of critical importance in artificial intelligence studies. Of course, first of all, data, data and studies should be stored in encrypted form. Apart from this, authorization management, server security, model security tests, regular penetration tests, closing unnecessary access are measures to secure both user data and project outputs.
