Top 5 Jobs in Government That Are Most at Risk from AI in Bolivia - And How to Adapt

Bolivia's public workforce matters because the state still carries outsized weight in an economy under strain: GDP per capita is only $3,748, the business climate is weak and public finances are tightening, creating pressure to cut costs by automating routine tasks in local offices and utilities; the Coface country file paints this fragile backdrop clearly (Coface Bolivia country risk file).

That pressure collides with a gendered automation risk found in Latin America - women face a slightly higher chance of job loss from automation (21% of women vs 19% of men at high risk) - so any tech transition must pair upskilling with equity (IDB task-based automation risk study).

Practical AI training - like Nucamp's 15-week AI Essentials for Work - can help public servants shift from repetitive tasks to oversight and service design, turning a fiscal squeeze into an opportunity to modernize citizen services without leaving people behind (Nucamp AI Essentials for Work bootcamp registration); after all, Bolivia's reserves include only about USD 47 million in liquid currency, a vivid reminder that cost-saving reforms will be urgent.

Economic activity slowed in 2024, reflecting the intensification of macroeconomic imbalances and the sharp deterioration of external accounts. Household consumption (68% of GDP) continued to support growth, but rising food and transportation inflation due to goods and fuel shortages fuelled by bad weather conditions and tighter foreign exchange controls, eroded purchasing power.

Methodology: the ranking blends job‑level automation scores with Bolivia's occupational mix to show where AI could bite hardest: automation probabilities come from Will Robots Take My Job occupational automation scores, which scores abilities, skills and tasks for 897 occupations, and those scores were averaged by occupational group before being combined with ILO/ILOSTAT employment counts to estimate each country's share of workers at “high risk” (BizReport follows Will Robots Take My Job's cutoff of 61%+ to flag high risk).

That approach explains why Bolivia shows up near the top - about 79.81% of the labor force falls into high‑risk groups - and why clerical, plant/machine and craft occupations dominate the list.

The method also flags equity concerns: a task‑based gender study for Latin America finds women face a higher average automation risk (21% of women vs. 19% of men at very high risk), so the numbers call for targeted reskilling, not one‑size‑fits‑all cuts.

For readers wanting the data sources and technical steps, see Will Robots Take My Job occupational automation scores for job scores, the BizReport analysis of occupational shares and country impacts, and the IADB task‑based study on automation risk for women in Latin America.

Registry clerks are among the most exposed Bolivian public servants because their work is intensely document‑centric - think stacks of permits, scanned IDs and repeated data entry - and automation tools are designed precisely for those tasks; ABBYY intelligent process automation (IPA) solutions explains how AI plus RPA and intelligent document processing (IDP) can extract data from messy forms, route records and achieve high rates of straight‑through processing, turning hours of copying into minutes.

In practice this means RPA bots can handle routine inputs while humans focus on exceptions, but evidence from public‑sector deployments shows a catch: automation without careful oversight intensifies the hardest parts of the job - handling frustrated constituents, fixing hallucinations and correcting bot errors - so clerks need targeted upskilling in process‑mining, IDP oversight and adjudication work rather than simple redundancy.

Case examples across government also underscore that well‑designed automation can free staff for higher‑value tasks, but only if procurement, training and performance metrics are set up front; see the Roosevelt Institute report on AI and government workers for why human oversight and thoughtful rollout must come first.

[F]ailures in AI systems, such as wrongful benefit denials, aren't just inconveniences but can be life-and-death situations for people who rely upon government programs.

Water treatment plant operators in Bolivia sit squarely in automation's crosshairs because so much of their daily work - monitoring flows, dosing chemicals, flipping valves and responding to alarms - is precisely what SCADA, PLCs, sensors and AI do best; automation promises faster, cheaper, safer treatment (real‑time monitoring can even tweak chlorine dosing before customers notice) but that also means routine control and sampling tasks are prime targets for replacement unless roles are recast.

The fix is practical and local: utilities can phase in digital tools while retraining operators to run OT/IT stacks, supervise predictive‑maintenance models and manage cybersecurity and exception workflows rather than manual tuning - training that mirrors the operator upskilling recommended in industry guides and vendor case studies (see automation fundamentals for operators at Racoman and how real‑time data improves control and predictive maintenance at Walchem).

Bolivia's cash‑constrained utilities should prioritize programmatic OT refreshes, vendor partnerships and targeted hiring pipelines so older workforces aren't left behind, using pilots to prove savings and safety before scale (Stantec's OT checklist is a useful playbook).

The net result can be fewer emergency callouts, smarter energy use and a smaller carbon footprint - if automation is implemented as augmentation, not unilateral replacement.

Building maintenance technicians in Bolivia face a changing workbench: automation and smart‑building tech are already shifting routine tasks - scheduled filter swaps, basic HVAC tuning and repetitive inspections - toward sensors, predictive maintenance and remote control, so jobs that once meant steady muscle and muscle memory now risk being reframed around software and data (see the rise of automation in skilled trades at Impact of Automation on Skilled Trades (PTT.edu)).

That doesn't mean a one‑way street to unemployment; the same forces create openings to run building OT/IT stacks, interpret sensor dashboards and lead energy‑efficiency retrofits for cash‑strapped municipalities.

A task‑level view of automation risk helps here: occupations with many routine, non‑collaborative tasks are most exposed, so the smart strategy is to pivot technicians from screwdriver work to oversight of automated systems and troubleshooting exceptions rather than competing with machines head‑on (Automation Risk Tool and Guidance (Cedefop)).

Practical steps for Bolivia include employer‑led pilots, targeted upskilling in predictive‑maintenance tools, and short AI bootcamps that teach technicians to translate field signals into decisions - picture a veteran tech trading a wrench for a tablet and a real‑time leak map, not retirement.

Local policy and training partnerships can make that transition realistic and equitable rather than abrupt (AI Essentials for Work Syllabus - Nucamp).

The decisions of companies, governments, and educators will help to shape the ultimate outcomes of the A.I. revolution.

Permit counter agents in Bolivia are prime candidates for rapid change because so much of their work - form validation, status checks and routine customer questions - is exactly what conversational AI, self‑service portals and workflow automation can do faster and around the clock; governments that get the mix right free staff for complex, in‑person problem solving rather than replace them outright.

Practical adaptation means starting with an automation vision and governance (so projects don't become a “wild‑west” of fragile scripts), pairing secure, audited tools with pilots that move simple renewals and document checks online, and investing in kiosk/agent training so frontline staff become exceptions managers and escalation experts rather than data clerks.

No‑code ITSM and portal tools let agencies build and iterate forms and workflows without heavy IT lift, improving uptake and reducing ticket volume, while contact‑centre and conversational AI examples show big wins - one council cut routine calls by 86% - freeing staff to handle the human moments that matter.

For Bolivia's cash‑and‑capacity constrained municipalities, the smart route is phased pilots, vendor partnerships and clear lifecycle plans so citizens get faster, fairer service and permit agents keep the expertise that automation can't replicate (government automation strategy and opportunities, no‑code ITSM and public sector portals best practices, AI automation in local government contact centers case study).

By using automation solutions, federal agencies will be able to change those processes to quickly respond to future global challenges.

IT support technicians in Bolivia are at the frontline of a quiet revolution: automation can smart-route tickets, auto-resolve routine onboarding/offboarding and run self‑service diagnostics that shrink repetitive work - but those same tools also threaten to hollow out first‑line roles unless technicians pivot to higher‑value oversight.

Government IT teams with tight budgets and limited in‑house capacity often turn to vendor-managed AI and cloud services, which can shave costs but raise risks around data governance, privacy and outsourced accountability; as observers note, automation often shifts work from staff to unpaid end users and contractors rather than eliminating complexity (so a single “hallucinated” AI reply or misrouted ticket can cascade into hours of manual fixes and escalations).

The prudent path for Bolivian IT technicians is practical and immediate: build skills in automation orchestration, incident response, cybersecurity for operational technology, and vendor contract management; insist on human‑in‑the‑loop controls and clear change governance; and pilot low‑risk automations that free time for complex troubleshooting rather than accelerate downsizing.

Policy and training investments should treat IT staff as guardians of service continuity - experts who tune, audit and correct automation - rather than as targets for replacement, echoing calls for responsible deployment and worker‑centred implementation in public agencies (Roosevelt Institute: AI and Government Workers, GovTech eBook on automating IT ticketing).

[F]ailures in AI systems, such as wrongful benefit denials, aren't just inconveniences but can be life-and-death situations for people who rely upon government programs.

Practical next steps for Bolivia start with pairing targeted pilots and training with real funding and shared costs: use the IDB's $62 million program to seed pilots that automate routine tasks while preserving human‑in‑the‑loop checks (so registry clerks, permit agents and IT technicians become exceptions managers, not benchwarmers), adopt a co‑investment model where government, employers and workers share training costs as recommended by skills funders (co‑investment model for workforce skills), and scale short, job‑focused courses like Nucamp's AI Essentials for Work to teach promptcraft, oversight of AI systems and basic OT/cyber skills for plant operators and maintenance technicians; complementary World Bank priorities - improving public services and resilience - give a policy frame for these investments.

Start small: pilot one municipality, measure service speed and error rates, fund instructor‑led reskilling for affected cohorts (including women and youth), and lock procurement and data‑governance rules into every contract so automation saves money without shifting risk to the poorest citizens.

“The program will contribute decisively to the efforts of the Bolivian government to ensure the sustainability of a consolidated public sector and deepen the process of fiscal decentralization being carried out within the new constitutional framework,” said Ramiro López Ghio, specialist in fiscal and municipal development and IDB project team leader.