Research management

Large language models may not simply replicate human analyses of qualitative data; they can offer additional insights and both challenge researchers' assumptions and prompt further reflection on their interpretations

Academic writing is often framed as something faculty should simply manage better; when they struggle, the blame is put on the individual academic. But this explanation doesn’t hold, as Rachel Gabriele explains

Rather than asking what writing can be outsourced to AI, we might first ask which parts of the process need to remain slow, imperfect and human, argue four academics

How do academics and research managers really feel about impact management? Here’s how it can be done badly, and how to do it right

Artificial intelligence can accelerate discovery in ways humans alone cannot. For Hongliang Xin, the key is pairing AI’s power with ethical safeguards, institutional governance and responsible oversight

Does a research-based explanation hold when applied to new situations? Here’s how to predict the future as well as clarifying the present

From drug design to climate modelling, artificial intelligence can process data at scales far beyond human capacity. Hongliang Xin argues that the future of research lies in harnessing agentic AI through human-guided discovery

The way GenAI surfaces sources for literature reviews risks exacerbating the citation Matthew effect, writes David Joyner. Here, he offers ways to prevent AI-driven search from blunting the impact of new research

AI-augmented research can speed up processes such as literature review and data synthesis. Here, Ali Shiri looks at functionality of three AI agents

Academics might find it hard to see the flaws in their work, but to be a writer is to be edited – embrace it. Laura Portwood-Stacer outlines the importance of developmental editing