The School maintains a set of practical AI tools used inside teaching, together with instruction in how to use them responsibly. The tools exist to support learning rather than to replace it, and every one of them operates under the same rule: output is a draft to be verified, never a finding to be trusted.
Six tools are provided. What follows describes what each does, what it is useful for, and where it fails, because a tool described without its limits is described dishonestly.
Prompt Library
A curated collection of structured prompts for recurring academic and professional tasks, organized by purpose rather than by tool.
The library exists because most people write prompts from scratch every time and get inconsistent results. A structured prompt that specifies the task, the context, the constraints, and the required output format produces markedly more usable output than a conversational request. Having tested versions available removes the guesswork.
Its limit is important. A good prompt improves relevance, structure, and consistency. It does not make the underlying system factually reliable, and no prompt in this library prevents fabrication. Prompts are taught alongside verification, never instead of it. The underlying technique is covered in Prompt Engineering Fundamentals in the course catalog.
AI Workflow
A framework for designing multi-step processes in which AI handles specific stages and humans handle others.
Workflow design is where most practical value is realized, and where most adoption attempts fail. The framework starts by requiring the existing process to be documented, then asks which individual steps genuinely benefit from AI support, then requires a verification step to be built into the workflow rather than appended to the end.
The recurring finding taught here is that documenting the process delivers a large share of the available benefit before any tool is introduced, and that automating an undocumented process reliably produces faster inefficiency. Institutional implementation is handled separately by KBA13 Consulting and the AI Laboratory.
AI Tutor
A structured explanation aid for learners working through course material.
The tutor is useful for rephrasing a difficult explanation, generating additional worked examples, testing comprehension through questions, and identifying which part of a concept a learner has not grasped. Used this way it addresses a real constraint, since a written course cannot rephrase itself for the particular reader who is stuck.
It is not a substitute for the course material, and it is not authoritative. Where the tutor and the course material disagree, the course material governs. The tutor does not assess work, does not determine outcomes, and does not contribute to certification, all of which require human academic review.
AI Research Assistant
A support tool for literature search, evidence organization, and synthesis of long material.
It is genuinely useful for orientation in an unfamiliar literature, for organizing collected sources, and for summarizing long documents into working notes. Used at that stage it saves substantial time.
Its failure mode is the most consequential of any tool here: it generates references that are correctly formatted, plausibly titled, attributed to real authors in relevant fields, and entirely nonexistent. Format-based checking cannot detect this, because the format is correct. Every suggested source must be located and confirmed at its primary location before use, and every summary must be checked against the document it claims to summarize. This requirement is absolute, and it is taught as method in AI for Research and AI for Literature Review.
AI Writing Assistant
Drafting, restructuring, and editing support for academic and professional text.
It is effective at restructuring material the writer has already thought through, tightening prose, adjusting register, and identifying unclear passages. Writers frequently find its most useful function is diagnostic: text the tool cannot summarize correctly is usually text that is not yet clear.
Two limits apply. It does not supply substance, and text generated without underlying thought reads fluent and says nothing. And where AI has contributed materially to a written output, the contribution is disclosed. The boundary between assistance and authorship is covered in AI for Academic Writing.
AI Translator
Translation support for academic and professional material across the languages the Academy works in.
Useful for comprehension of foreign-language sources, for first-pass translation of routine text, and for cross-checking terminology. For an institution working across Indonesian, English, and regional-language material, this removes a real barrier to source access.
Its limit is precision in consequential text. Legal, contractual, policy, and quotation material requires human translation or human verification, because machine translation produces plausible readings of ambiguous passages without flagging that a choice was made. Where a translated passage will be quoted or relied upon, it is confirmed by a competent human reader.
Conditions of use
Four rules apply to every tool without exception.
Output is a draft, not a finding. Nothing produced by these tools enters assessed work, published analysis, or a client deliverable without human verification against primary sources.
Material contribution is disclosed. Where a tool substantially shaped an output, that is stated.
No tool determines an assessment, a certificate, or a published judgment. Human academic review is a permanent structural requirement, not a transitional safeguard.
Sensitive and confidential material is not entered into these tools. Where data handling matters, the governance requirements taught in AI Governance and the analytical rules of the School of Intelligence & Strategic Studies apply.
Learning to use them properly
Tool access without instruction produces confident misuse, which is why these tools are taught rather than merely provided. The relevant subjects sit in the course catalog, structured routes are set out under academic programs, credentials under professional programs, and leadership framing under executive programs. The School’s overall position on AI is stated on the about page, and practical questions are answered on the FAQ page.