AI REVOLUTION

What Global Researchers are Thinking

A recent survey of RePORT International staff and investigators reveals how artificial intelligence (AI) is transforming tuberculosis research—and what researchers are worried about

Tuberculosis remains one of the world’s deadliest infectious diseases, claiming over a million lives annually. But could artificial intelligence be the game-changer researchers have been waiting for? A new survey from the RePORT International Coordinating Center offers insights into how AI is already reshaping the fight against TB.

The Current State of AI Adoption

A total of 65 individuals responded, representing roles such as investigators (41%), research coordinators/managers (23%), and others, including faculty and postdoctoral scholars. Over a third had 15 or more years of experience. The top areas of scientific interest included epidemiology (53%), diagnostics (46%), and treatment (44%). What they reported might surprise you: AI isn’t just coming to TB research, it’s already here.

The numbers tell a compelling story. More than 80% of researchers are using ChatGPT for text generation, while nearly half rely on Grammarly to polish their writing. But it’s not just about writing — over one-third of researchers are utilizing machine learning (ML) models, with logistic regression and random forest algorithms leading the charge. On the contrary, many people do not use image generation tools, and transcription tools (e.g. Zoom, Otter.ai) use is moderate.

Regarding impact, 38% of respondents indicated a moderate impact of AI/ML on their work, 19% significant, 10% transformative, and 12% no impact. There is a clear divide between early adopters and those still on the sidelines. While some researchers report transformative impacts on their work, others haven’t yet felt any change at all.

The Promise: Why Researchers Are Excited

The benefits are real and immediate. Non-native English speakers, particularly, praise AI’s ability to clarify their writing and help them communicate complex research findings. Researchers are saving precious hours on coding and data analysis—time they can redirect toward actual discovery.

Grant writing and report structuring are areas of the highest interest and use. AI tools help researchers organize their thoughts, create compelling narratives, and meet tight deadlines that could make the difference between funded and unfunded research.

The potential extends beyond individual productivity. Researchers envision AI-powered mobile tools that could revolutionize care for people undergoing treatment, helping monitor treatment adherence and supporting clinical decision-making in resource-limited settings where TB burden is high.

 The Concerns

This AI revolution isn’t without its shadows. Data privacy tops the worry list and for good reason. TB research often involves sensitive patient information, and researchers are right to question whether AI platforms adequately protect this data. Additionally, AI tools sometimes generate convincing but false information. In a field where accuracy can mean the difference between life and death, this concern resonates deeply.

Many researchers lack proper training in AI tools, creating a potential divide between the AI-enabled and those left behind. There’s also growing concern about environmental impact—training large AI models requires enormous computational resources.

The Path Forward: Building Responsible AI Integration

The survey reveals a research community that’s cautiously optimistic but hungry for guidance. Researchers are calling for:

What This Means for the Future of TB Research

The survey paints a picture of a field in transition. We are witnessing the early stages of what could be a vital transformation in how TB research is conducted. The researchers who are embracing these tools thoughtfully—while maintaining scientific rigor—may have significant advantages in advancing our understanding of this ancient disease.

But success is not guaranteed. The TB research community must navigate questions of equity, ethics, and effectiveness. The goal isn’t just to adopt AI tools, but to use them in ways that accelerate progress toward TB elimination while maintaining the highest standards of scientific integrity.

AI is already changing TB research, whether we’re ready or not. The question isn’t whether this transformation will happen, it’s whether we’ll guide it wisely.

Article by Sanjana Gandikota, Student, Rutgers School of Public Health & Daphne Martin, Program Manager, RePORT International Coordinating Center