In our first article, “Will AI take our jobs?”, we have made one point clear. AI changes work more than it removes work. IT teams can also move faster with AI, but they take on more validation and quality control. That’s why looking at work at the task level gives a more accurate picture than focusing on job titles.
Will AI take our jobs? This question is not abstract anymore. Teams build work with AI every day. Companies also face pressure on costs and speed. Many people ask the same question: Will AI take our jobs?
In this article, the goal is to replace panic with clarity and help you see the bigger picture. You’ll find concrete, real-world IT examples throughout, along with a simple, data-informed framework to structure the discussion. With that foundation in place, we’ll address the question “Will AI take our jobs?” in a practical, actionable way—focused on what’s changing, what’s not, and how to adapt.
AI changes learning fast. It builds personal paths for each student. It also helps students learn in new languages. Therefore, schools now use more digital tools each day.
However, AI needs a lot of data to work well. So, it collects clicks, answers, voice, and writing. This creates a real “privacy paradox.” Schools want smart learning. Yet they must also protect children and trust.
Data privacy in AI-driven education must guide every EdTech plan. Privacy does not block growth. Instead, privacy builds safe growth. Moreover, privacy protects students for many years.
Learning knows no borders. Many students come from diverse language backgrounds, and often, traditional learning platforms do not respond to this diversity. They typically offer feedback in one language. So this is an obstacle for non-native speakers. However, Multilingual AI feedback systems are changing the game with feedback in multiple languages. They help students understand better. Consequently, they make learning more enjoyable. Integrating these systems into learning platforms is a smart move. It ensures every student receives effective support.
The AI Summit Brainport 2025 took place on November 13 in Eindhoven and brought global AI leaders together. Mysoly joined the summit to explore new ideas, future trends, and strong insights on trusted AI.
This year’s theme, “How to Trust AI?”, shaped all discussions. Talks focused on ethics, safety, context, data quality, human-centered design, and the growing need for transparency.
The AI Summit Brainport once again proved its role as a key event for innovation and strategic AI thinking.
Related to custom CSS and packages in Frontend Development, developers often face an important decision. Should they write their own CSS or use a ready package? This choice affects performance, maintenance, user experience, and overall code quality. Sometimes writing a few custom lines is best. However, using one smart package can finish a long task in minutes.
This article explains the difference between writing custom CSS and using ready libraries. It also shows when each option is more effective with real examples.
The most important factor for success in AI projects is data cleaning. It does not matter how advanced your algorithm is. Because if your data is wrong or incomplete, the results will also be wrong.
As Lovelytics says, the rule “garbage in, garbage out” is still true. Therefore, datasets must be accurate, complete, up-to-date, consistent, and contextual.
In this article, we will share easy-to-understand information from recent blogs about data cleaning and AI, published in the last three months.
AI in Power BI projects is no longer optional. Teams need answers fast. Leaders expect visible value. This article gives a simple path. I keep the language clear and short. I cut complexity and remove guesswork. I also give copy‑ready prompts and ideas. AI in Power BI projects boosts speed, quality, and trust. Let’s turn that promise into daily practice.
With this blog, we’re kicking off an all-new blog series: the “LMS Buyer’s Guide – How to Choose the Right Learning Management System”.
In 2025, digital learning isn’t a nice-to-have—it’s a business necessity. Organizations must quickly upskill their teams to stay competitive. Hybrid work and global talent pools only raise the stakes. That’s why choosing the right LMS is more important than ever.
Online training is becoming more popular every day. It is helping both workers and companies grow.
In 2025, learning from home or anywhere else is normal. Many people do not go to the office anymore. That’s why online training is so important now.
Let’s look at the top benefits of online training for your team and business.
Speed is a critical requirement in modern frontend development processes. Developers aim to minimize time loss during local development and production build stages. However, traditional tools fail to meet this need, especially in scaled projects. For example, seeing “Compiled successfully in 89.6 seconds” in a React project raises concerns about efficiency. Such delays negatively affect not only the developer experience but also team productivity and CI/CD processes. In projects developed with CRA, increasing dependencies and complex configurations deepen this problem.
The pace of progress in AI goes beyond the dominant API-driven services like OpenAI’s ChatGPT, Google’s Gemini, and Anthropic’s Claude. Open-source Large Language Models (LLMs) are emerging rapidly and offer compelling alternatives. In particular, Chinese AI firm DeepSeek is competing fiercely with leading proprietary API-driven solutions.
