This article acknowledges a key shift: AI tools are not replacing scientists, but changing how they work. The concern is that if models generate convincing but incorrect summaries, they risk distorting the literature, especially when researchers use these tools without checking the sources. That is a valid risk, but it is a problem of tool misuse, not of the tools themselves.

The same has always been true of citation practices and review articles. Poorly written reviews can mislead just as easily. The difference is speed and scale. But the solution is the same: better training, transparent standards, and accountability in research outputs.

Concerns about LLMs producing hallucinated references are real, but that is a known limitation. It is not hidden. The responsible response is to insist that authors cite sources they have verified. That expectation already exists. AI should not change it.

The alternative would be to pretend that these tools can be banned or ignored. That is unrealistic. AI-assisted research is here, and the answer is not fear but proper oversight. Just as we adapted to calculators, spreadsheets and search engines, we can adapt to LLMs. The misuse of tools is a human failing, not a technological one.