AI Tools for Research: How to Choose the Right One for You

Artificial intelligence is transforming academic research, offering students and scientists powerful tools to streamline everything from literature reviews to statistical analysis. Once seen as a novelty, AI is now becoming an essential part of the researcher’s toolkit.

Take Mohammed Shafi, a PhD candidate in civil engineering at the Indian Institute of Technology Guwahati. In 2022, he dismissed AI platforms like ChatGPT as playful distractions with little academic value. But within a few months, as new tools tailored to researchers emerged, Shafi integrated them into his daily routine. Today, he relies on an interconnected suite of AI applications that help him discover the latest studies, interpret complex topics, troubleshoot experiments, manage citations, and organize his writing.

Shafi describes this shift as nothing short of a “research revolution”. He’s not alone: recent surveys suggest that many researchers now use AI tools regularly, even daily. While early responses from universities were cautious, institutions are becoming more open to AI use—provided it’s done responsibly.

Here’s a breakdown of how students and academics can use AI effectively throughout the research process:

1. Supercharge Your Literature Review

Modern AI platforms now go far beyond simple searches. Tools like Google’s Gemini Deep Research and OpenAI’s Deep Research use advanced methods like active learning to analyze vast amounts of data and generate insightful, well-referenced reports. These tools can produce summaries, charts, and even visuals based on a research query—making them invaluable for tackling new or unfamiliar topics.

For instance, MIT doctoral student Chuck Downing used Deep Research to evaluate emissions-reduction strategies in manufacturing, calling it the most effective tool he’s found for locating relevant studies and understanding complex material.

Other tools, like SciSpace, Claude, NotebookLM, and PDF.ai, allow users to upload academic papers and ask questions about their content. Cornell PhD candidate David Tompkins finds these platforms especially useful for preparing for journal club meetings. “They help me engage more deeply with the material,” he says.

2. Generate and Refine Research Ideas

AI’s ability to synthesize large volumes of information makes it a valuable partner in identifying research gaps and generating hypotheses. Researchers at the Allen Institute for AI are developing tools that combine concepts across academic papers to inspire new lines of inquiry.

Platforms like Research Rabbit let users explore a network of related studies starting from a single paper, uncovering connections across disciplines. Shafi has used Research Rabbit in combination with ChatGPT to spot underexplored areas in his work on microplastics in soil.

Advanced tools like CRESt (Copilot for Real-world Experimental Scientists)—developed at MIT—go even further. They help researchers automate lab tasks, track experiments, control equipment, and notify users of updates, functioning like a digital lab assistant. More accessible platforms like Scite, Elicit, and Gemini can also generate experiment plans based on a user’s hypothesis or literature.

Biomedical engineering PhD student Joseph Fernandez frequently turns to ChatGPT for everything from troubleshooting lab work to preparing for exams. “If I’m stuck on something, I always check if ChatGPT can help,” he says.

3. Simplify Data Analysis and Coding

For research involving programming, AI-powered code assistants are game-changers. Tools like GitHub Copilot, Amazon Q Developer (formerly CodeWhisperer), and Cursor by Anysphere help users clean, organize, and visualize data quickly and with minimal coding knowledge.

Cursor, in particular, has helped Downing become a more efficient coder by handling repetitive tasks and encouraging deeper data exploration. Tompkins also uses Claude to generate complex, interactive visualizations that were once too time-consuming to create manually.

Still, many researchers emphasize the importance of understanding statistical methods thoroughly. “I always write my code for statistical analysis to ensure accuracy,” says Tompkins.

To build on existing work rather than starting from scratch, platforms like CatalyzeX make it easier to find open-source code linked to published research. This helps promote reproducibility and speeds up the research process.

4. Enhance Your Scientific Writing

AI’s writing capabilities have matured significantly, with platforms now tailored specifically to academic writing. Tools like Paperpal, Thesify, and SciSpace offer grammar and structure suggestions, journal templates, and support for research papers, proposals, and dissertations.

Multilingual support is also becoming standard. Quillbot, Coral AI, and OpenAI’s Whisper provide translation services, helping researchers draft high-quality papers in multiple languages. For non-native English speakers like María Mercedes Hincapié-Otero, a PhD student in Finland, AI provides a much-needed second opinion on her writing.

“I use AI tools to check my grammar, improve flow, and boost confidence—especially when I don’t have someone else to review my work,” she says.

Some platforms, like Thesify, even go beyond manuscript editing. They offer grant-writing assistance, conference and journal recommendations, and resources to bridge the mentorship gap often faced by students. “AI can’t replace a great advisor,” says Thesify co-founder Marc-Oliver Gewaltig, “but it can make expert knowledge more accessible to everyone”.

Final Thoughts

AI is not just a research trend—it’s becoming a foundational part of modern science. Whether you’re looking to dig into the literature, design experiments, code your analysis, or polish your paper, there’s likely an AI tool ready to help.

As Fernandez put it: “With AI, the only real limit is your imagination”.