AI in Missionary Practice
Training Local Leaders
~5 min read
In June 2026, Daystar University’s School of Mission and Theology in Nairobi gathered thirty full- and part-time faculty members for two days of AI literacy and ministry-focused training. The sessions included theological foundations, prompting, critical discernment, biblical study, research, and practical ministry tools.1
The story matters because it reverses a common picture. African theological institutions are not waiting passively for Western organizations to decide what AI means for them. They are already experimenting, evaluating, teaching, and forming their own institutional responses.
Access Is Not Formation
AI can reduce one longstanding inequality in theological education: access to explanation. A student with a difficult paragraph can request another explanation. A lecturer can generate exercises. A small school can search digitized resources more effectively. Translation can open material from other languages.
This matters where faculty time and library access are constrained. But access to information is not the same as theological formation. A student can receive an excellent answer without learning how to interpret Scripture, evaluate arguments, or serve a church.
A model can explain leadership principles instantly. Leadership itself is formed through responsibility.
Local leaders need opportunities to make decisions, bear consequences, receive correction, navigate conflict, teach real people, and remain faithful over time.
AI can support that process. It cannot compress tested character into a content module.
This is why an AI-enabled theological school should not define success as faster completion alone. If students graduate sooner but with weaker interpretive competence or less pastoral maturity, efficiency has displaced the goal.
AI could lower barriers to theological education for leaders who cannot relocate, study in English, or access large libraries. That is an opportunity worth pursuing aggressively.
The aim should not be to produce globally standardized theological answers at lower cost.
It should be to strengthen the capacity of churches and institutions to form leaders who can interpret Scripture faithfully, think theologically in their own contexts, teach others, and exercise accountable Christian leadership.
Information can become cheaper. Leadership cannot be downloaded. AI may be especially significant for theological institutions teaching students in a second or third language.
A student can receive explanations in a stronger language while still engaging course material in the institution’s language. Faculty can generate glossaries, bridge readings, and language support.
This can widen access without requiring every student to reach elite academic English before serious theological study begins.
The long-term goal should include theological production in the student’s own language, not permanent translation dependence.
Who Is Teaching Through the Corpus?
Theological AI raises a question often hidden by fluent output: whose theology is most available digitally?
English-language publishing, North American seminaries, major Western denominations, and highly digitized traditions may dominate the material from which systems learn or retrieve.
A model can therefore sound like generic Christianity while reproducing a narrower theological center of gravity.
The solution is not to remove Western theology. Christian theology has always crossed borders. The better response is to make sources visible and expand the corpus.
African, Asian, Latin American, Middle Eastern, Indigenous, and diaspora scholarship should not enter only as contextual supplements to a default Western framework.
Institutions can build retrieval systems over their own reviewed libraries, faculty materials, denominational documents, regional scholarship, and local-language resources.
This allows AI to assist without pretending one global model’s latent knowledge represents the institution’s theological identity.
Corpus governance becomes part of academic governance. Who decides what enters? Which traditions are represented? What happens to copyrighted or unpublished materials? Can students see sources? Imported AI curricula can reproduce imported theology. An institution should decide which theological sources, ethical questions, and mission priorities belong in its own training. Global resources can enrich the curriculum without becoming the hidden default.
This is where local retrieval libraries and faculty-authored guidance can be particularly useful.
Faculty Remain a Scarce Form of Judgment
Where qualified theological educators are scarce, AI can handle some work that does not require the educator’s highest judgment.
Routine explanation. Practice questions. Feedback on structure. Language support. Administrative preparation. The goal should be to concentrate faculty time on what is hardest to automate well: formation, mentoring, contextual theology, difficult interpretation, pastoral wisdom, and assessment of real competence.
This is the same infrastructure shift seen elsewhere. Cheap first-pass assistance makes expert judgment more valuable.
AI complicates traditional assignments. An essay can now be generated or heavily assisted with little evidence of learning.
The answer is not necessarily stronger detection. Assessment can move toward oral defense, live interpretation, iterative drafts, ministry projects, source analysis, and tasks that require students to explain reasoning.
Theological education should assess the person who will teach and lead, not merely the polished artifact submitted.
AI literacy for faculty should go beyond tool demonstrations. Educators need to understand how assignments change, how source verification works, what data students may upload, and how to distinguish AI assistance from replacement of the learning objective.2
Faculty should also be allowed to disagree about appropriate boundaries. A theology professor may forbid AI in an interpretive exercise designed to assess independent exegesis while using it extensively to generate low-stakes quizzes. When AI supplies explanations cheaply, the educator’s comparative advantage shifts toward diagnosis. Which misconception is blocking the student? Which theological question actually matters in the student’s church context? Is the student becoming capable of interpreting independently? What kind of leader is the student becoming? These are not merely content-generation problems.
Build Local Institutional Capacity
There is no single “African response” to AI, just as there is no single Western response. Infrastructure, theology, regulation, language, faculty attitudes, and student access differ enormously.
St. Paul’s University and other African institutions have convened conversations about AI, pedagogy, access, spiritual formation, and the underrepresentation of African theological traditions. These are signs of agency, not evidence of one consensus.
The same pattern should be encouraged globally. Mission organizations should support institutions in developing their own policies and capacities rather than exporting a universal AI curriculum.
Theological education increasingly intersects with technology infrastructure. Schools may need staff capable of managing retrieval systems, privacy, accounts, digital libraries, and evaluation.
External partners can help build these systems. Transfer matters. If the system becomes essential but nobody local can maintain or govern it, the institution has gained capability and dependency at the same time.
AI education assumes devices, connectivity, accounts, and sometimes paid subscriptions. Institutions should avoid building pedagogy around tools students cannot reliably access outside the classroom.
A lower-capability system available consistently may serve formation better than a cutting-edge platform accessible only to a privileged subset.
PART IV