Religious leaders are experimenting with AI, spurring an industry of faith-based tech companies that offer AI tools to do theological research and write sermons
Eli Tan / New York Times : Bluesky: @numerius , @phillyfilly , @shelleybwoke , @michaelklein.io , @ruthgraham , and @notjessewalker Bluesky: Iulus Mayfair / @numerius : Megachurches were just an early experiment at scaling religion. [embedded post] @phillyfilly : So no Divine inspiration or meditating on Holy text(s)? @shelleybwoke : Maybe John of “The Revelation” fame was an OG AI [embedded post] Michael Klein / @michaelklein.io : Finally an industry where a machine that produces generic, unreliable slop that's tailored towards what people want to hear rather than accuracy is the perfect tool for! Ruth Graham / @ruthgraham : “Our job is not just to put pretty sentences together.” www.nytimes.com/2025/01/03/t... Jesse Walker / @notjessewalker : I love this sentence on about five different levels: “While harmless in certain situations, faith-based A.I. tools that fabricate religious scripture present a serious problem.”
Context & Ripple Effects
This extends the spread of AI text generation into a profession where the output is both written and institutionally accountable. Earlier coverage documented AI-generated text expanding across internet publishing, while this case shows vendors packaging similar capabilities around a specialized knowledge domain.
The story matters because theological research and sermon preparation are recurring workflows, giving faith-focused providers a clearer product category than a general-purpose chatbot alone.
First-order effects
- Religious leaders can use AI tools immediately for research and drafting, changing how sermon-preparation work is organized.
- Faith-based technology companies gain a defined customer segment for products tailored to religious workflows.
Second-order effects
- General AI providers and religious-tech vendors will have to compete on workflow fit, including the usefulness of theological research and drafting features rather than raw text generation alone.
- As more institutions use these tools, editorial review and source-checking become a more explicit part of religious-content workflows, because generated material still requires human accountability.
Third-order effects
- If adoption persists, AI’s commercialization will move further from horizontal chat tools toward sector-specific products built around recurring professional practices.
- The durable dividing line may be less whether AI can produce religious text than which institutions establish trusted human review over machine-assisted teaching.
The trend: This is part of the shift from general-purpose generative AI toward workflow-native software for specialized, trust-sensitive professions.