Preaching with AI: an exploration of preachers' interaction with large language models in sermon preparation

This study explores how Swedish preachers incorporate AI chats such as ChatGPT into sermon preparation. Based on interviews, chat logs, and sermon manuscripts from six priests in the Church of Sweden, the study uses relevance theory to analyse the preachers' prompting and evaluation strategies. The preachers primarily use large language models (LLMs) for brainstorming and inspiration, critically evaluating the AI-generated responses, guided by their convictions, theological training and pastoral experience. Their prompting strategies reveal that many of them have a rudimentary understanding of how LLMs work. This leads them to underutilise its synthesising capacities and underspecify their homiletic context in their prompts. We argue that the preachers both underestimate and overestimate the LLM's communicative capacities, due to its humanlike style of communication.

Authors

Institutions

Publication Details

Journal
Practical Theology
Published
2025-03-04
DOI
https://doi.org/10.1080/1756073x.2025.2468059
Citations
2
Primary Topic
Media, Religion, Digital Communication
Type
article
Field-Weighted Citation Impact
34.53
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Preaching with AI: an exploration of preachers' interaction with large language models in sermon preparation

Frida Mannerfelt, Rikard Roitto
2 citations
Practical Theology
Media, Religion, Digital Communication
34.53
article

Preaching with AI: an exploration of preachers' interaction with large language models in sermon preparation

Frida Mannerfelt, Rikard Roitto
article en
2 citations

Abstract

This study explores how Swedish preachers incorporate AI chats such as ChatGPT into sermon preparation. Based on interviews, chat logs, and sermon manuscripts from six priests in the Church of Sweden, the study uses relevance theory to analyse the preachers' prompting and evaluation strategies. The preachers primarily use large language models (LLMs) for brainstorming and inspiration, critically evaluating the AI-generated responses, guided by their convictions, theological training and pastoral experience. Their prompting strategies reveal that many of them have a rudimentary understanding of how LLMs work. This leads them to underutilise its synthesising capacities and underspecify their homiletic context in their prompts. We argue that the preachers both underestimate and overestimate the LLM's communicative capacities, due to its humanlike style of communication.

Practical TheologyVol. 18(2)
Lund University (SE)
Quality Education
Openalex Percentile: Top 1%
Media, Religion, Digital Communication
34.53
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.