Top 10 AI Prompts and Use Cases and in the Government Industry in Brunei Darussalam

Brunei's public sector is at an inflection point: national plans like the Digital Economy Masterplan 2025 and pilots across ministries are turning AI from buzzword into practical tools that can diversify the economy, speed up citizen services, and sharpen policy decisions; a BytePlus analysis shows how AI can boost economic diversification and service delivery in Brunei (BytePlus analysis: Impact of AI on Brunei).

The country faces a clear skills gap and needs wider AI literacy, so workforce training is vital - programs that teach prompt-writing and business-facing AI skills are a direct path to safer, faster adoption (see the Nucamp AI Essentials for Work bootcamp syllabus).

Think of AI as a 24/7 digital assistant that can cut red tape, improve healthcare triage, and free officials to focus on strategy rather than paperwork - if governance, people, and infrastructure move in step.

Bootcamp	AI Essentials for Work
Length	15 Weeks
Courses	AI at Work: Foundations; Writing AI Prompts; Job Based Practical AI Skills
Cost (early bird)	$3,582
Syllabus / Register	AI Essentials for Work syllabus (Nucamp) • AI Essentials for Work registration (Nucamp)

AI adoption should be “grounded in common principles, mutual trust, and shared ambition”

Selection of the Top 10 prompts and use cases followed a simple, practical rubric rooted in Brunei's own governance signals: priority was given to ideas that align with the Brunei Voluntary AI Guide's seven principles - transparency & explainability, security & safety, fairness & equity, and data protection & governance - so each entry could be justified to citizens and auditors (Brunei's Voluntary AI Guidelines); they also had to fit the region's principles‑based, technology‑neutral approach described in analyses of ASEAN readiness and domestic playbooks, ensuring policy compatibility as the national AI strategy and Personal Data Protection Law mature (Charting ASEAN's Path to AI Governance).

Practically, use cases were screened for pilotability (can ministries test them with existing staff and data), measurable public‑service impact (citizen services, triage, procurement), and vendor diligence - examples include live pilots such as the StrategusAI partnership testing scalable automation across ministries - so every shortlisted prompt needed to show how it would convert routine paperwork into a single, auditable workflow that frees officials to focus on strategy rather than form‑filling.

A Brunei government virtual assistant could turn routine citizen interactions into fast, auditable services - think of a midnight clerk that never sleeps - by combining the practical lessons from Darussalam Assets' SAP SuccessFactors rollout with proven intelligent virtual agent (IVA) patterns: automated answers for common queries, appointment scheduling, and seamless handoffs to human staff when needed.

Darussalam Assets already uses AI to generate job descriptions and populate interview workflows in Microsoft Teams, and plans to train SAP's Joule on internal policies to give employees consistent answers, a model easily adapted for public-facing FAQs and transactional services (Darussalam Assets case study: AI in HR operations).

IVAs deliver 24/7 multilingual support, reduce misdirected calls, and surface sentiment and compliance flags for escalation - benefits well documented by IVA vendors and state‑level pilots (Intelligent virtual agents definition and benefits; StrategusAI government IVA pilot case study).

Start with a narrow, high‑volume service (renewals, benefits checks, triage) so the assistant learns rapidly and produces measurable time‑savings for officials and clearer, faster outcomes for citizens.

“The moment we were done training with 10 to 15 job descriptions, from the 16th or 17th description onwards, it was already generating descriptions the way we wanted,” said Sharma.

A Policy Compliance Checker built around Brunei's own guidance would make oversight practical instead of theoretical: by mapping the AITI's voluntary Guidelines on AI Governance and Ethics and the mandates from the AI Governance and Ethics Working Group to concrete checks - transparency, human oversight, risk assessment and alignment with the Personal Data Protection Order 2025 - ministries can automatically flag procurement language, data-sharing clauses, or model outputs that need human review; see how AITI's guidelines are shaping ministerial thinking (AITI guidelines for AI governance and Brunei Digital Economy Master Plan) and why PDPO 2025 matters for data handling (PDPO 2025 Brunei personal data protection and AI law).

Start with a compact rulebook that converts national and ASEAN principles into automated red‑flags for high‑volume processes - an audit trail for officials and a practical bridge between policy and pilots so Brunei's safe, ethical AI ambitions aren't just words on a page but measurable actions in service delivery.

“AI will be central to Brunei's next Digital Economy Master Plan,” MTIC says Brunei must build AI systems that are safe, ethical and inclusive

Predictive analytics can make Brunei's hospitals far more anticipatory than reactive: the Ministry of Health's new Digital Health unit, led by CMIO Dr. Azmi Mohammad, is explicitly looking to “leverage data for accessible, quality care,” laying the institutional groundwork for forecasts that translate into real operational gains (Brunei digital health plans by CMIO Dr. Azmi Mohammad).

At a practical level, neural‑network driven models - already promoted as tools that forecast patient risk and suggest preventive action - can act like a weather report for hospitals, predicting next‑week bed demand, staffing needs, and supplies so administrators can pre‑position resources and reduce costly last‑minute scrambling (neural network forecasting for healthcare in Brunei).

Local collaboration is accelerating that shift: EVYD Technology's research workshop with MOH and UBD shows how cross‑sector data sharing and joint model development can surface priority research topics and pilotable forecasting use cases in line with national strategy (EVYD Technology, MOH and UBD data-driven healthcare collaboration in Brunei).

Success hinges on clean, interoperable data, strong privacy safeguards, and clinician‑friendly decision support - a small, well‑scoped pilot that proves a measurable drop in wait times or readmissions will make the “what if” potential unmistakably practical for Brunei's public health system.

Bandar Seri Begawan can leap from fixed‑time lights to a pragmatic “SMART” adaptive plan that starts with a few busy arterials and scales across neighbourhood grids: local research already proposed a SMART traffic control signal tailored to Brunei's linked intersections (Proposed SMART traffic control signal for Brunei intersections), and international pilots show how thermal sensors plus AI can turn slow, schedule‑bound junctions into real‑time decision points - an SSRN study using FLIR thermal sensing and reinforcement learning cut intersection delays by 20–38% in pilots, and argues multi‑intersection coordination yields further gains (Adaptive traffic signal optimization using thermal sensors and reinforcement learning (SSRN study)).

Practical vendor approaches - Miovision's adaptive platform and adaptive signal timing systems - illustrate how second‑by‑second optimization reduces travel time, idling and emissions, making a busy morning commute feel like a green ribbon unfurling for an entire corridor (Miovision adaptive traffic management platform).

Start small: pilot a single corridor with clear KPIs (avg delay, stops, emissions), pair sensors with human‑in‑the‑loop oversight, and the result can be unmistakable - not just faster trips but fewer brake lights and cleaner air across the city.

Source	Reported/Claimed Improvement
SSRN study (thermal sensors + RL)	20–38% reduction in average delays (pilot)
Miovision Adaptive	~25% faster travel, ~40% less waiting, ~20% fewer emissions

Prioritizing infrastructure with predictive maintenance turns reactive repairs into scheduled, strategic investments so Brunei's maintenance budgets fix the right asset at the right time: IoT Analytics shows the global market was already $5.5B in 2022 with a projected 17% CAGR to 2028 and a median unplanned‑downtime cost near $125,000 per hour, which makes even a single missed pump failure painfully visible on the ledger (IoT Analytics: Predictive maintenance market).

Practical implementations mix three approaches - anomaly detection for low‑data, scalable alerts; indirect failure prediction where historical specs exist; and RUL models when timing and planning matter - and must include the six core software features (data collection, analytics, pre‑trained models, dashboards/alerts, integrations and prescriptive actions) to move from alerts to work orders.

Deloitte outlines the wider value too: better safety, smarter procurement and higher asset ROI when AI forecasts guide interventions (Deloitte: AI in predictive maintenance).

Start with a narrow pilot - one water pump corridor or a fleet of municipal generators - so a measurable drop in outages proves the case; local pilots like the StrategusAI partnership illustrate how scalable government platforms can convert those pilots into ministry‑wide programs (StrategusAI pilot partnership).

Metric	Value / Notes
Market size (2022)	$5.5 billion (IoT Analytics)
Projected CAGR	~17% to 2028 (IoT Analytics)
Median unplanned downtime cost	~$125,000 per hour (IoT Analytics)
Common software features	Data collection; analytics & models; pre‑trained models; visualization & alerts; third‑party integration; prescriptive actions (IoT Analytics)

A Procurement Anomaly Detector for Brunei would turn siloed purchasing records into an always‑on watchdog that spots collusion, duplicate or forged invoices, and split purchases before funds leave the treasury - think of it as a spotlight that finds a single mismatched invoice in millions of rows.

Built on proven techniques - exploratory data analysis, visualizations and pattern‑mining from recent systematic reviews (EPJ Data Science procurement fraud mapping study) - and a hybrid analytical approach that mixes business rules, anomaly detection, profiling and link analysis, the system can flag bid‑rigging, shell companies and unexplained vendor relationships for human follow‑up rather than overwhelm auditors with false positives (SAS hybrid analytics for procurement fraud).

Pairing those engines with a red‑flag checklist drawn from fraud indicators - overly friendly vendor relationships, repeated low bids then large change orders, unusual invoice patterns - helps translate alerts into actionable investigations (DoDIG fraud red flags and indicators).

Start small - high‑volume categories or a single ministry - and connect vendor, contract and payment data to create an auditable loop that stops waste, preserves public trust, and makes detection demonstrably routine instead of reactive.

Field	Value
Article	Detection of fraud in public procurement using data-driven methods: a systematic mapping study
Journal / Date	EPJ Data Science - 22 July 2025
Authors	Everton Schneider dos Santos; Matheus Machado dos Santos; Márcio Castro; Jônata Tyska Carvalho
Access	Open access - 1,384 accesses

A Hospital Case Prioritization System tailored for Brunei could marry proven triage CDSS products with locally governed machine‑learning pipelines to make emergency care faster, fairer and more auditable: commercial tools such as TriageGO clinical decision support for emergency triage (which lists Brunei Darussalam among supported countries) show how risk‑driven acuity recommendations can be delivered at triage, while AHRQ's ongoing project demonstrates that an EHR‑integrated, ML‑based triage CDS - built to SMART/FHIR standards - can improve identification of critical illness, reduce delays, and expose algorithmic bias for correction (AHRQ machine‑learning triage project).

Start small: pilot in one hospital, use pseudonote or EHR‑text methods to surface full patient history, measure timeliness and equity, and iterate; the payoff is immediate and visceral - an ED system that acts like a second pair of eyes, flagging the single patient likely to deteriorate before the next chart review and freeing low‑risk cases to a faster pathway.

“What we've done is help the nurses confidently identify a larger group of those low risk patients,” said Levin.

Brunei's education system already points toward practical personalization: the SPN21 national education system and a clear Individualised Education Plan (IEP) pathway at secondary level mean AI‑assisted learning plans can slot into existing practice rather than reinvent it - start by automating routine plan updates and progress trackers so SENA teachers and school‑based teams spend more time teaching and less time filing.

By aligning pilots with the SPN21 strategy and the country's inclusive model, which relies on SENA teachers, IEPs/REPs, and inter‑agency support, a narrow, school‑level trial could connect formative assessments to the Ministry's records and surface teacher‑actionable prompts (for example, targeted scaffolds or remediation steps) for review by the School‑Based Team.

Begin in the Model Inclusive Schools where data, training and interdisciplinary teams already exist; the immediate, memorable win is simple - a one‑line alert that flags the single student likely to slip behind before a whole class falls behind, proving personalization can be equitable, auditable and classroom‑ready.

Feature	Evidence / Source
SPN21 national education system	Brunei SPN21 national education system (MFA overview)
Individualised Education Plans (IEPs) continued into secondary	SEAMEO Special Educational Needs programme and IEP continuity in Brunei
Inclusion framework & iNEIS data system	Brunei inclusion framework and iNEIS data system - Education Profiles

A Legislative Drafting Assistant for ministers would turn high‑level principles into clause‑level checks, scanning draft bills and procurement texts for conflicts with Brunei's own Voluntary AI Guide - those seven pillars of transparency, explainability, security, fairness and data governance - and flagging where human‑oversight, risk assessment or privacy safeguards are missing; see Brunei's Guiding Principles for AI (Brunei Voluntary AI Guidelines (USASEAN)).

Built to align with the country's evolving playbook - no standalone AI law yet but a national AI strategy under the 2025 Digital Economy Masterplan and a Personal Data Protection law nearing completion - a drafting assistant can produce annotated language, suggest compliant alternatives, and export an auditable trail for committees and parliamentarians (NBR: Charting ASEAN's Path to AI Governance).

The practical payoff is immediate and tangible: a single, machine‑driven red‑flag on a problematic clause could prevent a high‑risk system from travelling from ministry desk to law overnight, making regulatory impact analysis a routine part of legislative hygiene rather than an afterthought.

Item	Status / Source
Brunei Voluntary AI Guide - core principles	7 principles: transparency, explainability, security, fairness, data governance (Brunei Voluntary AI Guidelines (USASEAN))
National AI strategy	In progress under the 2025 Digital Economy Masterplan (NBR: Charting ASEAN's Path to AI Governance)
Personal Data Protection Law	Finalising - critical for data handling and legislative alignment (NBR: Charting ASEAN's Path to AI Governance)

A Public Engagement Digest for AITI should turn scattered consultation notes into a tight, usable roadmap - mapping public and industry feedback against Brunei's own Voluntary AI Guide and the region's soft‑law playbook so ministers can see at a glance which concerns are principle‑aligned and which need fixes; the digest can fold in inputs from the AI Governance and Ethics Working Group and public consultations (May–July 2024) to show where the Personal Data Protection Order 2025 creates new constraints for pilots (LawGratis: Brunei artificial intelligence law and PDPO implications).

Framed by ASEAN's adaptable, principles‑first approach, a succinct AITI digest - one page per issue, linked evidence, and clear next steps - turns noise into an auditable trail that helps officials prioritise safe pilots and vendor due‑diligence while preserving room for innovation (NBR analysis: Charting ASEAN's path to AI governance).

Include community highlights (symposia, industry pilots) and a short risk matrix so a single red flag in public comments won't be lost in thousands of lines of transcript but becomes a visible trigger for review (US-ASEAN: Brunei Voluntary AI Guidelines overview).

Item	Status / Notes
AITI AI Governance & Ethics Working Group	Established May 2024; public consultation held July 2024 (LawGratis: Brunei AI law consultation details)
Personal Data Protection Order (PDPO)	Enacted March 2025 - key constraint for AI pilots (LawGratis: PDPO and AI implementation implications)
Voluntary AI Guide	Published; principles-based (transparency, fairness, security, etc.) (US-ASEAN: Brunei Voluntary AI Guidelines overview)
Regional framing	ASEAN prefers adaptable, soft-law governance - useful template for digest (NBR analysis: Charting ASEAN's path to AI governance)

Brunei's next sensible step is iterative: prove the promise of a few tightly scoped pilots, lock in legal and privacy guardrails, then scale those wins across ministries - think a six‑month BruneiID trial that lets officials test digital credentials and user flows before a national rollout (BruneiID and Digital Economy Masterplan (Biometric Update)).

Pair each pilot with the Voluntary AI Guidelines so transparency, human oversight and data governance are non‑negotiable from day one (Brunei Voluntary AI Guidelines (US-ASEAN Center)), and invest in practical skills so civil servants can write prompts, evaluate outputs and manage vendor risk - a focused 15‑week program like the AI Essentials for Work bootcamp helps convert policy into operational competence (AI Essentials for Work bootcamp syllabus (Nucamp)).

Start with high‑volume, low‑risk services - ID onboarding, appointment booking, procurement screening or triage - measure time saved and error reduction, preserve an auditable trail, then expand: small pilots that produce visible, repeatable wins are the safest way to turn Brunei's Smart Nation ambitions into everyday public services rather than abstract plans.

Bootcamp	Length	Early bird cost	More
AI Essentials for Work	15 Weeks	$3,582	AI Essentials for Work registration (Nucamp)