By 2025, more than 400 robust generative AI tools will be available on the market, and nearly 30 of them are already being used specifically for academic and scientific research. Faced with this abundance, researchers, faculty, and students are confronted with a critical question: which tools should they prioritize to increase efficiency without compromising the reliability of their results?