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AI-powered decision making
Last year, 32% of IT professionals surveyed said AI was only good at relatively simple tasks. Developers are trying to solve this problem with agent-based AI.
Agent AI is smart programs that can operate with little panama telegram data or no human intervention. They don’t just answer questions like chatbots, but take on complex tasks. An agent can create a schedule, send the right emails, or analyze data to help make decisions. But for us to trust these systems, it’s important that they work reliably and don’t make mistakes. This is where the AI TRiSM (AI Trust, Risk, and Security Management) approach comes in. It helps track how and why AI makes certain decisions, and also identifies errors and biases in databases.
Deloitte predicts that by the end of 2025, 25% of companies using generative AI will be deploying AI agents, and this figure will grow to 50% by 2027.
Although generative neural networks create some tension in the labor market, they still cannot completely replace humans.
The problem of control will remain for a long time. We need to develop trust in artificial intelligence and improve the statistics of its error-free work. Modern models solve very specific problems: they need clear prompts with a lot of clarifications. Now AI works at a level lower than even an intern: it needs human control. But if an individual specialist wants to increase the efficiency and speed of his work, to grow his career, he definitely needs to know how to use AI.