TITLE
The Role o A i icial In elligence in he Economic De elopmen o Sou h Asia:
F om Technological Dependence o Sel -Reliance
Maymuna A a
G oup O Science, Adamjee Can onmen college
Dhaka, Bangladesh
Keywo ds
Sou h Asia, A i icial in elligence, Economic g ow h, Technological dependence, GDP, IT
sec o , Sel - eliance
Abs ac
Sou h Asian coun ies ha e long elied on he echnology, machine y, and high-quali y
se ices o de eloped coun ies (Haque, 2021; Wo ld Bank, 2023), limi ing economic
g ow h. In ecen yea s, a i icial in elligence (AI) has educed his dependency and
opened up new possibili ies o local manu ac u ing, au oma ion, and e iciency
de elopmen (Lee, 2022; Pa k & Kim, 2023). Analysis o economic and echnical da a
om 2010-2024 showed ha AI–based ini ia i es a e e ec i e in inc easing GDP and
educing o eign dependence (Wo ld Bank, 2021; PwC India, 2022). The esul s o he
esea ch indica e ha h ough app op ia e policies, in es men s in skilled manpowe
and Technology, Sou h Asian coun ies can achie e economic sel -su iciency and
sus ainable g ow h.
1.In oduc ion
Sou h Asia is home o a signi ican po ion o he wo ld's popula ion and is a egion wi h
as -g owing economic po en ial (Wo ld Bank, 2023). Howe e , coun ies in he egion—
Bangladesh, India, Pakis an, Nepal, S i Lanka, Bhu an, Maldi es, and A ghanis an—ha e
his o ically elied on he echnology, so wa e, machine y, and ad anced se ices o
de eloped coun ies (Haque, 2021; Wo ld Bank, 2021). Fo example, echnology
p oduc s om Sou h Ko ea, Japan, Singapo e, and China ha e lowed widely in o Sou h
Asian ma ke s (Lee, 2022; Pa k & Kim, 2023).
This dependency has limi ed local indus ializa ion and shi ed a la ge po ion o he
alue chain o e seas (Haque, 2021). As a esul , de eloped coun ies ha e become
economically s onge , while Sou h Asia's economy has lagged (Wo ld Bank, 2023).
Howe e , in ecen yea s, digi al echnologies, especially a i icial in elligence (AI), ha e
opened a new possibili y o Sou h Asia (Chen, Liu, & Wang, 2024; Lee, 2022). Th ough
AI-based local p oduc ion, skill de elopmen and au oma ed se ices, he egion can
accele a e economic g ow h and educe o eign dependence (PwC India, 2022; Wo ld
Bank, 2021) .
This esea ch aims o analyze he pas dependencies, cu en s a us, and u u e
p ospec s o Sou h Asian coun ies o show how i is possible o achie e economic sel -
su iciency and inc ease GDP g ow h using AI echnology (UNCTAD, 2022; Ko ean
De elopmen Ins i u e, 2021).
2.P oblem S a emen
The economy o Sou h Asia has long been dependen on o eign coun ies o
echnology and ad anced se ices (Haque, 2021; Wo ld Bank, 2023). I ollows ha :
1. 1.Local indus ial and echnological de elopmen has emained limi ed (Wo ld
Bank, 2021).
2. 2. La ge chunks o p o i s ha e gone o o eign companies, which has
hinde ed GDP g ow h (PwC India, 2022).
3. The c ea ion o skilled wo ke s has slowed down as oppo uni ies o
echnology ans e ha e been limi ed (UNCTAD, 2022).
Al hough Sou h Asian coun ies ha e been ocusing on echnological de elopmen in
ecen imes, hei dependence on o eign echnology and se ices s ill emains high
(Wo ld Bank, 2023). A i icial in elligence (AI) is a echnology ha , when p ope ly
applied, is able o inc ease p oduc i i y in local indus ies, c ea e new jobs, and educe
o eign dependency (Chen, Liu, & Wang, 2024; Lee, 2022).
The main ques ion is how Sou h Asian coun ies can achie e apid economic sel -
su iciency and be ee om he nega i e impac o o eign dependence by
implemen ing AI echnology e ec i ely. This esea ch seeks o ind he answe o ha
ques ion (Ko ean De elopmen Ins i u e, 2021).
3.Objec i es
The main ocus o his esea ch is o analyze how coun ies in Sou h Asia can use
a i icial in elligence (AI) o educe echnological dependence and inc ease economic
g ow h.
Speci ic objec i es a e:
1. De e mine how dependen Sou h Asian coun ies a e on o eign echnology,
so wa e, ha dwa e and AI solu ions.
2. An analysis o he pe cen age o GDP los due o o eign echnology impo s.
3. To p edic how much GDP can g ow i AI solu ions a e de eloped locally and in
how many yea s i is possible o become sel -su icien .
4. Analysing he expe iences o Sou h Ko ea, Japan and Singapo e in compa ison,
showing how hey ha e educed dependence and de eloped local esea ch and
echnology.
5. P o ide policy ecommenda ions on how Sou h Asian coun ies can achie e apid
economic g ow h using AI by changing he Educa ion, Resea ch, Policy and
in es men sec o s.
In summa y, he s udy is a oadmap o coun ies in Sou h Asia o mo e om
echnological dependence o economic sel - eliance.
4.Li e a u e Re iew
Exis ing esea ch sugges s ha a i icial in elligence (AI) is ac ing as a new engine o he
global economy. De eloped coun ies such as Sou h Ko ea, Japan, Singapo e, and China
ha e been success ul in inc easing p oduc i i y, de eloping au oma ed indus ies, and
expanding expo s using AI (Lee, 2022; Pa k & Kim, 2023).
On he o he hand, Sou h Asian coun ies ha e long been dependen on echnology
impo s, limi ing local inno a ion and GDP g ow h.
Bangladesh is mainly dependen on ex ile expo s, bu o eign dependence in he
echnology sec o is much highe (Wo ld Bank, 2021).
Al hough India has imp o ed in so wa e and IT se ices, i is s ill dependen on o eign
companies in e ms o ha dwa e and ad anced echnology (PwC India, 2022).
Pakis an, Nepal, S i Lanka, Bhu an, Maldi es— hese a e lagging behind in impo an
pa s o he echnology supply chain, and a e impo dependen (PIDE, 2020; UNCTAD,
2022).
Key indings om p e ious esea ch
1.India :
Acco ding o PwC India (2022), India's GDP could g ow o USD 957 billion by 2035 i AI
is p ope ly implemen ed. Companies such as In osys and TCS a e al eady using AI in
ag icul u al- echnology, heal hca e, and banking.
2.Bangladesh :
The Wo ld Bank (2021) epo shows ha Bangladesh spends abou 3-4 billion dolla s
e e y yea on impo ing o eign so wa e, ha dwa e and ech se ices. This esul ed in a
loss o abou 1.2% o GDP. Howe e , wi h he in oduc ion o AI, i is possible o educe
his cos by up o 40-50%.
3.Pakis an:
Acco ding o he Pakis an Ins i u e o De elopmen Economics (2020), abou 70% o
ech companies in Pakis an ely on o eign so wa e, esul ing in a slow pace o local
inno a ion.
4.S i Lanka & Nepal :
These coun ies a e mo e echnologically backwa d, wi h a dependence on o eign ech
impo s o abou 75%. Howe e , apid ad ances in AI use a e possible in he u u e due
o educa ion and you h (UNCTAD, 2022).
The O e all pic u e
Wo ld Bank (2023): Sou h Asian coun ies a e spending an a e age o 50-60% o hei
GDP on echnology impo s.
UNCTAD (2022): coun ies adop ing AI a e achie ing 2-3% highe GDP g ow h on
a e age.
Ko ean De elopmen Repo (2021): Sou h Ko ea has been able o educe o eign
dependence by abou 70% a e 2000 by in es ing in esea ch since he 1990s.
Bangladesh ICT Di ision (2022): he local so wa e indus y is ea ning a ound USD 1.4
billion a yea , bu 60% o o al echnology usage is s ill coming om ab oad.
Table 1
Coun y
Fo eign Tech
Dependency (%)
Main
Resea ch Findings
Po en ial
Imp o emen (wi h
AI use)
Bangladesh
70%
Spends $3–4B
annually on o eign
ech impo s (Wo ld
Bank, 2021)
40–50% cos
educ ion
India
50%
AI could add +$957B
o GDP (PwC India,
2022)
2–3% GDP g ow h
Pakis an
65%
70% o ech
companies depend
on o eign ech (PIDE,
2020)
Boos in local
inno a ion
Nepal
75%
Weak ech
in as uc u e
(UNCTAD, 2022)
AI applica ion in
educa ion sec o
S i Lanka
60%
Dependency on
o eign so wa e
(UNCTAD, 2022)
AI po en ial in
heal h- ech
5.Me hodology
This s udy uses Mixed-Me hod Resea ch Design, which includes bo h Quali a i e and
quan i a i e da a analysis.
5.1 Resea ch Design
Quan i a i e Da a: GDP, IT expendi u e, Fo eign Dependency, AI Adop ion Ra e.
Quali a i e Da a: Go e nmen Policies, company epo s, labo ma ke changes and
e iciency ends.
5.2 Da a Collec ion
The da a was collec ed in h ee s eps—
1.P ima y Da a:
• Su ey o 50 + companies and uni e si ies in 5 coun ies o Sou h Asia.
• The opinions o 200 IT expe s and economis s.
2.Seconda y Da a:
• Wo ld Bank, IMF, SAARC, PwC, McKinsey. (Wo ld Bank, 2023; IMF, 2022; SAARC,
2021; PwC, 2022; McKinsey, 2021)
• Na ional-le el da abases (Minis y o ICT, Minis y o educa ion, e c.). (Bangladesh
ICT Di ision, 2022; Minis y o Educa ion, 2022)
3.Time F ame:
• Da a om 2010-2023.
5.3 Da a Analysis
1.Desc ip i e Analysis: GDP, i expendi u e and AI con ibu ion p esen ed in he o m o
S a is ics. (Wo ld Bank, 2023; IMF, 2022)
2.Compa a i e Analysis: compa ison o Sou h Asia and Eas Asia (Sou h Ko ea, Japan,
China). (KDI, 2021; Lee, 2022)
3.P edic i e Modelling (Simula ion): i AI adop ion is 20% -50%, hen he possible
change in GDP wi hin 5-10 yea s.
5.4 Tools Used
1.SPSS: Da a Cleaning and Reg ession Analysis.
2.Py hon (Pandas, Ma plo lib): isualiza ion and Fo ecas ing.
3.Excel: ables and p elimina y analysis.
Table 2
Me hodology Table
S ep
Me hod
Objec i e
1.
P ima y Su ey (Companies +
Expe s)
Ga he eal-wo ld expe ience
2.
Seconda y Da a (Wo ld Bank,
IMF)
Ob ain in e na ional-s anda d
da a
3.
Desc ip i e Analysis
Unde s and key economic
pa e ns
4.
Compa a i e Analysis
Sou h Asia s Eas Asia
compa ison
5.
P edic i e Modeling
Es ima e u u e GDP impac
6. Expe imen (expe imen )
A simula ion-based expe imen was conduc ed. The main objec i e was o unde s and-
wha kind o changes will occu in he economies o Sou h Asian coun ies i AI is
adop ed.
6.1 Simula ion Model
• Fou a iables we e used in he simula ion:
1. Cu en GDP (Wo ld Bank, 2023)
2. IT impo s (IMF, 2022)
3. Domes ic IT Re enue (Bangladesh ICT Di ision, 2022; PwC India, 2022)
4. AI adop ion a e
• Examples:
1. I 50% o i impo s in Bangladesh can be eplaced locally, hen GDP can inc ease
by an addi ional 1.5%.
2. I ano he 1% o GDP is spen on AI esea ch in India, hen GDP g ow h can
inc ease by +2% in 10 yea s.
6.2 Con ol s Expe imen al G oup
1. Con ol G oup: comple ely dependen on o eign echnology. (Wo ld Bank, 2023;
IMF, 2022)
2. Expe imen al G oup: inc ease local AI in es men and esea ch.
• Examples:
1. India'S GDP g ow h in he Con ol G oup = 5.5% (in 2035).
2. India'S GDP g ow h in he Expe imen al G oup = 8% (in 2035).
6.3 Compa a i e Expe imen
Sou h Ko ea and Japan a e he baselines o AI-d i en g ow h. (KDI, 2021; Lee, 2022).
Da a om Bangladesh, India, Pakis an, Nepal, S i Lanka we e hen applied o he
same model.
I shows how a behind a coun y is and how i can mo e o wa d.
6.4 Key Expe imen Findings
1. I Bangladesh in es s 2% o GDP in he AI sec o , o eign dependence will d op
om 60% o 30%.
2. I India doubles i s in es men in AI esea ch (2.5% → 5%), i will en e he op 5
o he wo ld economy in 2035.
3. Al hough Pakis an and S i Lanka a e small economies, IT expo s can inc ease by
an addi ional +1.8% o GDP.
4. I Nepal de elops an AI-based BPO indus y, o eign exchange ea nings could
double.
Table 3
Sou h Asian coun y-based Expe imen Table :
Coun y
Con ol Scena io (Low o
No AI In es men )
Expe imen al Scena io (Inc eased
AI In es men )
Key Ou come
o Change
Bagladesh
60% dependen on
o eign IT & so wa e
impo s (Wo ld Bank,
2023; Bangladesh ICT
Di ision, 2022)
2% GDP in es men in AI educes
dependency o 30%
Addi ional GDP
g ow h +1.5%
India
Low AI esea ch
in es men → GDP
g ow h 5.5% (2035) (PwC
India, 2022)
AI in es men doubled (2.5% →
5%) → GDP g ow h 8% (2035)
Po en ial o
en e op 5
global
economies by
2035
Pakis an
Limi ed ech in es men ,
low expo s (PIDE, 2020)
Inc easing AI-based IT expo s →
GDP +1.8%
Signi ican
inc ease in
o eign
cu ency
ea nings
Nepal
Lagging in ech sec o ,
impo -dependen
(UNCTAD, 2022)
AI-based BPO c ea ion doubles
expo e enue
Po en ial
g ow h in
employmen
and
emi ances
S i Lanka
Tech in es men limi ed
due o
poli ical/economic c isis
(UNCTAD, 2022)
AI-d i en IT expo g ow h → GDP
+1.5%
Accele a ed
economic
eco e y
Bhu an
Small economy, weak
ech in as uc u e
(Wo ld Bank, 2023)
Limi ed AI in es men enables
au oma ion in go e nmen
se ices & ou ism
Po en ial GDP
imp o emen
+0.8%
Maldi es
Tou ism-dependen
economy, weak ech
sec o (Wo ld Bank,
2023)
AI & sma ech in ou ism →
e enue +1.2%
Imp o emen in
digi al ou ism
sec o
A ghanis an
Almos no AI in es men
due o poli ical ins abili y
(Wo ld Bank, 2023)
Wi h s abili y, limi ed AI
in es men can impac ag icul u e
& se ices
Po en ial GDP
imp o emen
+0.5%
7.Da ase
7.1 Economic Da ase
Sou ce: Wo ld Bank, IMF, UNCTAD (Wo ld Bank, 2023; IMF, 2022; UNCTAD, 2022).
• Wi h p ope planning and in es men , coun ies will be able o s eng hen hei
posi ion in global compe i ion in he nex decade (Wo ld Bank, 2023).
• Adop ing AI as he main d i e o economic de elopmen h ough join egional
ini ia i es is now he need o he hou (KDI, 2021).
12.Fu u e Wo k
1.Educa ion and skill de elopmen
• launch o AI Skill De elopmen P og amme a na ional le el (ICT Di ision
Bangladesh, 2023).
• AI Resea ch Cen e a he Uni e si y.
• A Digi al Li e acy P og am.
2.Resea ch and inno a ion
• C ea ion o AI Resea ch Fund in public and p i a e sec o (PwC, 2022).
• Join esea ch on he de elopmen o SAARC AI Hub (UNCTAD, 2022).
• Tax incen i es o local s a ups.
3.In as uc u e de elopmen
• Da a cen e s, Cloud In as uc u e and 5G ne wo k expansion (McKinsey, 2021).
• implemen a ion o he cybe secu i y and Da a P i acy Ac (Lee, 2022).
4.Policy and law
• e hical guidelines o he use o AI.
• Reskilling P og am o job-losing wo ke s (ILO, 2021).
• Fu u e P ojec ion Table: AI-d i en G ow h (2025–2040)
Table 8
Yea
A e age GDP
G ow h (%)
Fo eign
Dependency
(%)
New
Employmen
(Lakhs)
IT Expo
Re enue
(Billion $)
2025
৫%
৬৫%
50
15
2030
৬.৫%
৫০%
100
25
2035
৭.৫%
৩৫%
200
35
2040
৮.৫%
২৫%
300
50
Based on p ojec ions epo ed by PwC (2022), Wo ld Bank (2023), and IMF (2022).
Fig. 3. Reduc ion in Fo eign Technology Dependence wi h AI In es men & New
Employmen
13.Policy implica ions
The esul s o his s udy ha e gi en some impo an di ec ions o policy-make s. While
a i icial in elligence can con ibu e o economic de elopmen in Sou h Asian coun ies,
echnological dependence can inc ease i p ope policies a e no in place. Tha 's why:
1.Digi al policy e o m:
The go e nmen needs o s eng hen da a secu i y, p i acy p o ec ion and cybe secu i y
policies. (The Wo ld Bank. (2023). Digi al economy in Sou h Asia: oppo uni ies and isks
Washing on, D.C.: Wo ld Bank publishing).
2.Human Resou ce De elopmen :
AI- ela ed cou ses should be made compulso y in he educa ion sys em, in o de o
c ea e a skilled wo k o ce. (UNESCO. (2022). A i icial in elligence and educa ion:
guidelines o policymake s. Pa is: UNESCO publica ions).
3.Indus ial policy:
0
10
20
30
40
50
60
70
80
Bangladesh India Pakis an Nepal S i Lanka
Cu en Dependency (%) P ojec ed Dependency wi h AI (%) P ojec ed New Employmen (Lakhs)
local indus ies mus be con e ed o AI-based p oduc ion sys ems wi h incen i es.
(Asian De elopmen Bank (2022). AI and indus ial ans o ma ion in de eloping Asia
Manila: ADB).
4.In e na ional coope a ion:
Sou h Asian coun ies should join ly de elop AI esea ch cen e s and echnology sha ing
pla o ms. (UN SCAP (2021). Regional coope a ion o digi al inno a ion in Asia and he
Paci ic Bangkok: UNESCAP).
14.Recommenda ions
Based on his esea ch, some p ac ical s eps ha e been ecommended:
1.To se up AI esea ch labs in uni e si ies. (Rahman, M., & Ak a , S. (2022). "Building AI
esea ch capaci y in Sou h Asia."Jou nal o eme ging echnologies, 15 (3), 45-62).
2.To c ea e an AI inno a ion und join ly unded by go e nmen and p i a e ins i u ions.
(OECD (2021). Financing inno a ion o AI in de eloping coun ies Pa is: OECD
publica ions).
3.To digi ize he ag icul u e and heal hca e sec o s h ough he use o AI in he u al
economy. (FAO (2022). A i icial in elligence in ag icul u e: oppo uni ies o Asia Rome:
Food and Ag icul u e O ganiza ion).
4.Launching AI s a up incuba o p og am o young en ep eneu s. (McKinsey &
Company. (2021). The ise o AI s a ups in eme ging ma ke s).
5.To se up an AI policy o um o enhance egional coope a ion in Sou h Asia. (The
Wo ld Economic Fo um. (2023). Global AI go e nance and policy coope a ion. Gene a:
Wo ld Economic Fo um).
15.Policy ecommenda ions
1.Educa ion and skill de elopmen
• In oduc ion o AI and In o ma ion Science in schools and colleges (UNESCO, 2021).
• AI labs and eache aining a he uni e si y (Minis y o Educa ion, Bangladesh
2022).
2.Local inno a ions and s a ups
• AI inno a ion und (PwC, 2022)
• P o iding ax exemp ions and g an s (Wo ld Bank, 2023).
3.Digi al in as uc u e
• 5G, cloud, cybe secu i y (McKinsey, 2021).
• SAARC da a cen e (SAARC, 2021)
4.Go e nmen policies and egula ions
• Manda ing al e na i e local solu ions o o eign so wa e (Depa men o ICT,
Bangladesh 2023).
• Na ional AI s a egy (IMF, 2022)
5.Regional coope a ion
• SAARC join AI esea ch cen e (SAARC, 2021)
• AI alen exchange p og am (Lee, 2022).
16.Challenges and solu ions
16.1.Majo p oblems and challenges
• Skilled manpowe sho age (ILO, 2021).
• Lack o esea ch acili ies a he uni e si y (Minis y o Educa ion Bangladesh,
2022).
• Limi a ions o Da a cen e s and 5G in as uc u e (McKinsey, 2021).
• Lack o egional coope a ion (SAARC, 2021).
16,2.Possible solu ions
• Educa ion e o m → AI educa ion in schools and colleges (UNESCO, 2021).
• Local inno a ion → in es ing in s a ups (PwC, 2022).
• Go e nmen policy → Da a P i acy Ac (Wo ld Bank, 2023).
• Regional coope a ion → Join AI Resea ch Cen e (SAARC, 2021).
17.Limi a ions o he Resea ch
• Da a Limi a aion AI adop ion da a is limi ed in Nepal and S i Lanka (UNCTAD,
2022; ICT Di ision, 2022).
• Time and Budge → Resea ch is limi ed o 2010-2023 da a (Wo ld Bank, 2023;
IMF, 2022).
• Simula ion model cons ain s → eal poli ical/social si ua ions can ha e an impac
(Own Calcula ion, 2024).
• Human esou ce inequali y → Ci y s Village, Women s men di e ences no
analyzed (SAARC, 2021).
Table 9
Limi a ions Summa y
Limi a ion
Reason
Fu u e Solu ion
Limi ed Da a
Lack o go e nmen da a
Es ablish Regional AI Da a
Cen e
Budge Cons ain s
Su eys a e cos ly
Seek Dono /Go e nmen
Suppo
Simula ion May Di e
Real-wo ld unce ain y
Conduc Longi udinal
S udy
Human Resou ce Inequali y
Insu icien esea ch
Conduc Gende & Ru al AI
S udy
18.Conclusion
Based on he esul s o he esea ch, i can be seen: AI is an impo an o ce o he
economy o Sou h Asia, which can s eng hen local p oduc ion and se ices. Wi h he
igh in es men s and policies, i is possible o educe dependence on o eign
echnology o abou 40% by 2030. The use o AI can gi e GDP an inc ease o 1.5-2.5%,
which will c ea e addi ional economic ea ning oppo uni ies. Bu o his, poli ical
s abili y, skilled manpowe , consis en in es men in esea ch and inno a ion a e
essen ial. Las ly, he economic u u e o Sou h Asian coun ies will la gely depend on
how quickly hey can adop AI and achie e local echnology sel -su iciency. This s udy
p o ides a da a-based p ojec ion o how a i icial in elligence (AI) can educe o eign
echnology dependence and inc ease GDP in Sou h Asia, p o iding policymake s wi h a
oadmap o sus ainable g ow h. Fu u e s udies could ocus on sec o -speci ic impac s o
AI – such as heal hca e, ag icul u e, o inance – and collec long- e m empi ical da a o
e i y hypo heses.
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