The Complete Guide to Using AI in the Government Industry in Bolivia in 2025

As Bolivia moves into 2025, AI matters because it can help close clear gaps in public service delivery - turning paper-driven procurement into digital workflows with OCR and NLP, making grid management more resilient as rural solar grows via deep‑reinforcement approaches, and freeing officials from routine tasks so policy decisions become more data-informed; these are exactly the practical gains global benchmarks like the Government AI Readiness Index 2024 by Oxford Insights aim to measure and the Latin American literature warns must be paired with rights-focused governance - Crossing Routes: Artificial Intelligence Governance and Human Rights in Latin America notes Bolivia among lower-performing countries in the regional AI index and stresses human‑rights frameworks for AI in the region.

At the same time, practical tools - from citizen chatbots to predictive analytics - can improve transparency and electoral integrity if paired with training: civil servants and technologists can build those on-ramps through focused courses like the AI Essentials for Work bootcamp syllabus (15-week program), which teaches promptcraft and workplace AI skills to operationalize these possibilities.

Bootcamp	Length	Cost (early bird)	Registration
AI Essentials for Work	15 Weeks	$3,582	Register for AI Essentials for Work (15-week bootcamp)

Bolivia's legal scaffolding gives AI a distinctly rights‑centered starting point: the 2009 Plurinational Constitution enshrines telecommunications as a basic service (Article 20), guarantees the right to information and communication (Articles 106–107), and expressly tasks the State with promoting science, technology and ICT adoption (Article 103), so any public‑sector AI deployment must sit inside those obligations - and behind that legal frame lie concrete institutional players from the Plurinational Legislative Assembly to oversight bodies like the Contraloría and the Public Defender.

Civil‑society and e‑government work documented by REDES/ADSIB shows a patchwork of initiatives (the Bolivian Electronic Administration Programme and coordination with the Ministry for Transparency) that have advanced online services but still need stronger, unified laws and capacity building to scale AI responsibly; see the GISWatch country report on access to information and e‑government for context.

Regional analysis also flags Bolivia as a lower‑performing country on AI readiness and urges human‑rights‑centred governance rather than ad‑hoc rollouts, a point underscored in

Crossing Routes: Artificial Intelligence Governance and Human Rights in Latin America.

A vivid, practical constraint comes from the Constitution's list of official languages and the requirement that governments use at least two (one being Spanish): any government AI that aims to be inclusive will have to handle a dozen-plus linguistic and cultural contexts, not just code and models, and data/cyber rules noted in regional guides mean privacy, international transfers and security must be built in from day one.

Bolivia's digital backbone has strengthened - about 8.77 million internet users (≈70.2% of the population) rely heavily on mobile access and a growing fiber spine that concentrates roughly 77% of fixed connections along the central urban corridor - but readiness gaps remain stark and operational for AI: fixed broadband penetration and speeds (≈32 Mbps fixed, ≈10 Mbps mobile) lag regional peers, only ~1.4 million fixed subscriptions exist, and urban users vastly outpace rural ones (≈78% vs 38%), leaving many Amazon and high‑Andes communities offline or dependent on expensive satellite links; the country's state operator Entel has extended fiber to 219 of 340 municipalities and opened a US$52M Tier‑III data centre in El Alto (~4,000 m elevation) to host cloud services, yet affordability (basic plans still consume a nontrivial share of low incomes), limited competition, and a Starlink licensing ban - despite an estimated 10,000 gray‑market kits - mean public‑sector AI projects must design for intermittent, mobile‑first connectivity and multilingual, low‑bandwidth delivery if they are to work in Bolivia's geography and market (see the Bolivia connectivity diagnostics - The Internet Frontier (ts2.tech) and Entel El Alto data centre report (Developing Telecoms)).

Metric	Value (source)
Internet users	8.77M (~70.2%) - ts2.tech Bolivia internet statistics
Urban vs Rural internet use	≈78% urban / ≈38% rural - ts2.tech urban vs rural internet use
Fixed broadband subscriptions	~1.4M (~42% households) - ts2.tech fixed broadband subscriptions
Municipalities with Entel fiber	219 of 340 - ts2.tech report on Entel fiber expansion / Developing Telecoms Entel fiber report
El Alto data centre	US$52M Tier III facility - Developing Telecoms coverage of Entel El Alto data centre

“In Bolivia, most of the population [concentrated in urban areas] that accesses an internet connection does so through mobile phones”.

Bolivia's Electronic Government Plan 2018–2025 and the broader Digital Agenda 2025 provide a practical scaffold for introducing AI into public services, but the strategy is clearly evolutionary rather than declarative: AGETIC's digital citizenship work, the nascent Lab‑IA (focusing on fiscal analytics and geospatial AI for vaccination planning), and Law No.

31814 (2023) - which sets principles for responsible AI under the Secretariat of Government and Digital Transformation - create entry points for pilot projects while a full national AI strategy remains absent (see the country profile on Digital Watch country profile: Bolivia digital landscape and governance).

Municipal action plans are already translating e‑government goals into AI‑ready building blocks: La Paz's Open Government Action Plan (2025–2026) showcases an Open Data Portal, a Data Analytics tool for real‑time decision‑making, and public dashboards like

Seguimiento de Obras

that make an obvious UX path for AI‑driven transparency and service automation (La Paz Open Government Action Plan 2025–2026).

Practically speaking, deployment must account for a 70% national internet penetration, mobile‑first usage patterns and modest EGDI scores (E‑Government Rank 99, EGDI 0.66), so pilots that pair OCR/NLP for procurement digitization with low‑bandwidth, multilingual interfaces - examples explored in applied guides such as the Nucamp AI Essentials for Work syllabus (OCR and NLP for procurement) - will likely scale fastest; imagine a municipal

Seguimiento

map updated by field teams feeding geospatial AI models, turning weeks‑old paperwork into an immediately visible progress bar for citizens.

Instrument	Relevance to AI
Electronic Government Plan 2018–2025 / Digital Agenda 2025	Provides policy and operational priorities for digitization and open data that AI can augment
Law No. 31814 (2023) & Secretariat of Government and Digital Transformation	Establishes principles for responsible AI oversight and frameworks for adoption
La Paz OGP Action Plan (2025–2026)	Local implementation model: open data portal, analytics tools and citizen dashboards that AI can plug into
Lab‑IA and sector pilots	Early use cases (fiscal analytics, vaccination planning) that demonstrate feasibility and governance needs

Bolivia's most immediate, high‑impact AI opportunities sit inside health, procurement and infrastructure: AI‑augmented triage and outbreak forecasting can turn scattered clinical signals into clear, prioritised action for scarce hospital beds, while community‑health‑worker workflows can be turbocharged by phone‑based image screening and universal rapid‑diagnostic‑test readers to route only high‑risk patients to distant specialists; these concepts are explored in the review of AI for emergency triage and in practical public‑health roadmaps like “Using Artificial Intelligence to Advance Public Health” (Systematic review of AI in emergency triage (BMC Public Health, 2024), Using Artificial Intelligence to Advance Public Health (International Journal of Public Health, 2023)).

In municipal services, OCR and NLP pilots can slash paper delays in public procurement and make dashboards like La Paz's Seguimiento actionable in real time (OCR and NLP pilots to reduce procurement delays in Bolivian municipal services), and power‑system pilots using reinforcement learning can reduce blackout risk as distributed solar grows.

A vivid, practical image: a rural health worker uses a phone to capture an eye image, an AI flags diabetic‑retinopathy risk and the clinic schedule automatically reserves the next specialist slot - concentrating scarce resources where they matter most and making public services feel faster and fairer to citizens.

Study	Focus	Relevance for Bolivia
Application of AI in triage (BMC Public Health, 2024)	AI methods in emergency/disaster triage	Supports development of outbreak and emergency triage tools for hospitals and field teams
Using Artificial Intelligence to Advance Public Health (Int J Public Health, 2023)	AI for workforce support, RDT readers, image screening, logistics	Blueprint for phone‑based screening, RDT interpretation, and supply distribution in LMICs
Yale AI triage platform (Human Genomics coverage)	Predicts disease severity and length of stay	Model for proactive outbreak triage and hospital resource allocation

“Being able to predict which patients can be sent home and those possibly needing intensive care unit admission is critical for health officials seeking to optimize patient health outcomes and use hospital resources most efficiently during an outbreak.”

Bolivia's 2025 vote showed how AI is now a live threat to electoral integrity - and also how traditional strengths can help: the predominantly paper-based, manual counting system gave resilience against cyber hacks even as social media became a battleground for fast, AI‑generated content that observers flagged as “increasingly sophisticated artificial intelligence‑powered disinformation” (the TSE still managed timely preliminary results via SIREPRE and to publish scanned tallies online, while its social‑media monitoring remained understaffed).

International research underscores the global patterns now visible in Bolivia - AI is being used mostly to create tailored false content and deepfakes that can be weaponized across borders - so local risks include rapid narrative manipulation (as Blackbird.AI documented after the June coup attempt, with coordinated actors amplifying conspiracy threads) and high‑fidelity voice or video forgeries (McAfee notes voice cloning needs only seconds of audio to reach troubling accuracy).

Practical countermeasures that match these threats are already recommended: short‑term transparency rules and platform accountability, watermarking and staffed, well‑resourced monitoring inside the electoral administration, and public literacy campaigns so voters can spot AI‑driven fakes - steps the broader analysis in the CIGI briefing argues are essential to prevent AI from outpacing regulation and to protect trust in Bolivia's democratic processes.

Social media ... was a key element of political communication, with an online political arena driven by TikTok-era campaigning, uneven ad spending favouring some candidates, and increasingly sophisticated artificial intelligence-powered disinformation.

Data governance, privacy and technological sovereignty in Bolivia still look like a useful library with no single catalogue: national scores show a near‑total absence of a unifying data strategy or protective statutes - no national data strategy, no personal data protection law, and no open‑data or FOI backbone - details visible in the country profile from the Global Data Governance Mapping country profile for Bolivia.

At the same time, constitutional and sectoral provisions do give citizens some safeguards - Bolivia's Constitution recognises privacy and the telecoms law and Digital Citizenship rules place limits on processing - yet experts note the country lacks an overarching personal‑data law and that existing protections remain fragmented (see the Personal Data Protection Guidelines (Fundación Microfinanzas BBVA)).

The regulatory environment also affirms that public institutions and private actors performing public duties are holders of public information, which creates a legal opening for proactive disclosure and oversight if coordinated well (OECD Public Integrity Indicators for Bolivia).

Practically, this patchwork raises risks for citizen privacy, limits the government's capacity to assert technological sovereignty over public datasets, and slows the benefits of open data for transparency and innovation - fixing it will require a single legal spine, targeted training for data stewards, and practical open‑data roadmaps so public information can be both protected and productively reused.

Instrument / Area	Status (research)
National Data Strategy / AI strategy	Absent (score 0) - Global Data Governance Mapping country profile for Bolivia
Personal Data Protection Law	No overarching law (score 0); sectoral provisions only - Personal Data Protection Guidelines (Fundación Microfinanzas BBVA)
Open Data Law / Freedom of Information	Absent or limited (score 0) - Global Data Governance Mapping country profile for Bolivia
Public institutions as holders of public information	Recognised in regulatory framework - OECD Public Integrity Indicators for Bolivia
Local training & capacity	Available from providers offering data governance training (e.g., NobleProg)

Procurement is where AI's promise meets Bolivia's legal realities and political economy: public contracting follows Supreme Decree 181 and is published on the national platform SICOES, with built‑in preference margins (20% for micro and small enterprises and a 5% margin for Bolivian‑partnered firms) and clear thresholds for minor, ANPE and public bidding that shape who can compete - details usefully summarized in the Lexology guide to Public Procurement in Bolivia (Lexology).

Those structural features - and a state‑run economy where SOEs and public entities dominate - mean any procurement AI must be tuned to support inclusivity and national policy goals, not just cost minimization.

Ethics and governance therefore matter: procurement models trained on historical awards can entrench exclusion unless paired with explainability, bias audits and appeal mechanisms (the

black box

problem discussed in Comprara's primer on AI ethics in procurement (Comprara)), while regional work shows analytics can also flag corruption patterns if used transparently and with oversight (CAF event: How AI can curb corruption in Latin America and the Caribbean).

Practically, successful public‑sector pilots will marry algorithmic audits, human review panels, local capacity‑building (to meet tech‑transfer and hiring expectations) and privacy safeguards so AI shortlists expand, rather than narrow, Bolivia's supplier base - otherwise the tech risks becoming an efficient gatekeeper instead of a tool for fairer, faster contracting.

Procurement feature	Implication for AI
Supreme Decree 181 / SICOES publication	AI must align with formal tender rules and public disclosure processes (Lexology guide to Public Procurement in Bolivia)
SME & domestic preference margins (20% / 5%)	Models should preserve policy preferences and avoid disadvantaging small or local suppliers
State‑run economy / SOEs	High public participation means AI must support competition and transparency to reduce capture (US State report)
Corruption detection potential	Procurement analytics can surface anomalies if governed transparently (CAF event on AI to curb corruption in Latin America and the Caribbean)

Bolivia's nascent AI law (Law No. 31814) and the Secretariat of Government and Digital Transformation create a clear ethical starting point - risk‑based rules, plural debate and privacy protection are written into the playbook - but translating those principles into trustworthy systems will require three practical moves: rigorous algorithmic audits and human‑rights impact assessments to catch bias and protect dignity as recommended in regional analyses like CEBRI: Crossing Routes - Artificial Intelligence Governance and Human Rights in Latin America; fast, public transparency (explainable models, logging and redress channels) so citizens can see how decisions affecting benefits or services are made; and targeted capacity building - training data stewards, auditors and municipal officials while favouring mission‑fit, smaller models where appropriate to curb cost and carbon - as argued in practical ethics guidance and industry analyses such as Publicis Sapient: Ethical AI Implementation and ESG analysis.

Left uncorrected, well‑meaning pilots risk becoming a “greenwashed” service - useful on paper but unusable in practice - so pairing Law No. 31814's principles with funded training, multi‑stakeholder oversight and routine audits is the quickest route to AI that actually earns public trust in Bolivia (Law Gratis: Bolivia Artificial Intelligence Law overview).

“Ethical AI will be a crucial part of ESG itself, and not a metric measured on its own.”

Implementation in 2025 should marry Bolivia's Plan Estratégico de Gobierno Electrónico 2018–2025 - anchored on three pillars (gobierno soberano, eficiente y abierto y participativo) with its critical‑path diagnostics and monitoring framework - with a practical, phased AI playbook: start with strategic alignment to prioritise high‑impact, low‑complexity pilots that respect sovereignty and language requirements; move quickly into infrastructure choices that favour hybrid, low‑bandwidth delivery for mobile‑first users; build a disciplined data strategy and pipelines so models use trusted, interoperable datasets; develop and validate models for narrow tasks (OCR/NLP for procurement, triage tools, geospatial Seguimiento); deploy with MLOps and staged rollouts; and lock in governance, audits and continuous optimisation.

The global six‑phase methodology - Strategic Alignment; Infrastructure; Data Strategy; Model Development; Deployment & MLOps; Governance & Ethics - offers a realistic 18–24 month horizon for pilots to prove value and scale if paired with the Electronic Government Plan's institutional roles and monitoring systems (see Bolivia's Electronic Government Plan 2018–2025).

Practical next steps: select two municipal pilots (one procurement OCR/NLP, one health triage or grid control), fund short‑term infrastructure and training, run explainability and bias audits, and fast‑track staff capacity through focused courses like AI Essentials for Work 15‑Week Bootcamp so civil‑servant teams can operationalise prompts, pipelines and governance; this mix of strategic sequencing, local capacity and clear milestones is how Bolivia moves from paper‑bound processes to AI‑augmented services that citizens actually trust.

Phase	Typical duration	Key focus
Phase 1: Strategic Alignment	2–3 months	Readiness assessment, use‑case prioritisation
Phase 2: Infrastructure Planning	3–4 months	Architecture, cloud/hybrid decisions, edge for low‑bandwidth
Phase 3: Data Strategy	4–6 months	Data pipelines, governance, quality/lineage
Phase 4: Model Development	6–9 months	Training, validation, bias mitigation
Phase 5: Deployment & MLOps	3–4 months	CI/CD, monitoring, staged rollouts
Phase 6: Governance & Optimization	Ongoing	Audits, transparency, continuous value capture

“If there is no data strategy, there is no AI success.”