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Society and innovations
Journal home page:
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Artificial intelligence and public administration: trends,
challenges, and prospects
Ilkhomjon ALIEV
1
Institute of Legislation and Legal Policy under the President of the Republic of Uzbekistan
ARTICLE INFO
ABSTRACT
Article history:
Received May 2025
Received in revised form
15 June 2025
Accepted 25 June 2025
Available online
15 July 2025
Governments worldwide are increasingly exploring artificial
intelligence (AI) to transform public administration, improve
service delivery, and enhance policy-making. This article surveys
contemporary trends in AI adoption by public agencies, drawing
on international studies and country examples (USA, EU, Japan,
South Korea, Uzbekistan). It highlights AI’s promise to boost
efficiency, citizen engagement, and data-driven governance,
while analyzing legal, ethical, technical, and social challenges
such as bias, privacy, infrastructure gaps, and workforce
readiness. We examine prospects
–
for instance, AI-powered
state services, strategic analytics, and e-government chatbots
–
and underscore the need for robust governance and public trust.
Perspectives from experts (OECD, World Bank, UNDP)
emphasize that governments must balance innovation with
oversight. Finally, we review Uzbekistan’s national AI strategy
(Resolution PP-358) and Digital Uzbekistan
–
2030 initiative,
which set concrete targets (e.g. $1.5 billion AI market, 10% of e
-
services using AI) and institutional measures (big data platform,
AI coordination center) to accelerate AI in the public sector. This
comprehensive analysis informs policymakers and scholars
about the evolving AI
–
governance landscape and the road ahead.
2181-
1415/©
2025 in Science LLC.
DOI:
https://doi.org/10.47689/2181-1415-vol6-iss6/S-pp106-112
This is an open access article under the Attribution 4.0 International
(CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/deed.ru)
Keywords:
Artificial Intelligence,
public administration,
digital government,
e-government,
ethics,
governance,
Uzbekistan,
OECD,
UNDP,
World Bank.
1
PhD student, Institute of Legislation and Legal Policy under the President of the Republic of Uzbekistan.
Жамият
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инновациялар
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Общество
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инновации
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Society and innovations
Special Issue
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06 (2025) / ISSN 2181-1415
107
Sun’iy intellekt va davlat boshqaruvi: yo‘nalishlar,
qiyinchiliklar va kelajak istiqbollari
ANNOTATSIYA
Kalit so‘zlar
:
Sun’iy intellekt,
davlat boshqaruvi,
raqamli hukumat,
elektron hukumat,
etika,
boshqaruv,
O‘zbekiston,
IQHT,
BMTTaD,
Jahon banki.
Dunyodagi hukumatlar davlat boshqaruvini o‘zgartirish,
xizmat ko‘rsatishni
yaxshilash va siyosat ishlab chiqishni
takomillashtirish uchun sun’iy intellektdan (SI) tobora ko‘proq
foydalanmoqda. Ushbu maqolada xalqaro tadqiqotlar va
mamlakatlar (AQSH, Yevropa Ittifoqi, Yaponiya, Janubiy Koreya,
O‘zbekiston) misolida davlat idoralari tomonidan SI’ni joriy
etishning zamonaviy tendensiyalari o‘rganiladi. Unda SI’ning
samaradorlikni oshirish, fuqarolar ishtirokini kuchaytirish va
ma’lumotlarga asoslangan boshqaruvni takomillashtirish
imkoniyatlari ta’kidlanib, noxolislik, shaxsiy ma’lum
otlar
maxfiyligi, infratuzilma yetishmovchiligi va kadrlar tayyorgarligi
kabi huquqiy, axloqiy, texnik va ijtimoiy muammolar tahlil
qilinadi. Biz istiqbollarni, jumladan, SI’ga asoslangan davlat
xizmatlari, strategik tahlillar va elektron hukumat chatbotlarini
ko‘rib chiqamiz hamda kuchli boshqaruv va jamoatchilik
ishonchining zarurligini ta’kidlaymiz. Mutaxassislarning (IHTT,
Jahon banki, BMTTDp) fikriga ko‘ra, hukumatlar innovatsiyalar
va nazorat o‘rtasidagi muvozanatni saqlashi kerak. Nihoyat, biz
O‘zbek
istonning milliy SI strategiyasi (PQ-358-sonli qaror) va
"Raqamli O‘zbekiston
-
2030" dasturini ko‘rib chiqamiz. Bu
dasturlar aniq maqsadlarni (masalan, 1,5 milliard dollarlik SI
bozori, elektron xizmatlarning 10 foizida SI’dan foydalanish) va
davlat sektori
da SI’ni rivojlantirishni tezlashtirish uchun
institutsional chora-
tadbirlarni (katta ma’lumotlar platformasi,
SI’ni muvofiqlashtirish markazi) belgilaydi. Ushbu keng qamrovli
tahlil siyosatchilar va olimlarni rivojlanayotgan SI boshqaruvi
manzarasi va kel
ajakdagi yo‘nalishlar haqida ma’lumot bilan
ta’minlaydi.
Искусственный
интеллект
и
государственное
управление: тенденции, вызовы и перспективы
АННОТАЦИЯ
Ключевые слова:
искусственный
интеллект,
государственное
управление,
цифровое правительство,
электронное
правительство,
этика,
управление,
Узбекистан,
ОЭСР,
ПРООН,
Всемирный банк
.
Правительства во всем мире все чаще изучают
возможности искусственного интеллекта (ИИ) для
трансформации государственного управления, улучшения
предоставления услуг и совершенствования процесса
разработки политики. В данной статье рассматриваются
современные тенденции внедрения ИИ государственными
учреждениями на основе международных исследований и
примеров стран (США, ЕС, Япония, Южная Корея,
Узбекистан). Статья подчеркивает потенциал ИИ в
повышении эффективности, вовлеченности граждан и
управления на основе данных, одновременно анализируя
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юридические, этические, технические и социальные
проблемы, такие как предвзятость, конфиденциальность,
пробелы в инфраструктуре и готовность рабочей силы. Мы
рассматриваем перспективы
-
например, государственные
услуги на
базе ИИ, стратегическую аналитику и чат
-
боты
электронного
правительства
-
и
подчеркиваем
необходимость надежного управления и общественного
доверия. Мнения экспертов (ОЭСР, Всемирный банк, ПРООН)
подчеркивают, что правительствам необходимо находить
баланс
между инновациями и контролем. Наконец, мы
рассматриваем национальную стратегию ИИ Узбекистана
(Постановление ПП
-
358) и инициативу "Цифровой
Узбекистан
-
2030," которые устанавливают конкретные цели
(например, рынок ИИ объемом $1,5 млрд, 10% электронных
услуг с использованием ИИ) и институциональные меры
(платформа больших данных, центр координации ИИ) для
ускорения внедрения ИИ в государственном секторе. Этот
всесторонний анализ информирует политиков и ученых о
развивающемся ландшафте управления искусственным
интеллектом и перспективах его развития
.
INTRODUCTION
Global adoption of AI in the public sector is accelerating. Governments play multiple
roles
–
as enablers, regulators, users, and funders
–
in this transformation. The OECD notes
that “AI, including generative AI, has the potential to transform how governm
ents function,
design policies, and provide services” if used strategically and responsibly. In practice,
countries are embedding AI into internal processes and citizen-facing services. For
example, a U.S. survey found that over half of federal, state, and local officials use AI tools
daily, aiming to streamline operations and decision-making. Similarly, the EU is exploring
AI in health, mobility, e-government, and education to boost analytic capacity and
efficiency. In Asia, South Korea has proclaimed a sh
ift from digital platforms to an “AI
Government,” building a shared GenAI infrastructure for agencies. These cases reflect a
broad trend: governments worldwide are treating AI as a strategic priority to enhance
productivity and citizen services. For instance, Deloitte envisions AI improving report
generation, case management, and knowledge sharing in government, while technology
firms highlight chatbots and data analytics as tools for a more responsive state.
METHODS
At the same time, experts emphasize that AI adoption must be coupled with caution.
Across jurisdictions, leaders are issuing policy and guidance on AI risk management. In the
United States, the Biden administration’s 2023 Executive Order (EO 14110) and
subsequent OMB memos have embedded principles of fairness, transparency, and privacy
into government AI use. The U.S. Government Accountability Office reported that by mid-
2024, federal agencies had “fully carried out” the EO’s initial management and talent
requirements, setting up AI councils, guidance, and talent programs. Likewise, the
European Commission has commissioned studies to understand barriers in e-government
AI and is finalizing an AI Act. A recent EU study found that while AI could “enhance citiz
en-
government interactions” and efficiencies in key services, uptake is hindered by
“complex
public procurement processes, difficulties in data management, [and] a lack of regulatory
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clarity”
. OECD research concurs that governments are crafting national strategies, data
governance frameworks, and standards to foster a “safe, secure and trustworthy” AI
environment.
RESULTS
Challenges:
Despite potential gains, AI deployment in government faces substantial
hurdles. Ethically and legally, public sector AI must guard against bias, discrimination, and
opacity. The OECD cautions that unchecked AI can “amplify bias, lack transparency, and
breach privacy,” leading to unfair or discriminatory outcomes. For instance, algorithmic
systems in policing or benefits decisions have raised equity concerns worldwide.
Policymakers thus stress AI governance, accountability, and redress mechanisms. Data
privacy regulations (e.g., GDPR in Europe) constrain public AI use unless privacy is built
in.
Technical barriers are also significant, especially in developing contexts. The World
Bank notes that many governments lack the digital infrastructure and data readiness
needed for AI. Low awareness and limited digital skills in the civil service are cited as top
impediments. In Bank client
countries, “inadequate foundational digital technologies, low
availability or quality of data, and low access to digital skills” are major limits on AI use.
Similarly, surveys show governments often struggle with legacy IT systems and
fragmented data silos. Procuring advanced compute (GPU clusters) and integrating AI with
existing systems pose fiscal and expertise challenges.
Social and organizational factors also constrain AI’s reach. Public trust in AI
-driven
decisions remains uneven. An NCSL analysis of the U.S. context found that unclear
governance or ethical frameworks were the top barrier (48%) to government AI use.
Workers and citizens may resist the automation of services without adequate
transparency. Moreover, introducing AI often demands new skills; governments are
anxious about the digital divide between well-resourced agencies and those lagging. As
UNDP observes, many institutions “are being asked to regulate what they barely have the
bandwidth to understand”. The UNDP highlights a tension: gove
rnments are urged to
experiment with AI, yet institutional capacity (for procurement, oversight, and citizen
engagement) can lag. Without deliberate measures, AI pilots risk reinforcing existing
inequalities or privileging external vendors.
Future Prospects:
Looking ahead, AI promises to reshape public administration in
several ways. In service delivery, natural language chatbots and virtual assistants could
provide 24/7 citizen support and simplify interactions. For example, early pilots in Korea
include ChatGPT-powered chatbots to train transit employees and mobile apps that offer
AI-driven advice to farmers. AI can also personalize government communications and
triage requests by urgency or need. Generative AI tools are being explored to auto-draft
docume
nts: Korea’s procurement service uses GenAI to help draft RFPs, while IP offices
use AI to analyze patents. In health, AI image analysis and predictive models could optimize
diagnostics and resource allocation (consistent with Uzbekistan’s plan for AI in
healthcare). In transportation, smart traffic systems and autonomous vehicles (cited in the
EU study) may emerge as mature domains for public AI use.
Beyond services, AI offers powerful analytics for strategic decision-making.
Governments can use machine learning to detect fraud (as cited by Deloitte and the World
Bank), forecast budgetary or epidemiological trends, and optimize supply chains (e.g.
disaster response logistics). Data-driven policy design could become more dynamic, with
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AI identifying emerging patterns from citizen data. However, experts urge that human
oversight remain central: UNDP stresses that AI must “support –
not replace
–
public
decision-
making,” and that systems be co
-designed with frontline staff and communities.
Crucially, the future of AI in government depends on trust and inclusion. OECD and
UN reports emphasize that AI systems in the public sector must be “human
-
centric” and
co-governed. The new UNDP Human Development Report (2025) and Global AI Summits
have echoed the call for AI
that is “trustworthy, inclusive, and democratically governed”.
In practice, this means embedding ethics and transparency from the start: performing
algorithmic impact assessments, engaging citizens in oversight, and legislating clear
accountability for automated decisions. Institutional capacity-building is key: training civil
servants in AI literacy, appointing Chief AI Officers (as in the US), and creating multi-
agency councils to share best practices. The OECD finds many governments are already
institutionalizing such roles and frameworks.
Regional and International Perspectives:
Approaches vary by region, reflecting
political cultures and policy environments. In the United States, a flurry of federal actions
underscores a push for enterprise-wide AI integration. Beyond the Executive Order and
OMB guidance, U.S. agencies have requested increased R&D budgets (over $1.9 billion in
FY2024) and embraced NIST’s AI Risk Management Framework. Both Congress and state
legislatures are considering laws on AI inventories, impact assessments, and procurement
standards, indicating a governance-driven mindset.
The European Union stresses both opportunity and caution. The EU’s new AI Act (in
force August 2024) will regulate high-risk public sector AI, and the Commission funds
projects like the
Adopt AI
study (Sept 2024), which identified procurement and data
challenges. EU research also highlights organizational enablers: a Joint Research Centre
survey of public managers in seven countries concluded that leadership support, a clear AI
strategy, and in-house expertise are critical to AI uptake. It recommends that governments
invest not only in technology but in ethics and legal training for officials. EU member states
have begun launching AI offices (e.g. France’s Interminis
terial AI Task Force) and exploring
cross-border data sharing within the Digital Single Market.
In Asia, Japan and South Korea illustrate contrasting styles. Japan’s
Society 5.0
vision
drives a human-centric, incremental AI adoption. Its newly issued guideline (May 2025)
explicitly encourages generative AI use in government processes “for the sake of evolution
and innovation,” while emphasizing risk management. Japan is also building government
cloud infrastructure to democratize AI development (in partnership with private cloud
providers, as AWS reports). South Korea, by contrast, is rapidly centralizing AI innovation:
the National Information Society Agency (NIA) is creating a
government-wide
GenAI
platform. In April 2024, Korea released principles prioritizing private-sector cloud and
Korean LLMs for public use, aiming to accelerate AI rollout via public
–
private partnership.
Korean examples include AI tools for public procurement and labor-law guidance, and
initiatives to open government data to drive AI innovation. These illustrate a dynamic,
experimental approach.
Global institutions echo these themes. The World Bank urges developing countries
to see AI as a development tool but warns of a “digital divide” in readiness. It identifies use
cases (fraud detection, personalized services, analytics) and calls for ethical principles and
supporting institutions as outlined in chapter four of its public sector AI report. The OECD
recommends that governments act on all fronts: as users of AI to improve efficiency, and
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as regulators to ensure fairness. UNDP emphasizes that AI should be shaped by strong
public institutions. A recent UNDP Asia-
Pacific commentary argues that without “coherent
digital ecosystems and contextual governance,” rushing AI adoption risks exclu
sion. It
proposes that experimentation and oversight co-evolve, so that policy frameworks are
informed by on-the-ground learning.
Uzbekistan’s Strategy:
Uzbekistan provides a national perspective. In October
2024, the President approved Resolution PP-358, formalizing the
Strategy for the
Development of AI Technologies until 2030
. This strategy explicitly ties into the country’s
broader
Digital Uzbekistan
–
2030
agenda. Key target indicators were set: by 2030,
Uzbekistan aims for a $1.5 billion annual volume o
f AI-based products/services and 10%
of public services delivered via AI-enhanced e-government platforms. The strategy also
commits Uzbekistan to enter the top 50 of the global
Government AI Readiness Index
.
To achieve these goals, the resolution mandates concrete actions. It tasks ministries
to create a unified “Big Data” repository by Sept 2025 and to launch high
-performance
computing infrastructure by 2026. A special Coordination Commission under the
Digital
Uzbekistan 2030
strategy (chaired by the Prime Minister) is charged with overseeing AI
projects and ensuring their transparency and competitiveness. The law also establishes a
new
Center for the Development of Artificial Intelligence and the Digital Economy
, which will
evaluate AI systems and coordinate data-sharing among agencies. In sectors like banking,
tax, healthcare, agriculture, and energy, Uzbekistan has prioritized AI use cases (fraud
prevention, diagnostics, resource forecasting, etc.). A $50 million state loan was allocated
to subsidize AI development starting in 2025. In summary, Uzbekistan’s strategy
illustrates a comprehensive approach: it sets clear metrics, allocates funding, mandates
data infrastructure, and embeds AI within a national digital transformation plan.
CONCLUSION/DISCUSSION
The current trajectory suggests that AI will play an ever-greater role in public
administration. When implemented thoughtfully, AI can make government more efficient,
data-driven, and responsive. Examples from around the world show potential benefits:
streamlined services, smarter decision support, and novel citizen engagement channels.
However, realizing these gains requires navigating serious challenges. Ethical governance,
legal safeguards, technical capacity, and public trust are essential prerequisites. The
consensus among scholars and international organizations is that AI must be approached
as a public policy capability: governed proactively and iteratively, not simply adopted off-
the-shelf. Governments should prioritize inclusive AI by design
–
involving civil servants,
technologists, and citizens in creating AI systems that reflect public values. The
experiences of the US, EU, Japan, Korea and Uzbekistan suggest that multi-stakeholder
collaboration (public
–
private partnerships, cross-border knowledge-sharing) is key. In
coming years, we expect continued investment in AI expertise within governments, new
norms of transparency (e.g. AI registries, impact assessments), and international dialogue
on best practices. Ultimately, the promise is to transform state services and policymaking
in ways that enhance welfare and democracy. This will require a “human
-
centered” AI
path, as Japan’s Society 5.0 envisions, and as global leaders have urged, treating AI as a
public asset to be stewarded carefully.
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