Silchar: Around 100 Accredited Social Health Activists (ASHAs) in Assam have helped shape an artificial intelligence-enabled training platform and multilingual voice chatbot aimed at strengthening cervical cancer screening and community counselling in rural areas.
The co-design workshop was organised by The George Institute for Global Health India in collaboration with Cachar Cancer Hospital and Research Centre (CCHRC), Assam.
The workshop brought together ASHAs, doctors, trainers, programme coordinators, researchers and technologists to identify the challenges frontline health workers face while supporting women with cervical cancer screening and counselling.
The exercise focused on understanding what kind of information and digital support ASHAs need during community visits and how technology could complement their existing training.
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The workshop is part of a three-year pilot study, Leveraging Artificial Intelligence for Strengthening Cervical Cancer Screening Through Capacity Building, funded by the Indian Council of Medical Research (ICMR). The project runs from November 2025 to November 2028.
As part of the project, researchers are developing an AI-based learning platform for ASHAs and a voice-based chatbot capable of responding to questions in multiple languages.
During the workshop, ASHAs reviewed 155 common questions related to cervical cancer and screening. Using a bindi-based voting exercise, they identified the questions they encounter most frequently from women, husbands, family members and others in their communities.
The exercise indicated that questions frequently raised in the field do not always correspond with those considered clinically important. The findings will be used to develop the chatbot’s knowledge base, incorporating both priority health information and practical concerns encountered by ASHAs.
The workshop also examined ASHAs’ familiarity with digital technology. Younger and middle-aged participants reported regularly using mobile phones for reporting, communication and accessing information, while some older participants said they found digital tools and technical language more challenging.
However, participants expressed willingness to improve their digital skills.
ASHAs also mapped their work and training needs, including counselling women, explaining test results, maintaining knowledge, and making appropriate referrals. The exercise helped participants identify areas where additional information or refresher training could be useful.
Participants suggested features including Bangla voice-based interactions, simple-language content, search functions that reflect how ASHAs naturally frame questions, short audio-visual lessons, frequently asked questions, reminders, quizzes and progress tracking.
One ASHA worker who attended the workshop said the interactive exercises made the session different from routine meetings and helped participants understand which information about cervical cancer was important.
Dr Anita Gadgil, Principal Investigator of the project and Senior Research Fellow at The George Institute for Global Health, and Co-Director of the WHO Collaboration Center for Emergency Critical and Operative Care, said the platform would be developed around the experiences of ASHAs.
“Their experience of explaining screening, responding to concerns and finding answers in real time will guide the language, content and functions of this AI platform,” Gadgil said.
She added that the aim was to develop clinically validated support that fits into ASHAs’ existing work rather than create an additional digital burden.
Cervical cancer remains a major public health concern in India, with gaps in awareness and screening affecting early detection. ASHAs often play a role in reaching women in their communities, explaining screening procedures and connecting them with healthcare services.
The inputs from the workshop will inform the development of the AI learning platform and chatbot. The training content and questions will undergo clinical review and testing with ASHAs before the tools are rolled out.
The study will subsequently compare AI-supported training and chatbot access with standard training methods through a two-arm cluster-randomised controlled trial involving 20 clusters and around 110 ASHAs.
Researchers will assess the practicality and acceptability of the tools, their usage and consistency, and their potential for scale-up. The study will also examine changes in ASHAs’ knowledge, attitudes and practices to inform a potential larger trial.
The proposed chatbot is intended to support ASHAs with training and field-based information and will not replace clinical assessment, diagnosis or existing referral pathways.
