Chino acky, Roman; S almaseko a, Na alia; Madlenak, Rado an; Madlenako a,
Lucia
A icle
A e na ions eady o digi al ans o ma ion? A
mac oeconomic pe spec i e h ough he lens o educa ion
quali y
Economies
P o ided in Coope a ion wi h:
MDPI – Mul idisciplina y Digi al Publishing Ins i u e, Basel
Sugges ed Ci a ion: Chino acky, Roman; S almaseko a, Na alia; Madlenak, Rado an; Madlenako a,
Lucia (2025) : A e na ions eady o digi al ans o ma ion? A mac oeconomic pe spec i e h ough
he lens o educa ion quali y, Economies, ISSN 2227-7099, MDPI, Basel, Vol. 13, Iss. 6, pp. 1-22,
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Ci a ion: Chino acky, R.,
S almaseko a, N., Madlenak, R., &
Madlenako a, L. (2025). A e Na ions
Ready o Digi al T ans o ma ion?
A Mac oeconomic Pe spec i e
Th ough he Lens o Educa ion
Quali y. Economies,13(6), 152. h ps://
doi.o g/10.3390/economies13060152
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A icle
A e Na ions Ready o Digi al T ans o ma ion?
A Mac oeconomic Pe spec i e Th ough he Lens o
Educa ion Quali y
Roman Chino acky, Na alia S almaseko a , Rado an Madlenak * and Lucia Madlenako a
Facul y o Ope a ion and Economics o T anspo and Communica ions, Uni e si y o Zilina, Uni e zi ná 8215/1,
010 26 Žilina, Slo akia; [email p o ec ed] (R.C.); [email p o ec ed] (N.S.);
[email p o ec ed] (L.M.)
*Co espondence: [email p o ec ed]
Abs ac : The global shi owa d digi al ans o ma ion p esen s bo h oppo uni ies and
challenges o na ional economies, pa icula ly in e ms o wo k o ce eadiness. While
many s udies assess digi al eadiness ia in as uc u e o echnological adop ion, ewe
in es iga e he p epa edness o coun ies’ u u e labo o ces. This a icle add esses his
esea ch gap by examining how quali y o educa ion ela es o job au oma ion isk ac oss
OECD coun ies. The goal is o iden i y which na ions a e leas p epa ed o digi al
dis up ion due o weak educa ional ounda ions and high au oma ion exposu e. Using
da a on educa ion expendi u e, PISA sco es, and he Educa ion Index, compa ed o he
pe cen age o jobs a high isk o au oma ion, his s udy applies co ela ional analysis
and a quad an o e iew o assess na ional eadiness. Findings show ha coun ies
such as Slo akia, Poland, and G eece a e leas p epa ed, combining low in es men in
educa ion and high exposu e o au oma ion. Con e sely, na ions like Finland, No way,
Sweden, and New Zealand exhibi s ong eadiness, cha ac e ized by obus educa ion
sys ems and lowe au oma ion isks. This s udy con ibu es o he li e a u e by in eg a ing
au oma ion ulne abili y in o na ional eadiness assessmen s and o e s ac ionable insigh s
o policymake s ocused on educa ion e o m and wo k o ce de elopmen .
Keywo ds: digi aliza ion; job au oma ion; educa ion; echnological change
1. In oduc ion
Digi al ans o ma ion— he widesp ead adop ion o digi al echnologies—has eme ged
as a de ining end o he 21s cen u y. I is undamen ally al e ing how indi iduals li e and
wo k, businesses ope a e, and how go e nmen s deli e se ices (Mikale & Pa miggiani,
2022;Ve hoe e al.,2021). The impo ance o s udying coun ies’ eadiness o digi al
ans o ma ion lies in he p o ound economic and social implica ions o his shi . Na ions
ha e ec i ely ha ness digi aliza ion can achie e highe p oduc i i y, inno a ion, and
compe i i eness, whe eas hose ha lag isk widening de elopmen gaps and losing ou
on g ow h oppo uni ies. As digi al ools become ubiqui ous, coun ies mus be p epa ed
o in eg a e hese ools in o hei indus ies. Unde s anding which coun ies a e eady (and
which a e no ) is c i ical o in e na ional de elopmen and policy making, as digi al ans-
o ma ion is now closely linked o economic p ospe i y and social well-being (Co ejo a &
Chino acky,2021;A ıkan Ka gı,2022;Cisco Sys ems,2019;OECD,2019b;Aleksand o a
e al.,2022;Tudose e al.,2023).
Economies 2025,13, 152 h ps://doi.o g/10.3390/economies13060152
Economies 2025,13, 152 2 o 22
A key insigh om compa a i e s udies is ha mul iple ac o s in luence a coun y’s
digi al ans o ma ion eadiness, cu ing ac oss echnology, human capi al, go e nance, and
economic condi ions. Robus ICT in as uc u e is a ounda ional equi emen —widesp ead
in e ne access, eliable elec ici y, and mode n elecommunica ions ne wo ks enable digi al
connec i i y. Equally impo an is human capi al, including educa ion quali y and digi al
skills in he wo k o ce, since people mus be able o use and de elop new echnologies. The
business en i onmen and in es men clima e shape how eadily i ms can adop digi al
inno a ion; ac o s such as R&D expendi u e, en ep eneu ship, and ease o doing business
all con ibu e o eadiness o digi al ans o ma ion (Cisco Sys ems,2019). E ec i e go e n-
men policies and ins i u ions— om na ional digi al s a egies and e-go e nmen se ices
o legal amewo ks o da a and in ellec ual p ope y—c ea e an enabling en i onmen o
digi al ans o ma ion. As he Uni ed Na ions De elopmen P og amme no es, an inclusi e
digi al ans o ma ion equi es coo dina ed e o s ac oss i e pilla s: people, connec i i y,
go e nmen , egula ion, and economy (Uni ed Na ions De elopmen P og amme [UNDP],
2023). In sum, eadiness is mul idimensional, e lec ing a coun y’s echnical capaci y, skill
base, and policy suppo o le e aging digi al echnology.
Wi hin his con ex , an impo an and unde -examined ques ion ises: Which coun ies
a e leas p epa ed o he changes b ough abou by digi aliza ion, based on he po en ial
o hei u u e wo k o ce? The “ u u e wo k o ce” e e s o he upcoming gene a ion
o wo ke s— oday’s s uden s and young people—who will d i e and sus ain digi al
ans o ma ion in he yea s ahead.
This aspec is especially c i ical because e en i a coun y builds in as uc u e, i
canno ully bene i om digi aliza ion wi hou a skilled wo k o ce o use and inno a e
on hose echnologies. Coun ies wi h a well-educa ed, adap able you h popula ion may
leap og in eadiness despi e lowe income le els (A n z e al.,2016;OECD,2022;Wo ld
Economic Fo um,2024;Uni ed Na ions De elopmen P og amme [UNDP],2023). Ye ,
ela i ely ew s udies ha e explici ly ocused on he in e sec ion o wo k o ce de elopmen
and na ional digi al eadiness. Many exis ing indices emphasize cu en in as uc u e
o ins i u ional me ics, while gi ing less a en ion o whe he he educa ional sys em
and labo o ce a e equipped o apid echnological change. This is a no able esea ch
gap: o ins ance, global assessmen s ha e poin ed ou ha low-skilled and low-educa ed
wo ke s a e he mos ulne able o job au oma ion, and ha wi hou su icien e aining,
coun ies will ace ising inequali y as au oma ion accele a es (A n z e al.,2016). E en
high-skilled wo ke s a e no immune— ecen e idence shows ha non- ou ine analy ical
asks pe o med by highly educa ed p o essionals a e inc easingly suscep ible o AI-d i en
au oma ion, wi h signi ican a ia ion in wage ou comes and job edesign implica ions
(Ozgul e al.,2024;OECD,2022). T ansla ing his insigh in o a coun y-le el eadiness
pe spec i e—iden i ying which coun ies’ u u e labo wo k o ce ace he g ea es isk—
emains an open challenge.
This a icle add esses his gap by examining global digi al ans o ma ion eadiness
h ough he lens o wo k o ce educa ion and au oma ion isk. In pa icula , i in es iga es
which coun ies appea al eady p epa ed and leas p epa ed o digi al dis up ion due o
limi a ions in hei u u e wo k o ce’s skills and he suscep ibili y o hei jobs o au oma ion.
This ocus on he human capi al dimension complemen s p io wo k and is c ucial o
policymake s: i a coun y’s nex -gene a ion wo k o ce lacks digi al skills, o i a la ge
sha e o i s jobs a e poised o be eplaced by echnology, hen ha coun y’s digi al u u e
is unce ain despi e o he a o able ac o s. Iden i ying such na ions can in o m a ge ed
in e en ions (such as educa ional e o ms, upskilling p og ams, o labo ma ke policies)
o suppo p epa edness o he coming wa e o digi aliza ion.
Economies 2025,13, 152 3 o 22
The emainde o his a icle is o ganized as ollows: i s , we p esen a e iew o he
ele an li e a u e, cla i ying key concep s (digi iza ion s. digi al ans o ma ion), he
economic bene i s o digi aliza ion, he concep o na ional eadiness and i s d i e s, and
p io indings on wo k o ce eadiness and au oma ion. We hen ou line he esea ch gap
and con ibu ion o his s udy in de ail, be o e p oceeding o he me hodological app oach
and analysis ha add ess he esea ch ques ion. The las pa o he a icle is dedica ed o
a discussion and conclusion. Sec ion 5sums up he esea ch and subsequen ly poin s o
he policy implica ions. Sec ion 6ou lines esea ch limi a ions and lis s oppo uni ies o
u u e esea ch.
2. Li e a u e Re iew
Robe Wachal, in his essay add essing he social consequences o socie al changes
in he con ex o e alua ing he po en ial o compu e -based esea ch in he humani ies,
was he i s o use he e m digi aliza ion (Wachal,1971). The e m digi aliza ion is o en
inco ec ly con used wi h he e m digi iza ion. While digi iza ion is he con e sion o
in o ma ion lows om analogue o digi al in a o m o a combina ion o ze os and ones
wi hin one p ocess, digi aliza ion is he con e sion o all in o ma ion lows wi hin he
en i e p ocess. Digi aliza ion simply e e s o he use and implemen a ion o speci ic digi al
echnology by a company, an en i e indus y, o e en socie y as a whole wi hin he scope o
a single p ojec (Mikale & Pa miggiani,2022;Wachal,1971;B ennen & K eiss,2016).
A company may ca y ou a se ies o p ojec s aimed a digi aliza ion: om he au-
oma ion o p oduc ion p ocesses, he implemen a ion o in o ma ion sys ems managing
a ious elemen s o supply chains, o he c ea ion o ecomme ce pla o ms and he aining
o employees o wo k wi h a i icial in elligence. The se o such digi aliza ion p ojec s is
collec i ely e e ed o as digi al ans o ma ion, which is a s a egic ans o ma ion based
no only on he implemen a ion o digi al echnologies, bu also on changes in co po a e
cul u e, c oss-o ganiza ional shi s, and adjus men s in business models (Vial,2019;V ana
& Singh,2021).
Digi iza ion is abou bi s and by es—con e ing analog o digi al. Digi aliza ion is
abou p ocesses—using digi al echnologies o do wha we al eady do, bu be e . Digi al
ans o ma ion is abou s a egy and pa adigm shi s—doing wha we ne e could be o e,
o doing undamen ally new hings, enabled by digi al echnology (Mikale & Pa miggiani,
2022;Wachal,1971;B ennen & K eiss,2016;Vial,2019;V ana & Singh,2021).
A he na ional le el, a coun y may s a by building in e ne in as uc u e (digi iza-
ion), hen p omo e online se ices and e-comme ce (digi aliza ion), and e en ually see i s
economy ans o med wi h new digi al indus ies and inno a ions (digi al ans o ma ion).
Cla i ying hese e ms is no jus seman ic, i helps in scoping wha “ eadiness” en ails.
A coun y migh be well-equipped o digi iza ion (e.g., ha ing he ha dwa e o con e
analog sys ems) bu no ye eady o deepe digi al ans o ma ion (which equi es alen ,
inno a ion ecosys ems, and adap able ins i u ions) (Sch eckling & S eige ,2017). Thus,
in assessing eadiness, we mus conside no only echnology deploymen bu also he
capaci y o s a egic, ans o ma i e change.
Digi al ans o ma ion is widely seen as a posi i e o ce o economic de elopmen . Fo
example, i ms ha digi alize hei ope a ions ( h ough en e p ise so wa e, au oma ion, AI,
and so o h) can p oduce mo e wi h he same inpu s, inno a e as e , and se e cus ome s
in new ways, he eby expanding hei ma ke sha e and p o i abili y.
On a la ge scale, when many i ms in an economy become mo e p oduc i e hanks
o digi al ools, he agg ega e economic ou pu (GDP) o ha coun y is expec ed o ise.
Empi ical esea ch suppo s hese expec a ions:
Economies 2025,13, 152 4 o 22
•
A c oss-coun y econome ic analysis by Tudose e al. (2023) inds ha highe digi al
eadiness co ela es wi h highe GDP pe capi a. Using he Ne wo k Readiness Index
(NRI) as a measu e o na ions’ digi al ans o ma ion s a us, hey show ha he NRI
has a posi i e and signi ican impac on GDP pe capi a ac oss a sample o 46 coun ies.
In o he wo ds, coun ies ha sco e be e on in as uc u e, echnology adop ion,
skills, and o he digi al c i e ia end o enjoy s onge economic pe o mance, e en
a e con olling o hei income g oup. This sugges s ha digi al ans o ma ion is a
d i e o g ow h: be e ne wo ked, mo e digi al-sa y economies can p oduce mo e
goods and se ices o highe - alue ou pu s, boos ing a e age incomes (Tudose e al.,
2023;Du a & Lan in,2023).
•
Simila ly, Cisco’s global digi al eadiness s udy epo ed a s ong ela ionship be ween
digi al eadiness and GDP pe capi a, unde sco ing ha in es ing in digi al capaci y
yields angible economic alue. One eason is ha digi aliza ion can spu inno a ion
and en ep eneu ship, c ea ing en i ely new indus ies (such as in ech, e-comme ce,
digi al en e ainmen ) and job oppo uni ies ha did no exis be o e. Fo example,
he ise o he mobile app economy o digi al con en c ea ion has con ibu ed sig-
ni ican ly o employmen and GDP in coun ies ha ha e emb aced hese ends
(Cisco Sys ems,2019).
•
F om he pe spec i e o wo k- ela ed p ocesses, ou ine asks can be au oma ed,
educing labo cos s o eeing wo ke s o highe - alue ac i i ies; supply chains can
be synch onized in eal ime, minimizing in en o ies and down ime; and da a analy ics
can op imize e e y hing om ene gy use o ma ke ing s a egies. His o ical e idence
shows ha majo echnological adop ions—s eam powe , elec ici y, e c.—boos ed
p oduc i i y, and digi al echnology is no excep ion (Co ejo a & Chino acky,2021).
Co ejo a and Chino acky (2021) u he no e ha he e ec s o digi al echnologies a e
associa ed wi h g ow h in e iciency and ou pu , o en leading o inc eased e enues
and p o i s o businesses ha success ully in eg a e hem.
Digi al ans o ma ion also ends o enhance a coun y’s compe i i eness and e iciency
in global ma ke s. By adop ing ad anced echnologies (like obo ics in manu ac u ing
o digi al inance in banking), coun ies can inc ease he p oduc i i y o hei indus ies,
making hei expo s mo e compe i i e. I enables cos educ ions and quali y imp o e-
men s ha can expand a na ion’s ade po en ial. Digi aliza ion o en imp o es se ice
deli e y in bo h p i a e and public sec o s, which can aise he o e all p oduc i i y o
he economy. Fo example, digi al banking and e-paymen s make inancial ansac ions
as e and mo e secu e, suppo ing comme ce; e-go e nmen se ices educe bu eauc a ic
hu dles, sa ing ime o businesses and ci izens. These e iciency gains collec i ely imp o e
wha economis s call o al ac o p oduc i i y, a key ing edien o long- e m g ow h (A ıkan
Ka gı,2022;Tudose e al.,2023). The OECD and Wo ld Bank ha e documen ed ha digi al
adop ion boos s p oduc i i y and g ow h, pa icula ly when combined wi h complemen-
a y in es men s in skills and o ganiza ional change (OECD,2019a;Cusoli o e al.,2020).
Ano he bene i o digi al ans o ma ion is he po en ial o inclusi e g ow h, hough
his is no au oma ic. Digi al pla o ms can empowe small en ep eneu s o each wide
ma ke s ( hink o a isans selling on global e-comme ce pla o ms) and can p o ide new
job oppo uni ies such as gig wo k o IT-enabled se ices in egions whe e o mal jobs a e
sca ce. This means ha digi al echnologies can help o e come geog aphic ba ie s— o
ins ance, allowing emo e educa ion and elemedicine in u al a eas— he eby con ibu ing
o human capi al de elopmen and heal h, which eed back in o economic g ow h. (Alek-
sand o a e al.,2022) A s udy by Sun so a (2024), on he global digi al economy, a gued
ha while digi aliza ion is a “ wo-edged swo d”, he oppo uni ies o economic g ow h,
inno a ion, and imp o ed se ices a e signi ican i managed well. Howe e , i mus be
Economies 2025,13, 152 5 o 22
no ed ha he bene i s o digi al ans o ma ion can be une en i pa s o he popula ion o
ce ain egions a e le behind; hence, many schola s and in e na ional o ganiza ions s ess
he need o policies o b idge he digi al di ide so ha he gains om digi aliza ion a e
b oadly sha ed (Sun so a,2024).
In summa y, digi al ans o ma ion can d i e a coun y’s economy o wa d by inc eas-
ing p oduc i i y, os e ing inno a ion, c ea ing new ma ke s and indus ies, and imp o ing
e iciency in exis ing sec o s. Coun ies ha success ully emb ace digi aliza ion o en ex-
pe ience as e economic g ow h and imp o ed compe i i eness. Fo example, Es onia’s
economy has bene i ed om i s ea ly adop ion o e-go e nmen and digi al se ices (o en
ci ed as “e-Es onia”) (Vassil,2015;e-Es onia,2022), and China’s apid digi al economy
expansion (e.g., in e-comme ce and in ech) has con ibu ed o i s GDP g ow h and global
ade p esence (McKinsey & Company,2021;ING Think,2022). These examples illus a e
he gene al inding ha digi al eadiness is ied o economic pe o mance. Howe e , ealiz-
ing hese bene i s is con ingen on ha ing he necessa y condi ions in place—which b ings
us o he concep o digi al ans o ma ion eadiness a he na ional le el.
Readiness o digi al ans o ma ion a he na ional economic le el e e s o a coun y’s
capaci y o adop , implemen , and le e age digi al echnologies o i s de elopmen and
g ow h. I is a holis ic concep ha encompasses he s a e o in as uc u e, human capi al,
ins i u ions, and o he ounda ional elemen s ha de e mine how well posi ioned a coun y
is o unde go digi al ans o ma ion. In simple e ms, a na ion ha is “digi ally eady” has
he p e equisi es needed o success ully in eg a e ad anced echnologies in o i s economy
and socie y, whe eas a less eady na ion aces signi ican gaps o ba ie s in doing so.
Se e al amewo ks and indices ha e been de eloped o measu e digi al eadiness ac oss
coun ies, including he ollowing:
•The Ne wo k Readiness Index (NRI) (Tudose e al.,2023;Du a & Lan in,2023),
•The IMD Wo ld Digi al Compe i i eness Ranking (IMD,2024),
•The Digi al Adop ion Index o he Wo ld Bank (Wo ld Bank,2016),
•Indus y-backed measu es like he Cisco Digi al Readiness Index (Cisco Sys ems,2019).
These ypically agg ega e a ious indica o s in o a composi e sco e mean o bench-
ma k coun ies’ digi al capabili ies. Common o hese assessmen s is he unde s anding
ha eadiness spans mul iple dimensions.
One use ul example is Cisco’s model, which uses se en componen s o gauge digi al
eadiness: (1) Basic Needs, (2) Business and Go e nmen In es men , (3) Ease o Doing
Business, (4) Human Capi al, (5) S a -up En i onmen , (6) Technology Adop ion, and
(7) Technology In as uc u e (A ıkan Ka gı,2022;Cisco Sys ems,2019):
•
The “Basic Needs” (1) componen acknowledges ha gene al socio-economic de elop-
men (heal h, educa ion, basic se ices) se s he s age—i basic needs a e no me , a
coun y will s uggle o ocus on digi al ad ancemen (A ıkan Ka gı,2022).
•
The “Technology Adop ion and In as uc u e” (6) (7) componen s measu e he a ail-
abili y o digi al ne wo ks (like b oadband and mobile) and he ex en o which people
and businesses a e ac ually using digi al se ices.
•
The “Human Capi al” (4) componen cap u es educa ion le els, digi al skills, and
labo o ce pa icipa ion, indica ing whe he he wo k o ce can suppo and sus ain
digi al ini ia i es.
•
The “Business en i onmen and go e nmen in es men ” (2) (3) (5) componen s e lec
whe he i ms ha e he eedom, incen i es, and suppo o inno a e and in es in
echnology ( o ins ance, ease o s a ing a business, R&D spending, en u e capi al a ail-
abili y). When all hese ac o s a e a o able, coun ies c ea e a i uous cycle ha a ac s
ech in es men and enables widesp ead ech adop ion, hus being highly “ eady”.
Economies 2025,13, 152 6 o 22
Apa om dimensions, he li e a u e iden i ies a b oad a ay o ac o s ha impac
hese dimensions. These ac o s a e o en in e linked and ein o ce one ano he . The ac o s
a e ca ego ized as ollows:
•
In as uc u e and Connec i i y: A undamen al equi emen o any digi al ac i i y
is physical and digi al in as uc u e. This includes elecommunica ions ne wo ks
(b oadband in e ne , mobile 4G/5G co e age, ibe op ic ne wo ks), da a cen e s and
cloud se ices, elec ici y supply, and access o de ices (sma phones, compu e s).
High-quali y, ubiqui ous connec i i y is consis en ly associa ed wi h g ea e digi al
up ake. Fo ins ance, he expansion o b oadband in as uc u e has been linked o
inc eases in economic g ow h and online business ac i i y (Rölle & Wa e man,2001).
Coun ies ha ha e in es ed in na ionwide high-speed in e ne (like Sou h Ko ea’s
ea ly adop ion o b oadband o Es onia’s public Wi-Fi and digi al ID sys em) enjoy a
head s a in digi al eadiness. In con as , in as uc u e gaps—whe he u al commu-
ni ies wi hou he in e ne o equen powe ou ages—se e ely hinde digi al p og ess.
Thus, me ics like in e ne pene a ion a e, b oadband speed, and ne wo k eliabili y
a e co e indica o s in eadiness indices (A ıkan Ka gı,2022;Cisco Sys ems,2019).
•
Human Capi al and Skills: A guably he mos c i ical ac o is he educa ion and skill
le el o he popula ion, pa icula ly he wo k o ce. Digi al ans o ma ion is no sel -
ac ing; i equi es people who can de elop, implemen , and u ilize new echnologies.
A coun y wi h a high le el o gene al educa ion, s ong STEM (science, echnology,
enginee ing, ma hema ics) aining, and widesp ead digi al li e acy will be a mo e
eady o inno a e and adap . Indica o s such as he li e acy a e, a e age yea s o
schooling, sha e o g adua es in STEM ields, and p o iciency in ICT skills a e eg-
ula ly used o e alua e his (A ıkan Ka gı,2022;Cisco Sys ems,2019). I is no jus
echnical skills—adap abili y, p oblem sol ing, and con inuous lea ning a e i al in
a as -changing digi al en i onmen . The Wo ld Economic Fo um o en emphasizes
“ eskilling and upskilling” he wo k o ce as a pilla o u u e eadiness (Wo ld Eco-
nomic Fo um,2024). Empi ical s udies ein o ce he impo ance o human capi al:
coun ies ha sco e highe on educa ion indices end o ha e g ea e echnology adop-
ion and inno a ion ou pu . Con e sely, na ions whe e la ge po ions o he wo k o ce
ha e low educa ional a ainmen may s uggle; indeed, esea ch on au oma ion isk
inds ha wo ke s wi h low educa ion ace g ea e h ea s om displacemen by
echnology, which can hampe a coun y’s o e all eadiness o ansi ion o a digi al
economy. A digi ally eady coun y in es s hea ily in i s people— h ough quali y
basic educa ion, digi al skills aining, oca ional IT p og ams, and li elong lea ning
(A n z e al.,2016).
•
Policy and Regula o y En i onmen : Go e nmen policies and he egula o y amewo k
can signi ican ly enable o impede digi al ans o ma ion. P oac i e go e nmen
in es men in digi aliza ion ( o example, unding b oadband ollou , sma ci y pilo s,
o R&D in ech) can jumps a p og ess (Digi al Regula ion P ojec ,2023). Clea and
o wa d-looking egula ions (such as da a p o ec ion laws, cybe secu i y amewo ks,
elec onic ansac ion laws) build us and s abili y, encou aging businesses and
consume s o pa icipa e in he digi al economy (Uni ed Na ions Capi al De elopmen
Fund,2023). Fo ins ance, a coun y ha quickly es ablishes a legal basis o in ech
and digi al paymen s may expe ience apid g ow h in hose se ices. On he o he
hand, unce ain egula ions can supp ess inno a ion. The p esence o a na ional digi al
s a egy o an e-go e nmen agenda also signals eadiness—many o he op- anked
coun ies ha e comp ehensi e plans (e.g., Singapo e’s Sma Na ion ini ia i e o he
EU’s Digi al Decade a ge s) (Go e nmen o Singapo e,2024;Eu opean Commission,
2021). Addi ionally, ease o doing business and go e nance quali y ma e : i i is
Economies 2025,13, 152 7 o 22
easie o s a a business, egis e in ellec ual p ope y, o engage in ade, hen digi al
en ep eneu s can lou ish (Beie e al.,2018). In summa y, an enabling ins i u ional
en i onmen —cha ac e ized by poli ical suppo o digi al ini ia i es, e ec i e public
adminis a ion, and inclusi e digi al policies—is a key ac o . This includes public-
sec o eadiness oo: go e nmen s ha hemsel es adop digi al ools ( o ax collec ion,
se ice deli e y, e c.) no only become mo e e icien bu also d i e demand o digi al
solu ions in socie y (Ha,2022;Lindg en e al.,2019).
•
Economic Fac o s and In es men Clima e: A coun y’s o e all economic de elopmen
and openness o in es men shape i s digi al eadiness. Weal hie coun ies na u ally
ha e mo e esou ces o in es in echnology and educa ion, bu beyond income, he
alloca ion o in es men ma e s. High R&D spending (public o p i a e), a ib an
s a -up ecosys em, and a ailabili y o en u e capi al o inancing o ech p ojec s
all con ibu e o eadiness (de Lucas Ancillo & Ga ila Ga ila,2023). Fo example,
Is ael’s s ong en u e capi al scene and go e nmen suppo ha e made i one o he
leading ech hubs ( he “S a up Na ion”) despi e i s small size (Seno & Singe ,2009).
T ade openness can acili a e access o new echnologies and expe ise om ab oad
(Ška e & Ribei o So iano,2021). A cul u e o inno a ion also plays a ole: socie ies
ha encou age expe imen a ion, en ep eneu ship, and ha e a ole ance o isk and
ailu e o en adap as e o echnological shi s (Bu e al.,2024). On he lip side,
coun ies wi h igid economic s uc u es, monopolis ic ma ke s, o low compe i ion
may see slowe digi al adop ion. The p esence o la ge ech companies o indus ies
can also help— o ins ance, Taiwan’s semiconduc o indus y o India’s IT se ices
sec o ha e spillo e e ec s on he coun y’s digi al capabili ies (Raj,2024;Chen &
Shih,2007). In essence, a dynamic economy ha in es s in u u e echnologies and
os e s business inno a ion will be mo e eady o ans o m digi ally.
•
Social and Cul u al Fac o s: These a e some imes less quan i ied bu s ill impo an .
Public a i udes owa ds echnology (e.g., us in digi al se ices, willingness o adop
new p oduc s) in luence up ake. In some coun ies, ea o job loss o p i acy conce ns
migh impede hings like AI o da a sha ing unless add essed. Demog aphics can
ma e oo—a younge popula ion migh be mo e ech-sa y and quick o emb ace
digi al li es yles, whe eas aging socie ies may ha e mo e di icul y e aining wo ke s
(Kise & Washing on,2015). Addi ionally, inequali y and he digi al di ide wi hin
a coun y a ec eadiness: i ce ain g oups ( u al, lowe income, women) ha e less
access o echnology o educa ion, ha coun y’s o e all eadiness is hampe ed by an
unde u ilized segmen o alen (Ba a e al.,2024). The e o e, inclusi e policies ha
b ing ma ginalized g oups in o he digi al old can imp o e a na ion’s eadiness p o ile.
These ac o s o en in e ac . Fo example, imp o ing b oadband in as uc u e ( ech-
nology ac o ) migh be o limi ed use i he educa ion sys em is no p oducing IT-p o icien
g adua es (human capi al ac o )—bo h need o p og ess in andem. Likewise, e en a
highly educa ed wo k o ce may inno a e elsewhe e i he domes ic business clima e is
poo (policy/economic ac o s). This sugges s ha ounda ional socio-economic de el-
opmen and p oac i e in es men s c ea e he e ile g ound upon which speci ic digi al
ad ancemen s g ow.
In p ac ice, coun ies need o add ess all hese a eas o a ying deg ees o boos hei
eadiness. Fo de eloping na ions, in e na ional o ganiza ions o en ecommend s a ing
wi h in as uc u e and skills (as basics) bu also mode nizing egula o y amewo ks o
no all behind. Fo ad anced na ions, he ocus migh be on on ie inno a ions and
con inuously upda ing skillse s h ough li elong lea ning. The li e a u e emphasizes ha
digi al eadiness is no a s a ic end-s a e bu a con inuous p ocess o capaci y building
(Uni ed Na ions De elopmen P og amme [UNDP],2023).
Economies 2025,13, 152 8 o 22
Policies such as imp o ing STEM educa ion, incen i izing ICT in as uc u e expan-
sion, ensu ing a o dable in e ne access, encou aging ech s a ups, and p o ec ing digi al
igh s a e all le e s o enhance eadiness. I hese policies a e neglec ed, i may e ol e in o
a key ba ie o p og ess. Fo ins ance, i a coun y ails o in es in educa ion, i may ace a
alen sho age ha lea es expensi e new in as uc u e unde u ilized.
The eadiness o a coun y’s u u e wo k o ce—essen ially he supply o young alen
and he adap abili y o i s labo o ce—is inc easingly iewed as a key d i e o digi al
ans o ma ion success. While esea ch, s udies and indices ha e measu ed na ions’ digi al
in as uc u e and cu en usage ex ensi ely, ewe ha e closely analyzed how he edu-
ca ion sys em and occupa ional s uc u e o a coun y p epa e i (o no ) o impending
digi al dis up ions.
Digi al ans o ma ion, especially in i s nex phase in ol ing a i icial in elligence and
obo ics, is expec ed o b ing abou subs an ial changes in he labo ma ke . Many asks
will be au oma ed, some jobs will decline, new jobs will eme ge, and almos all jobs will
equi e a highe baseline o digi al compe ency. The e o e, a coun y’s capaci y o educa e,
ain, and e ain i s people is absolu ely c i ical o ensu ing ha digi aliza ion leads
o b oadly sha ed p ospe i y a he han unemploymen o pola iza ion. The li e a u e
s ongly indica es ha coun ies in es ing in educa ion and skills de elopmen a e be e
posi ioned o abso b echnological shocks (A n z e al.,2016).
Wo ke s wi h lowe educa ional a ainmen a e disp opo iona ely a isk om au-
oma ion (A n z e al.,2016;Chang & Huynh,2016). Low-wage, ou ine jobs—o en held by
less-educa ed wo ke s—a e easie o au oma e han high-skill jobs ha in ol e c ea i i y,
complex p oblem sol ing, o human in e ac ion (Chang & Huynh,2016;OECD,2019a).
Thus, coun ies wi h a la ge sha e o employmen in low-skill ou ine occupa ions ( o
example, assembly line manu ac u ing o basic cle ical wo k) ace a double challenge: hese
jobs migh be los o machines, and he wo ke s may no ha e he educa ion needed o shi
in o new oles. The In e na ional Labou O ganiza ion (ILO) and o he bodies ha e wa ned
ha wi hou signi ican upskilling, au oma ion could wo sen inequali y be ween high-skill
and low-skill wo ke s, and be ween coun ies ha ha e skilled labo e sus hose ha do
no (Uni ed Na ions & In e na ional Labou O ganiza ion,2024).
Al hough esea ch poin s o he isk o au oma ion o wo k based on ou ine asks
pe o med by low-skilled wo ke s, ecen s udies poin o he ac ha high-skilled wo ke s
a e no immune o dis up ing changes. Ad ances in a i icial in elligence and machine
lea ning enable au oma ion o non- ou ine cogni i e asks adi ionally hough o be he
domain o highly educa ed p o essionals (Ozgul e al.,2024;OECD,2022). While some
highly skilled wo ke s bene i om ask augmen a ion, o he s expe ience wage s agna ion
o e osion, pa icula ly in occupa ions whe e ou ine elemen s a e suscep ible o au oma ion
(Acemoglu & Res epo,2018). B ynjol sson and McA ee (2014) emphasize ha his wa e o
“digi al dis up ion” has in oduced a new o m o skill-biased echnological change, whe e
bo h low- and mid-skill jobs a e hollowed ou while high-skill oles become mo e compe i-
i e. This sugges s ha inequali y isks a e no only e ical (low- s. high-skill) bu also
ho izon al—cu ing ac oss sec o s and job ypes depending on hei speci ic ask s uc u es.
While policymake s alk abou he u u e o wo k, adi ional eadiness me ics do
no di ec ly accoun o how h ea ened a coun y’s exis ing jobs a e by au oma ion. A
coun y migh sco e easonably on in as uc u e and cu en usage, bu i a la ge ac ion
o i s wo k o ce is in au oma able jobs and he coun y lacks e aining p og ams, i s u u e
eadiness is shaky. The Economis In elligence Uni ’s Au oma ion Readiness Index (ARI) in
2018 was a pionee ing e o o quali a i ely assess how p epa ed coun ies a e o au oma-
ion, examining educa ion policies, labo ma ke p og ams, and inno a ion s a egies. The
ARI ound ha e en leading na ions had much oom o imp o emen — o example, ew
Economies 2025,13, 152 15 o 22
Figu e 3. Au oma ion isk s. Educa ion Index.
Table 2. S a is ical signi icance o measu emen s.
B and A C and A D and A
Co ela ion Co ela ion Co ela ion
−0.5959752068 −0.3594763521 −0.4876465918
p- alue p- alue p- alue
0.0008182403957 0.06027140363 0.008481857593
In he hi d case (D–A), he p- alue is again below 0.05, con i ming a s a is ically
signi ican nega i e co ela ion be ween me ics D and A.
I is impo an o no e ha while he s eng h and di ec ion o he ela ionship a e
desc ibed by he co ela ion coe icien , he p- alue is used o de e mine whe he he obse ed
co ela ion is s a is ically unlikely o ha e occu ed by chance. In line wi h his c i e ion, only
hose co ela ions wi h p- alues below 0.05 a e conside ed u he in he analysis.
I we o m clus e s g ouping coun ies by me ic A, i is possible o see a pa e n in he
alues o me ics B and D (Tables 3and 4). The clus e s, acco ding o Me ic A, a e o med wi h
5% nume ic in e als. Tha is, he g oups a e dis ibu ed as 0–5%, 5–10%, 10–15%, 15–20%,
and 20–25%. The pa e n is exp essed using a hea map. Using he colo scales ela ionships,
de ia ions and ex eme alues a e iden i ied. Me ic B alues abo e 5% a e highligh ed wi h a
da ke shade o g een. Values below 5% a e highligh ed by ligh e shades o g een. Fo me ic
D, he da kes shades o g een a e applied o hose alues ha a e in closes p oximi y o 1.
Fu he upg ading he cla i y o Tables 3and 4,
Figu es 4and 5
show quad an s whe e we
can g oup coun ies acco ding o he deg ee o isk o wo k au oma ion and a e age spending
on educa ion o a e age alues o he Educa ion Index. Quad an s a e numbe s om 1 o 4
( op le is 1, op igh is 2, bo om igh is 3, bo om le is 4).
Economies 2025,13, 152 16 o 22
Table 3. Hea map o pa e ns be ween me ics A and B.
Coun y (A) Jobs a High Risk
o Au oma ion (2012)
(B) A e age Expendi u e on
Educa ional Ins i u ions as a
Pe cen age o GDP (2012–2020)
No way 5.70% 6.48%
Finland 7.20% 5.48%
Sweden 8.00% 5.40%
New Zealand 10.00% 5.63%
Uni ed S a es 10.20% 6.11%
Sou h Ko ea 10.40% 5.15%
Denma k 10.70% 5.84%
Ne he lands 11.40% 5.28%
Uni ed Kingdom 11.70% 6.29%
Es onia 12.20% 4.70%
Canada 13.50% 5.83%
Belgium 14.00% 5.73%
Japan 15.10% 4.12%
I aly 15.20% 3.93%
Czechia 15.50% 3.97%
I eland 15.90% 4.00%
Tu key 16.40% 5.13%
F ance 16.40% 5.24%
Aus ia 16.60% 4.83%
Is ael 16.80% 6.09%
Ge many 18.40% 4.30%
Poland 19.80% 4.57%
Li huania 21.10% 3.87%
Chile 21.60% 6.13%
Spain 21.70% 4.41%
G eece 23.40% 3.73%
Slo enia 25.70% 4.46%
Slo akia 33.60% 3.87%
Figu e 4. Quad an iew—au oma ion isk s. educa ion expendi u e.
Economies 2025,13, 152 17 o 22
Table 4. Hea map o pa e ns be ween me ics A and D.
Coun y (A) Jobs a High Risk o
Au oma ion (2012)
(D) A e age Value o
Educa ion Index
(2012–2022)
No way 5.70% 0.93
Finland 7.20% 0.95
Sweden 8.00% 0.93
New Zealand 10.00% 0.97
Uni ed S a es 10.20% 0.91
Sou h Ko ea 10.40% 0.87
Denma k 10.70% 0.95
Ne he lands 11.40% 0.92
Uni ed Kingdom 11.70% 0.92
Es onia 12.20% 0.90
Canada 13.50% 0.90
Belgium 14.00% 0.94
Japan 15.10% 0.85
I aly 15.20% 0.80
Czechia 15.50% 0.88
I eland 15.90% 0.90
Tu key 16.40% 0.78
F ance 16.40% 0.82
Aus ia 16.60% 0.85
Is ael 16.80% 0.85
Ge many 18.40% 0.95
Poland 19.80% 0.88
Li huania 21.10% 0.90
Chile 21.60% 0.81
Spain 21.70% 0.82
G eece 23.40% 0.88
Slo enia 25.70% 0.90
Slo akia 33.60% 0.84
Figu e 5. Quad an iew—au oma ion isk s. Educa ion Index.
Economies 2025,13, 152 18 o 22
Looking a Table 3, a e age sha e o jobs a high isk o au oma ion is 15.65%, wi h
he lowes alue 5.7% and he highes eaching 33.6%. As o spending on educa ional
ins i u ions, he a e age is 5.02% o GDP, wi h alues anging om 3.73% o 6.48%. These
da a poin o a ela i ely wide dispe sion in he in ensi y o public in es men in educa ion,
e lec ing di e en poli ical and economic s a egies o indi idual coun ies. The hea map
o Table 3clea ly shows ha he uppe pa o he able ep esen ing hose coun ies, whose
isk o job au oma ion is lowe han a e age, ha e highe expendi u es in educa ion. The
bo om pa o he able does no gi e us a clea answe .
Figu e 4 u he elabo a es and g oups coun ies as ollows:
•
Quad an 1: Coun ies wi h abo e-a e age educa ion expendi u es as a % o GDP
(>0.05) ha e a below-a e age % o jobs a high isk o au oma ion (<0.157). These
a e No way, Finland, Sweden, New Zealand, Uni ed S a es, Sou h Ko ea, Denma k,
Ne he lands, Uni ed Kingdom, Canada, and Belgium.
•
Quad an 2: Coun ies wi h abo e-a e age educa ion expendi u es as a % o GDP
(>0.05) ha e an abo e-a e age % o jobs a high isk o au oma ion (>0.157). These a e
Is ael, Chile, Tu key, and F ance.
•
Quad an 3: Coun ies wi h below-a e age educa ion expendi u es as a % o GDP
(<0.05) ha e an abo e-a e age % o jobs a high isk o au oma ion (>0.157). These a e
I eland, Aus ia, Ge many, Poland, Spain, Slo enia, Li huania, G eece, and Slo akia.
•
Quad an 4: Coun ies wi h below-a e age educa ion expendi u es as a % o GDP
(<0.05) ha e a below-a e age % o jobs a high isk o au oma ion (<0.157). These a e
Es onia, I aly, Japan, and Czechia.
In e ms o he Educa ion Index (Table 4), he a e age alue is 0.886, wi h a minimum
alue o 0.78 and a maximum alue o 0.97. These da a again indica e signi ican di e si y
be ween coun ies in e ms o exposu e o au oma ion isk and yea s spen schooling in
educa ion sys ems. Again, as is he case wi h da a in Tables 3and 4, using hea map
colo ing, i is spli in o wo pa s. The uppe pa again clea ly shows ha coun ies ha
ha e a high Educa ion Index a e less suscep ible o job au oma ion. The lowe pa o he
able is no so clea . Cla i y again p o ides a sca e plo g aph di ided in o quad an s
(Figu e 5) whe e quad an s a e again g ouped in o ou ca ego ies:
•
Quad an 1: Coun ies wi h abo e-a e age a e age alues o he Educa ion Index
(>0.886) ha e a below-a e age % o jobs a high isk o au oma ion (<0.157). These a e
No way, Finland, Sweden, New Zealand, Denma k, Belgium, Ne he lands, Uni ed
Kingdom, Uni ed S a es, Es onia, and Canada.
•
Quad an 2: Coun ies wi h abo e-a e age a e age alues o he Educa ion Index
(>0.886) ha e an abo e-a e age % o jobs a high isk o au oma ion (>0.157). These
a e I eland, Ge many, Li huania, and Slo enia.
•
Quad an 3: Coun ies wi h below-a e age a e age alues o he Educa ion Index
(<0.886) ha e an abo e-a e age % o jobs a high isk o au oma ion (>0.157). These
a e Tu key, F ance, Aus ia, Is ael, Poland, G eece, Spain, Chile, and Slo akia.
•
Quad an 4: Coun ies wi h below-a e age a e age alues o he Educa ion Index
(<0.886) ha e a below-a e age % o jobs a high isk o au oma ion (<0.157). These a e
Czechia, Japan, I aly, and Sou h Ko ea.
5. Discussion
The indings o his s udy e eal subs an ial dispa i ies in coun ies’ eadiness o
digi al ans o ma ion in e ms o human capi al and he isk o job au oma ion. We
iden i ied a g oup o bes -p epa ed coun ies ha sys ema ically in es signi ican ly in
educa ion and demons a e high educa ional pe o mance (e.g., Educa ion Index), while
simul aneously exhibi ing a ela i ely low sha e o jobs a high isk o au oma ion. These
Economies 2025,13, 152 19 o 22
include economically ad anced coun ies such as New Zealand, Canada, Sweden, No way,
Denma k, and Finland, which consis en ly de elop human capi al and whose labo o ces
possess he compe encies equi ed o mi iga e he dis up i e e ec s o au oma ion. A
he opposi e end o he spec um a e leas -p epa ed coun ies— o example, Slo akia,
Poland, and G eece—wi h below-a e age in es men in educa ion and weake educa ional
ou comes, which also show a high p opo ion o jobs suscep ible o au oma ion. This
combina ion o insu icien human capi al and high echnological ulne abili y sugges s
signi ican exposu e o labo ma ke shocks.
While he Au oma ion Readiness Index (ARI) (The Economis In elligence Uni ,2018)
quali a i ely highligh ed ha many coun ies had no su icien ly upda ed hei educa ion
policies in esponse o he ise o AI and au oma ion, ou s udy quan i a i ely ein o ces
his pe spec i e. I shows ha coun ies wi h unde de eloped o unde unded educa ion
sys ems al eady exhibi highe ulne abili y, wi h la ge p opo ions o au oma able jobs.
Thus, policy ecommenda ions include implemen ing la ge-scale upskilling p og ams and
li elong lea ning s a egies a ge ing wo ke s in he mos exposed sec o s. I neglec ed,
au oma ion may exace ba e egional and social inequali ies— o ins ance, h ough ising
long- e m unemploymen o he decline o en i e economic sec o s. Go e nmen s should
p io i ize inc easing educa ion in es men , which includes no only aising educa ion
expendi u e as a sha e o GDP bu ensu ing he e ec i e alloca ion o hese esou ces.
Examples o such alloca ion can be ocused on mode nizing cu icula (wi h emphasis
on digi al skills, STEM disciplines, and adap abili y), imp o ing eaching quali y, and
p epa ing educa o s o he digi al e a.
Fo mode a ely p epa ed coun ies, ou indings indica e he need o be e policy
alignmen . Na ions like F ance o Is ael, whe e educa ion spending is high ye au oma ion
isk emains ele a ed, should assess whe he esou ces a e used e ec i ely— o ins ance,
whe he educa ion sys ems espond o labo ma ke needs in he digi al e a. These coun ies
may bene i om e o ms linking educa ion and p ac ice (e.g., dual educa ion, pa ne ships
wi h ech i ms) and p omo ing ans e able digi al skills. O he s, such as Ge many and
I eland, wi h high-quali y educa ion ou comes bu pe sis en au oma ion isk, should
examine hei economic s uc u es. A la ge sha e o ou ine-in ensi e indus ial sec o s
may ende e en well-educa ed wo k o ces ulne able. Hence, policy p io i ies include
inno a ion suppo and job c ea ion in sec o s esilien o au oma ion, alongside eskilling
wo ke s om indus ies nega i ely impac ed by digi al ans o ma ion.
Bes -p epa ed coun ies should no be complacen . While cu en ly leading, apid
echnological change (e.g., AI, obo ics, pla o m economy) may e eal u u e weaknesses.
These coun ies should con inue in es ing in human capi al, egula ly upda e educa ional
con en , and p omo e a cul u e o li elong lea ning. They may se e as models o bes p ac-
ice o less-p epa ed coun ies. Less-p epa ed coun ies could adop success ul policies,
such as ea ly digi al li e acy educa ion, in es men in R&D, and ac i e labo ma ke policies.
F om he b oade li e a u e pe spec i e, his s udy ex ends and complemen s p io
esea ch on digi al ans o ma ion eadiness, especially by emphasizing he ole o human
capi al and au oma ion isk. Many exis ing indices (Ne wo k Readiness Index (NRI)
(Du a & Lan in,2023), IMD Wo ld Digi al Compe i i eness Ranking (IMD,2024), Digi al
Adop ion Index o he Wo ld Bank (Wo ld Bank,2016), Cisco Digi al Readiness Index
(Cisco Sys ems,2019)) emphasize cu en in as uc u e o usage bu unde ep esen he
u u e wo k o ce dimension. Resul s o his esea ch ad ance his pe spec i e by linking
educa ion quali y indica o s wi h au oma ion isk es ima es. Thus, his s udy add esses a
gap p e iously no ed in he li e a u e: he need o in eg a e au oma ion ulne abili y in o
na ional eadiness assessmen s. Ou indings om a ce ain poin o iew con i m on a
mac o le el wha p e ious s udies (Co ejo a & Chino acky,2021;A n z e al.,2016;F ey &
Economies 2025,13, 152 20 o 22
Osbo ne,2017;Nedelkoska & Quin ini,2018) sugges ed on an indi idual le el— ha he
wo k o ces o coun ies wi h a lowe quali y o educa ion and hus, wi h lowe educa ion,
ace a highe au oma ion isk. Unlike he quali a i e ARI (The Economis In elligence
Uni ,2018), his s udy uses quan i a i e da a o iden i y he mos ulne able coun ies.
The esul ing ypology c ea es a mo e comp ehensi e pic u e o eadiness ha me ges
echnological and human capi al dimensions.
6. Conclusions
This s udy con ibu es o unde s anding how coun ies a e p epa ed o changes
d i en by digi al ans o ma ion om he pe spec i e o hei u u e wo k o ce. By quan i-
ying he ela ionship be ween educa ion quali y indica o s and job au oma ion isk, we
iden i ied which OECD coun ies a e bes and leas p epa ed o impending echnological
changes. The analysis showed ha inadequa e educa ional in es men and weak lea ning
ou comes co ela e wi h g ea e au oma ion ulne abili y. This has implica ions o bo h
esea ch and policymaking.
The s udy and analysis ha e se e al me hodological limi a ions o which di ec ions
o u he esea ch a e sugges ed:
•
The s udy is based on isk es ima es om 2012 by Nedelkoska and Quin ini, 2018. Tech-
nological ad ances since 2012—pa icula ly in AI and obo ics—ha e likely shi ed
bo h he na u e and scale o au oma able asks. The di ec ion o u he esea ch should
build on he s udy by Nedelkoska and Quin ini and should p oduce an upda ed lis o
coun ies ca ego ized acco ding o he isk o au oma ion o wo k in hose coun ies.
•
Da a o he o he indica o s, which a e PISA sco es, Educa ion Index and A e age
Educa ion Expendi u e as % o GDP, a e om p e ious yea s. This can be seen as a
o m o limi a ion o he esea ch, which is a sugges ion o u he esea ch: depending
on he a ailabili y o mo e ecen da a, he measu emen s need o be upda ed o bes
e lec he cu en si ua ion.
•
The sample o coun ies was limi ed o hose wi h a ailable s anda dized da a (OECD
coun ies). Fu u e esea ch should examine da ase s om o he coun ies o o ganiza-
ions ha use simila o complemen a y me ics.
•
Due o he a ailabili y o da a o a selec ed sample o coun ies, he indica o s used o
measu e human capi al we e limi ed o h ee: educa ion expendi u e, PISA sco es, and
he Educa ion Index. While ele an , hese me ics do no ully cap u e he dimensions
necessa y o p o ide a comp ehensi e o e iew o educa ion quali y. The e o e,
u u e esea ch could del e deepe by clus e ing coun ies based on complemen a y
indica o s speci ically designed o assess he quali y o educa ion.
In conclusion, his s udy highligh s he impo ance o u u e wo k o ce p epa ed-
ness as a key pilla o na ional digi al eadiness. Coun ies wi h weak in es men in
educa ion and a ulne able labo s uc u e may s uggle o adap o apid echnological
change. Fo policymake s, he indings o e a clea di ec i e: in es in human capi al,
p omo e skill adap abili y, and os e esilien labo ma ke s o secu e he bene i s o digi al
ans o ma ion and mi iga e i s isks.
Au ho Con ibu ions: Concep ualiza ion, R.C. and N.S.; me hodology, R.C.; alida ion, R.M.; o mal
analysis, R.C. and N.S.; in es iga ion, R.C.; esou ces, R.C.; da a cu a ion, R.C.; w i ing-o iginal
d a p epa a ion, R.C.; w i ing- e iew and edi ing, R.C., N.S. and L.M.; isualiza ion, R.C.; unding
acquisi ion, R.M. All au ho s ha e ead and ag eed o he published e sion o he manusc ip .
Funding: This esea ch was unded by a g an p o ided by he scien i ic esea ch p ojec 2020-1-MT01-
KA203-074215: In eg a ed RPL & APEL Le el 6 Acc edi ed Online P og amme o En ep eneu s.
Ins i u ional Re iew Boa d S a emen : No applicable.
Economies 2025,13, 152 21 o 22
In o med Consen S a emen : No applicable.
Da a A ailabili y S a emen : The da a ha suppo he indings o his s udy a e de i ed om
publicly a ailable sou ces (OECD,2019c,2023,2025;Uni ed Na ions De elopmen P og amme
[UNDP],2024) and we e p ocessed by he au ho s.
Con lic s o In e es : The au ho s decla e no con lic s o in e es .
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