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AI News in 2026: From More Powerful Models to Autonomous Agents and Stricter Rules
Artificial intelligence entered 2026 in a more mature and tense phase. While recent years focused on generative models, chatbots, and spectacular experiments, in 2026 attention shifts to practical use, autonomy, governance, and control. AI is no longer just an experiment—it is becoming a central part of business processes.
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AI and Critical Thinking: When the Digital Assistant Starts Thinking for Us
AI is useful precisely because it reduces cognitive effort. It summarizes, compares, classifies, formulates, and checks hypotheses, transforming in seconds tasks that once required time, attention, and patience. For companies, the promise is powerful: faster decisions, smoother processes, and increased productivity.
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The AI Productivity Paradox: Why Saving Time Doesn’t Automatically Create Value
Artificial intelligence has quickly become one of the most powerful promises of efficiency for companies. It can draft texts, synthesize documents, generate analyses, automate repetitive tasks, support decisions, and accelerate activities that previously took hours. On the surface, the equation seems simple.
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Tail Control: How to Ensure the Reliability of Agentic AI Workflows in Business
Tail control is the key to reliable AI automation: it’s not just speed or average accuracy that matters, but also controlling extremes and variation. Companies can increase the predictability and safety of AI workflows by applying strategies such as adaptive timeouts, redundancy, and active monitoring.
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Who Will AI Replace?
In recent years, we have heard the same question hundreds of times: “Will AI take our jobs?” Alarmist headlines, spectacular demonstrations of new models, and the speed of technological progress suggest we are facing an unprecedented revolution. But what if we’re asking the wrong question?
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AI Is Changing the Start of a Career: Why Entry-Level Jobs Already Require Senior Skills
Artificial intelligence is not only changing how experienced employees work. It is also profoundly transforming how young people enter the job market. The repetitive and simple analytical tasks that generations of juniors used to learn the trade are now among the first to be automated.
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How AI Is Changing Officiating in Sports: The Automated Out-of-Bounds Decision System in the NBA
The NBA is implementing an AI-powered video analysis system for out-of-bounds decisions, promising fairer and faster officiating. Automation reduces human error but raises new challenges around transparency, acceptance, and technological dependence. The future of sports officiating will depend on balancing innovation and ethics.
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Artificial Intelligence in Business: From Theory to Tangible Results
Artificial intelligence is quickly becoming an indispensable tool for companies looking to automate processes, analyze data, and make better decisions. This article explains the benefits, challenges, and steps for implementing AI in business, offering concrete examples and resources for further exploration. It is a practical guide for professionals seeking to move from theory to real…
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Why Automation Fails: 7 Real Causes
Automation seems like an “easy” idea: take a repetitive process, make it faster, cheaper, safer. Yet in many companies, automations die in a predictable place: between the demo and reality. They look perfect in presentations, but in production they break at the first different format.
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