Mu i e, Ob ain Tinashe
A icle
A i icial in elligence and i s ole in shaping o ganiza ional
wo k p ac ices and cul u e
Adminis a i e Sciences
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MDPI – Mul idisciplina y Digi al Publishing Ins i u e, Basel
Sugges ed Ci a ion: Mu i e, Ob ain Tinashe (2024) : A i icial in elligence and i s ole in shaping
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Ci a ion: Mu i e, Ob ain Tinashe.
2024. A i icial In elligence and I s
Role in Shaping O ganiza ional Wo k
P ac ices and Cul u e. Adminis a i e
Sciences 14: 316. h ps://doi.o g/
10.3390/admsci14120316
Recei ed: 10 Sep embe 2024
Re ised: 3 No embe 2024
Accep ed: 14 No embe 2024
Published: 28 No embe 2024
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A icle
A i icial In elligence and I s Role in Shaping O ganiza ional
Wo k P ac ices and Cul u e
Ob ain Tinashe Mu i e
Adminis a ion and In o ma ion Managemen Depa men , Facul y o Managemen and Public Adminis a ion
Sciences, Wal e Sisulu Uni e si y, Bu e wo h 4960, Sou h A ica; omu i [email p o ec ed]
Abs ac : The ad en o A i icial In elligence (AI) is p o oundly ans o ming o ganiza ional land-
scapes, signi ican ly in luencing wo k p ac ices and igge ing cul u al shi s. This s udy explo es he
ole o AI in eshaping o ganiza ional wo k p ac ices and examines he esul ing cul u al ans o ma-
ion. Th ough a sys ema ic li e a u e e iew, his s udy syn hesizes exis ing esea ch o p o ide a
comp ehensi e unde s anding o AI’s impac on o ganiza ional landscapes. A sys ema ic li e a u e
e iew was conduc ed, analyzing pee - e iewed a icles, books, and con e ence pape s o iden i y
key hemes ela ed o AI-d i en changes in wo k p ac ices, including au oma ion, decision making,
and employee oles. I also explo es how hese changes in luence o ganiza ional cul u e, pa icula ly
shi s owa d inno a ion, agili y, and con inuous lea ning, alongside challenges like esis ance o
change and e hical conce ns. While AI adop ion p omises bene i s such as enhanced e iciency,
p oduc i i y, and inno a ion, i also p esen s signi ican challenges ela ed o cul u al alignmen , em-
ployee esis ance, e hical conce ns, and leade ship communica ion. E ec i e leade ship, anspa en
communica ion, and in es men s in skills de elopmen eme ge as pi o al s a egies o o e coming
hese obs acles and ensu ing success ul AI implemen a ion. The indings o e insigh s in o he
complex in e play be ween AI adop ion and cul u al ans o ma ion, highligh ing gaps in he cu en
esea ch and sugges ing di ec ions o u u e s udies. This s udy se es as a aluable esou ce o
academics and p ac i ione s seeking o unde s and he b oade implica ions o AI on o ganiza ional
s uc u es and cul u e.
Keywo ds: a i icial in elligence; o ganiza ional cul u e; cul u al ans o ma ion
1. In oduc ion
In he con empo a y business landscape, he in eg a ion o a i icial in elligence (AI)
has eme ged as a ans o ma i e o ce, eshaping adi ional wo k p ac ices wi hin o gani-
za ions (Thilaga a hy and Venka asamy 2023). The apid ad ancemen o AI echnologies
has led o hei widesp ead adop ion ac oss a ious indus ies, anging om manu ac u -
ing and heal hca e o inance and e ail. As AI sys ems become inc easingly sophis ica ed,
o ganiza ions a e le e aging hei capabili ies o au oma e ou ine asks, enhance decision-
making p ocesses, and d i e inno a ion (Benbya e al. 2020). Howe e , he in eg a ion o
AI is no me ely a echnological endea o ; i engende s p o ound changes in o ganiza ional
cul u es and wo k p ac ices.
O ganiza ional cul u e is b oadly de ined as he sha ed alues, belie s, no ms, and
p ac ices ha shape he beha io s and in e ac ions o indi iduals wi hin an o ganiza ion.
This cul u e se es as an unde lying amewo k ha guides decision making, wo k p ac-
ices, and social dynamics ac oss a ious o ganiza ional le els. Acco ding o Schein (2010),
o ganiza ional cul u e ope a es on h ee dis inc le els: a i ac s ( isible o ganiza ional
s uc u es and p ocesses), espoused alues (s a ed belie s and no ms), and unde lying
assump ions (unconscious, aken- o -g an ed belie s). These laye s o cul u e in luence
how employees pe cei e hei oles, ela e o hei colleagues, and adap o o ganiza ional
changes, including echnological shi s such as he in eg a ion o AI. Fu he mo e, Ho s ede
Adm. Sci. 2024,14, 316. h ps://doi.o g/10.3390/admsci14120316 h ps://www.mdpi.com/jou nal/admsci
Adm. Sci. 2024,14, 316 2 o 16
(1991) concep ualized cul u e as “ he collec i e p og amming o he mind,” unde sco ing
i s deep in luence on indi idual and g oup beha io wi hin o ganiza ions. Ho s ede’s wo k
sugges s ha cul u al alues d i e beha io al pa e ns, a ec ing how inno a ions like AI
a e adop ed and how hey eshape wo kplace in e ac ions and alues.
This s udy used a de ini ion by (Mo cos 2018), who de ined o ganiza ional cul u e
as he sha ed alues, belie s, and beha io s ha cha ac e ize an o ganiza ion and guide
i s membe s’ in e ac ions, and decision making plays a pi o al ole in shaping employee
a i udes, in luencing pe o mance, and ul ima ely de e mining he o ganiza ional e ec i e-
ness. Mo eo e , o ganiza ional cul u e is no s a ic; i e ol es in esponse o in e nal and
ex e nal s imuli, including echnological ad ancemen s such as AI
(Chaudha y e al. 2023).
The in oduc ion o AI echnologies in o o ganiza ional wo k lows can ha e a -
eaching implica ions o o ganiza ional cul u e (Aldose i e al. 2023). The AI-d i en
au oma ion o ou ine asks can s eamline p ocesses, imp o e e iciency, and ee up
employees o ocus on mo e alue-added ac i i ies (Chaudha y e al. 2023). Howe e , i
can also lead o conce ns abou job displacemen , skills obsolescence, and esis ance o
change among employees (Aghion e al. 2019). Mo eo e , AI sys ems a e no neu al; hey
embody he alues and biases o hei designe s and de elope s, aising e hical and social
implica ions ha e e be a e h oughou o ganiza ional cul u e (Chaudha y e al. 2023).
O ganiza ions ac oss a ious indus ies a e inc easingly in eg a ing AI echnologies
in o hei wo k p ac ices, p omising enhanced e iciency, p oduc i i y, and inno a ion
(Benbya e al. 2020). Howe e , he adop ion o AI p esen s signi ican challenges ega ding
i s impac on o ganiza ional cul u e (Dwi edi e al. 2021). The apid de elopmen and
inco po a ion o AI echnology in o o ganiza ional wo k ope a ions ha e b ough abou
majo cul u al shi s. Unde s anding he exac na u e and scope o hese changes, howe e ,
is s ill a complex and mul i ace ed ask. In es iga ing how AI a ec s o ganiza ional wo k
p ac ices is, he e o e, impe a i e, wi h a pa icula emphasis on he complex in e ac ions
be ween cul u e adap a ion and echnology up ake.
As o ganiza ions na iga e he complexi ies o in eg a ing AI, hey ace he c i ical
ask o managing cul u al ans o ma ion o ensu e alignmen wi h s a egic objec i es
and sus ained employee engagemen (Ta iq e al. 2021). The apid e olu ion o AI has
in oduced p o ound changes in how asks a e pe o med, al e ing adi ional wo k lows
and necessi a ing new skill se s (Odonko e al. 2024). Employees may expe ience un-
ce ain y o esis ance in adap ing o hese changes, impac ing mo ale and p oduc i i y.
Mo eo e , cul u al no ms and alues wi hin o ganiza ions may clash wi h he in oduc ion
o AI, equi ing ca e ul na iga ion o os e accep ance and collabo a ion. This esea ch
unde sco es he impo ance o explo ing he in e sec ion o AI and o ganiza ional cul u e
o iden i y oppo uni ies and challenges. By unde s anding how AI in luences cul u al
dynamics, o ganiza ions can de elop s a egies o le e age i s po en ial while mi iga ing
nega i e impac s. Fu he mo e, os e ing a cul u e o con inuous lea ning and adap a ion
can acili a e smoo he AI in eg a ion, empowe ing employees o emb ace echnological
ad ancemen s and con ibu e o o ganiza ional success. The in eg a ion o AI in o o ga-
niza ional p ac ices necessi a es a nuanced app oach o managing cul u al change. By
ecognizing he in e play be ween AI adop ion and o ganiza ional cul u e, businesses can
p oac i ely add ess challenges and capi alize on oppo uni ies o g ow h and inno a ion.
The aim o his s udy is o in es iga e he impac o AI on o ganiza ional wo k p ac ices
and cul u al ans o ma ion, p o iding insigh s and ecommenda ions o success ul AI
in eg a ion. The scope o his a icle encompasses a comp ehensi e e iew o he exis ing
li e a u e and empi ical s udies ha examine he dual in luence o AI on o ganiza ional
wo k p ac ices and cul u e. I will add ess key hemes such as he ede ini ion o em-
ployee oles, he enhancemen o collabo a ion and communica ion, he challenges posed
by cul u al esis ance, and he e hical conside a ions ha a ise wi h AI implemen a ion.
Addi ionally, his esea ch seeks o iden i y bes p ac ices o e ec i ely managing he
cul u al shi s necessi a ed by AI in eg a ion, ensu ing ha o ganiza ions can le e age
hese echnological ad ancemen s while upholding co e alues such as inclusi i y and
Adm. Sci. 2024,14, 316 3 o 16
accoun abili y. Ul ima ely, his a icle aims o p o ide aluable insigh s o p ac i ione s
and esea che s alike on na iga ing he complex landscape o AI-d i en o ganiza ional
change. The ollowing sec ion discusses he p oblem s a emen .
2. P oblem S a emen
Despi e he g owing in e es in AI, he e is a limi ed unde s anding o how i s in eg a-
ion in o o ganiza ional wo k p ac ices in luences cul u al ans o ma ion (Thilaga a hy
and Venka asamy 2023). Exis ing s udies o en ocus on he echnical aspec s o AI o
i s impac on p oduc i i y, o e looking he b oade cul u al implica ions (Benbya e al.
2020). This knowledge gap makes i di icul o o ganiza ions o an icipa e and manage
he cul u al shi s ha accompany AI adop ion.
This s udy aims o explo e he impac o AI on o ganiza ional cul u e, wi h a pa icula
ocus on how AI-d i en changes in luence employee beha io , communica ion pa e ns,
leade ship dynamics, and he o e all wo k en i onmen (Ta iq e al. 2021). The esea ch
seeks o p o ide insigh s in o he challenges and oppo uni ies ha AI p esen s o o ga-
niza ional cul u al ans o ma ion, and o iden i y s a egies ha can help o ganiza ions
na iga e his complex p ocess e ec i ely (Odonko e al. 2024).
Objec i es
1. In es iga e he bene i s o AI in o ganiza ional wo k p ac ices.
2.
Analyze he po en ial challenges and esis ance ha o ganiza ions may encoun e
du ing he cul u al ans o ma ion d i en by AI.
3.
De elop ecommenda ions o o ganiza ions o manage cul u al ans o ma ion e ec-
i ely and align AI ini ia i es wi h hei s a egic goals.
Main Resea ch ques ion
How does he in eg a ion o AI in luence and ans o m wo k p ac ices and o ganiza-
ional cul u e wi hin o ganiza ions?
Resea ch Ques ions
1. Wha a e he bene i s o AI in o ganiza ional wo k p ac ices?
2.
Wha challenges and esis ance migh o ganiza ions encoun e du ing a cul u al
ans o ma ion d i en by AI?
3.
How can o ganiza ions acili a e a smoo h cul u al ans o ma ion in he con ex o AI
adop ion?
3. Signi icance o he S udy
Unde s anding he cul u al implica ions o AI is c i ical o o ganiza ions seeking
o le e age AI echnologies e ec i ely. By add essing he cul u al ans o ma ion ha
accompanies AI in eg a ion, o ganiza ions can be e align hei AI ini ia i es wi h hei
s a egic objec i es, enhance employee engagemen , and c ea e a wo k en i onmen ha is
adap able, inno a i e, and u u e- eady.
This s udy explo es he in ica e ela ionship be ween AI in eg a ion and o gani-
za ional cul u e, o e ing in aluable insigh s in o he socio echnical dynamics a play.
By examining how AI impac s cul u al no ms, alues, and p ac ices, i in o ms s a e-
gic decision-making p ocesses, aligning echnological in es men s wi h o ganiza ional
objec i es. Addi ionally, he indings con ibu e o he de elopmen o ailo ed change
managemen s a egies, add essing esis ance, os e ing engagemen , and ensu ing suc-
cess ul AI implemen a ion. E hical conside a ions and go e nance amewo ks ela ed o
AI in eg a ion a e also examined, p omo ing esponsible AI use while upholding o gani-
za ional alues. Mo eo e , his s udy empowe s o ganiza ional leade s wi h ac ionable
ecommenda ions o managing cul u al ans o ma ions amids AI adop ion, ad ancing
academic discou se in AI echnology, o ganiza ional cul u e, and change managemen .
Adm. Sci. 2024,14, 316 4 o 16
4. Li e a u e Re iew
Cul u al T ans o ma ion Th ough Technology
Eme ging echnologies, pa icula ly a i icial in elligence (AI), a e p o oundly eshap-
ing o ganiza ional no ms, alues, and employee engagemen by ede ining oles and
esponsibili ies, enabling employees o engage in complex p oblem-sol ing ac i i ies and
he eby shi ing he cul u e owa ds inno a ion and c ea i i y (Alupo e al. 2022). Ad-
di ionally, AI-powe ed pla o ms acili a e communica ion and collabo a ion, inc easing
employee engagemen and pa icipa ion in decision-making p ocesses, leading o a cul u e
o empowe men (Dasgup a and Wendle 2019). Howe e , cul u al esis ance can pose
challenges du ing AI in eg a ion, necessi a ing e ec i e change managemen s a egies o
o e come skep icism and p omo e an accep ing cul u e (Jango 2024). E hical conside a ions
also come o he o e on , as o ganiza ions mus es ablish amewo ks o AI use o build
us among employees and cus ome s, ein o cing alues like ai ness and accoun abili y
(Majeed and Hwang 2021). Fu he mo e, AI has he po en ial o enhance di e si y and
inclusion by minimizing biases in ec ui men and pe o mance e alua ions, p omo ing
a me i oc a ic cul u e, al hough igilance agains algo i hmic bias emains c ucial (Singh
and Pandey 2024). O e all, he in eg a ion o AI in o he wo kplace equi es o ganiza-
ions o na iga e hese cul u al ans o ma ions hough ully, ensu ing ha hey emb ace
inno a ion while upholding e hical s anda ds and inclusi i y. The in eg a ion o AI in o
o ganiza ional wo k p ac ices is an inc easingly impo an a ea o s udy, wi h signi ican
implica ions o how o ganiza ions ope a e, communica e, and e ol e. (Singh and Pandey
2024) emphasize ha AI can os e a cul u e ha p io i izes e iciency, agili y, and con in-
uous lea ning. Howe e , hese shi s may also challenge exis ing cul u al amewo ks,
pa icula ly in o ganiza ions ha alue adi ion and human-cen ic decision making.
AI-d i en change o en encoun e s esis ance, pa icula ly when i h ea ens es ab-
lished p ac ices o job secu i y (Phaladi e al. 2022). The li e a u e unde sco es he c ucial
ole o o ganiza ional cul u e in de e mining he success o ailu e o AI in eg a ion. Fo
example, Foun aine e al. (2019) a gue ha o ganiza ions wi h a cul u e o inno a ion and
openness a e mo e likely o success ully adop AI, whe eas hose wi h igid hie a chical
s uc u es may s uggle.
AI is ans o ming job oles and skill equi emen s, necessi a ing a shi owa ds mo e
ad anced echnical and analy ical compe encies (Olai an e al. 2021). A s udy by Da enpo
and Ki by (2016) highligh s how AI is ede ining he na u e o wo k, leading o a blend
o human and machine collabo a ion. While his shi can enhance p oduc i i y, i also
equi es o ganiza ions o in es in eskilling and upskilling p og ams.
The au oma ion o ou ine asks by AI has been linked o bo h posi i e and nega i e
e ec s on employee mo ale. While some employees app ecia e he educ ion in mono onous
wo k, o he s may expe ience anxie y o dissa is ac ion due o ea s o job displacemen
(Majeed and Hwang 2021). The li e a u e emphasizes he impo ance o add essing hese
conce ns h ough anspa en communica ion and inclusi e decision-making p ocesses
(Chilunjika e al. 2022).
The ole o leade ship in an AI-d i en o ganiza ion is e ol ing, wi h leade s needing
o adap o new echnologies and os e a cul u e o inno a ion (Alupo e al. 2022). Leade s
a e inc easingly expec ed o in eg a e AI insigh s in o s a egic decision making, which
equi es a blend o echnological unde s anding and adi ional leade ship skills. Haenlein
and Kaplan (2019) s a ed ha AI can suppo leade s in making mo e in o med and
objec i e decisions.
The e hical implica ions o AI in he wo kplace a e a g owing conce n, pa icula ly
ega ding issues o anspa ency, ai ness, and accoun abili y (Singh and Pandey 2024).
Leade s a e asked wi h es ablishing go e nance amewo ks ha ensu e AI is used espon-
sibly and aligns wi h o ganiza ional alues. The li e a u e sugges s ha e hical leade ship
is c i ical in na iga ing he complexi ies o AI adop ion (Majeed and Hwang 2021).
AI has he po en ial o signi ican ly op imize wo k p ocesses by au oma ing epe i i e
asks, p o iding p edic i e analy ics, and enhancing decision-making capabili ies (Phaladi
Adm. Sci. 2024,14, 316 5 o 16
e al. 2022). The li e a u e highligh s he dual impac o AI: while i can s eamline ope -
a ions and os e inno a ion, i also equi es he e hinking o adi ional wo k lows and
p ocesses o ully ealize i s bene i s (Dasgup a and Wendle 2019).
Collabo a ion be ween humans and AI sys ems is a c i ical a ea o s udy, wi h e-
sea che s explo ing how AI can augmen human capabili ies a he han eplace hem.
Wilson and Paul (2017) discusses he concep o “augmen ed in elligence”, whe e AI
suppo s humans in complex decision making, leading o imp o ed ou comes and new
oppo uni ies o inno a ion.
5. Theo e ical F amewo k
This s udy employs O ganiza ional Cul u e Theo y. As AI e olu ionizes o gani-
za ional landscapes ac oss sec o s, p esen ing bo h oppo uni ies and challenges, O ga-
niza ional Cul u e Theo y o e s a lens h ough which o unde s and he impac s on
o ganiza ional cul u e and employee beha io .
A i s co e, O ganiza ional Cul u e Theo y posi s ha o ganiza ional cul u e encom-
passes sha ed belie s, alues, and no ms ha shape how membe s pe cei e and in e ac
wi hin an o ganiza ion (Schneide e al. 2013). In he con ex o AI adop ion, o ganiza ions
mus ecognize ha in eg a ing AI echnologies in oduces changes no only in wo k lows
and decision-making p ocesses, bu also in cul u al no ms and p ac ices (Kim 2019).
As AI au oma es ou ine asks, augmen s decision-making p ocesses, and enables
da a-d i en insigh s, i undamen ally al e s how wo k is pe o med wi hin o ganiza ions
(Kim 2019). Howe e , his ans o ma ion also dis up s es ablished no ms and p ac ices,
p omp ing esis ance and ea o job displacemen among employees (V on is e al. 2022).
O ganiza ional Cul u e Theo y emphasizes he impo ance o unde s anding and add ess-
ing hese cul u al dynamics o acili a e success ul AI adop ion (Al-Su mi e al. 2022).
Building on his, O ganiza ional Cul u e Theo y (OCT) highligh s ha cul u e is no s a ic,
bu e ol es h ough in e ac ions be ween indi iduals and o ganiza ional sys ems (Ma in
2002). OCT emphasizes ha echnology, as a componen o wo k p ac ices, bo h shapes and
is shaped by o ganiza ional cul u e, a dynamic in e play ha is c ucial when in oducing
dis up i e inno a ions like AI.
6. Me hodology
This s udy employs a sys ema ic li e a u e e iew (SLR) app oach o in es iga e he
impac o AI on o ganiza ional wo k p ac ices and cul u e. The SLR me hod ensu es a
comp ehensi e and unbiased syn hesis o exis ing esea ch, ollowing a s uc u ed p ocess
called P e e ed Repo ing I ems o Sys ema ic Re iews and Me a-Analyses (PRIMSA) o
iden i y, e alua e, and in e p e ele an s udies. PRISMA is a widely ecognized p o ocol
o conduc ing sys ema ic e iews and is pa icula ly use ul in s uc u ing li e a u e sea ch
and selec ion p ocesses. PRISMA encou ages anspa ency h ough de ailed epo ing
o he c i e ia o inclusion and exclusion o s udies, sea ch s a egy, and da a ex ac ion
me hods (Mohe e al. 2009;Higgins and G een 2011;Ki chenham 2007). Inco po a ing
PRISMA s eng hens his e iew by documen ing each s ep, making i eplicable and
educing selec ion bias.
The e iew was guided by he ollowing esea ch ques ion: “How does he in eg a ion o
AI in luence and ans o m wo k p ac ices and o ganiza ional cul u e
wi hin o ganisa ions?”
A sys ema ic sea ch was conduc ed ac oss mul iple academic da abases, including
Google Schola , IEEE Xplo e, ScienceDi ec , and JSTOR. The sea ch s a egy in ol ed using
speci ic keywo ds and ph ases, such as “A i icial In elligence”, “o ganiza ional wo k
p ac ices”, “o ganiza ional cul u e”, “AI adop ion”, and “cul u al ans o ma ion”. Boolean
ope a o s (AND, OR) we e used o e ine he sea ch, ensu ing ha all ele an li e a u e
was cap u ed.
The ollowing c i e ia we e applied o de e mine he ele ance o s udies: pee -
e iewed a icles, books, and con e ence pape s published be ween 2017 and 2024, ocusing
on AI’s impac on wo k p ac ices and o ganiza ional cul u e. S udies no w i en in English,
Adm. Sci. 2024,14, 316 6 o 16
a icles lacking empi ical e idence, and pape s ocusing solely on echnical aspec s o AI
wi hou add essing o ganiza ional implica ions we e excluded. Non-English pape s we e
excluded, p ima ily due o p ac ical conside a ions in conduc ing a sys ema ic li e a u e
e iew. The esea che s conduc ing his e iew ha e p o iciency in English, which allows
hem o accu a ely in e p e , analyze, and syn hesize s udies in his language. Including
non-English pape s could in oduce isks o misin e p e a ion, especially when discussing
nuanced o echnical de ails ela ed o o ganiza ional cul u e and AI. Da a om he selec ed
s udies we e ex ac ed using a s anda dized o m, cap u ing key in o ma ion such as au-
ho ship, publica ion yea , esea ch objec i es, me hodology, indings, and conclusions. The
SLR was conduc ed by a single esea che , who handled all s ages o he e iew p ocess, in-
cluding da a ex ac ion, quali y assessmen , and analysis. Recognizing he po en ial o bias
and he need o consis ency, a s uc u ed, s anda dized app oach was adop ed o ensu e
accu acy and eliabili y h oughou he e iew. To main ain a consis en app oach o da a
collec ion, a s anda dized ex ac ion o m was de eloped, con aining he ollowing ields:
•S udy Iden i ica ion: au ho (s), yea , i le, and publica ion sou ce.
•
S udy Design and Me hodology: de ails o he esea ch design, sample size, da a
collec ion me hods, and analysis echniques.
•
Key Findings and Themes: main insigh s ela ed o AI’s impac on wo k p ac ices,
pa icula ly any hemes eme ging a ound o ganiza ional cul u e.
•
Quali y Assessmen : e alua ion c i e ia based on es ablished p o ocols (e.g., PRISMA,
Ki chenham) o assess each s udy’s me hodological igo .
•
Limi a ions and Con ibu ions: obse a ions on each s udy’s limi a ions, po en ial
biases, and unique con ibu ions o he esea ch opic.
This o m was pilo ed wi h a ew ini ial s udies o ensu e ha all necessa y da a
poin s we e cap u ed e ec i ely, a e which sligh adjus men s we e made o enhance
i s comp ehensi eness. E o s we e made o coun e po en ial bias by implemen ing a
sys ema ic sel -audi p ocess including egula sel -checks, p o ocol documen a ion, and
alida ion agains p o ocols. In ins ances whe e he e was ambigui y in in e p e ing ce ain
indings o assessing quali y, al e na i e iewpoin s om p io li e a u e and es ablished
SLR examples we e consul ed o guide decision making. This app oach helped mi iga e
pe sonal bias and ensu ed alignmen wi h accep ed no ms in he ield. The ex ac ed da a
we e hen analyzed o iden i y common hemes, ends, and gaps in he li e a u e.
To ensu e he eliabili y and alidi y o he indings, each s udy was subjec ed o a
quali y assessmen based on c i e ia such as he cla i y o esea ch ques ions, app op i-
a eness o me hodology, igo o da a analysis, and ele ance o he esea ch ques ions.
S udies mee ing a p ede ined quali y h eshold we e included in he inal syn hesis.
The da a analysis in ol ed hema ic syn hesis, whe e key hemes and pa e ns we e
iden i ied ac oss he e iewed li e a u e. The analysis ocused on how AI has in luenced
wo k p ac ices, he cul u al shi s obse ed in o ganiza ions, and he challenges and oppo -
uni ies a ising om hese changes. The indings we e hen compa ed and con as ed o
p o ide a comp ehensi e unde s anding o he opic.
The esul s o he sys ema ic li e a u e e iew a e p esen ed in a na a i e o ma ,
suppo ed by ables and igu es whe e app op ia e. The discussion sec ion in e p e s
he indings in he con ex o exis ing knowledge, highligh ing con ibu ions o he ield,
iden i ying esea ch gaps, and o e ing ecommenda ions o u u e s udies.
Figu e 1 ep esen s he P e e ed Repo ing I ems o Sys ema ic Re iews and Me a-
Analysis (PRISMA) model employed in his s udy.
The PRISMA model, shown in Figu e 1, ou lines e e y s ep ha was ca ied ou in he
da a collec ion p ocess. The s udy’s inclusion c i e ion equi ed ha each s udy explo e he
impac o AI in o ganiza ional wo k p ac ices. This choice was made o ensu e ha a wide
ange o s udies could be included in he e iew. F om all he selec ed da abases, a o al o
4200 s udies, jou nal a icles, and con e ence pape s we e e ie ed.
Howe e , he ini ial esul s con ained unsui able and un il e ed da a. The e o e,
nume ous echniques, such as sea ch engine il e ing and ange and egional il e ing, we e
Adm. Sci. 2024,14, 316 7 o 16
employed o na ow he esul s o 150 a icles. These a icles we e hen ead and u he
sc eened o sui abili y based on he ollowing inclusion c i e ia: publica ion da es be ween
2017 and 2024 and a icle ocus on he impac o AI on o ganiza ional wo k p ac ices.
Adm. Sci. 2024, 14, x FOR PEER REVIEW 7 o 17
indings in he con ex o exis ing knowledge, highligh ing con ibu ions o he ield, iden-
i ying esea ch gaps, and offe ing ecommenda ions o u u e s udies.
Figu e 1 ep esen s he P e e ed Repo ing I ems o Sys ema ic Re iews and Me a-
Analysis (PRISMA) model employed in his s udy.
Figu e 1. PRISMA model.
The PRISMA model, shown in Figu e 1, ou lines e e y s ep ha was ca ied ou in
he da a collec ion p ocess. The s udy’s inclusion c i e ion equi ed ha each s udy ex-
plo e he impac o AI in o ganiza ional wo k p ac ices. This choice was made o ensu e
ha a wide ange o s udies could be included in he e iew. F om all he selec ed da a-
bases, a o al o 4,200 s udies, jou nal a icles, and con e ence pape s we e e ie ed.
Howe e , he ini ial esul s con ained unsui able and un il e ed da a. The e o e, nu-
me ous echniques, such as sea ch engine il e ing and ange and egional il e ing, we e
employed o na ow he esul s o 150 a icles. These a icles we e hen ead and u he
sc eened o sui abili y based on he ollowing inclusion c i e ia: publica ion da es be-
ween 2017 and 2024 and a icle ocus on he impac o AI on o ganiza ional wo k p ac-
ices.
A e he i s sc eening, 150 a icles we e iden i ied. The au ho s hen e iewed he
ull ex o hese a icles, and a inal numbe o 19 a icles was hen a ained. The elimina-
ion o 30 a icles was due o ull ex e iew. Some a icles, al hough ela ed o a i icial
in elligence (AI) and o ganiza ional opics, lacked di ec ocus on he s udy’s co e hemes;
Figu e 1. PRISMA model.
A e he i s sc eening, 150 a icles we e iden i ied. The au ho s hen e iewed
he ull ex o hese a icles, and a inal numbe o 19 a icles was hen a ained. The
elimina ion o 30 a icles was due o ull ex e iew. Some a icles, al hough ela ed o
a i icial in elligence (AI) and o ganiza ional opics, lacked di ec ocus on he s udy’s
co e hemes; speci ically, AI’s in luence on wo k p ac ices and o ganiza ional cul u e. Fo
ins ance, se e al s udies ocused solely on echnical ad ancemen s in AI wi hou discussing
hei implica ions o wo k p ac ices, making hem less ele an o his SLR.
Ce ain s udies we e excluded due o insu icien me hodological igo , which could
po en ially comp omise he alidi y o hei indings. A icles wi h limi ed sample sizes,
poo da a collec ion p ac ices, o a lack o clea analysis me hods did no mee he quali y
s anda ds es ablished o his e iew, ollowing PRISMA and Ki chenham guidelines.
Following a hema ic analysis, he 19 a icles included in his s udy a e lis ed in Appendix A,
along wi h he hemes ha eme ged om hem.
7. Resul s
7.1. Oppo uni ies o AI in Cul u al T ans o ma ion
In oday’s as -paced and compe i i e business en i onmen , o ganiza ions a e con in-
ually seeking inno a i e ways o enhance hei ope a ional e iciency, make da a-d i en
Adm. Sci. 2024,14, 316 8 o 16
decisions, and deli e excep ional cus ome expe iences. The in eg a ion o AI echnolo-
gies in o o ganiza ional wo k p ac ices has eme ged as a ans o ma i e solu ion, o e ing
a my iad o bene i s ac oss a ious domains o business ope a ions. F om au oma ing
ou ine asks and p o iding deep da a insigh s o pe sonalizing cus ome in e ac ions
and enabling new business models, AI is eshaping he way o ganiza ions ope a e. This
sec ion explo es a eas whe e AI signi ican ly con ibu es o o ganiza ional success. Th ough
eal-wo ld examples and expe insigh s, i becomes e iden how AI no only op imizes
cu en p ocesses, bu also opens new a enues o g ow h and inno a ion.
7.1.1. Enhanced E iciency and P oduc i i y
The in eg a ion o AI echnologies has he po en ial o signi ican ly enhance e iciency
and p oduc i i y wi hin o ganiza ions (Ta iq e al. 2021). By au oma ing ou ine asks
and augmen ing decision-making p ocesses, AI sys ems can s eamline wo k lows, educe
manual e o s, and inc ease he ope a ional e iciency (Wan e al. 2020). This allows
o ganiza ions o ealloca e esou ces om epe i i e asks o mo e s a egic ini ia i es.
Employees can hen ocus on high- alue ac i i ies ha equi e c ea i i y, c i ical hinking,
and p oblem-sol ing skills, leading o inc eased p oduc i i y and inno a ion (Chilunjika
e al. 2022). In manu ac u ing, o example, AI-powe ed p edic i e main enance sys ems
can analyze equipmen pe o mance da a o an icipa e ailu es and schedule main enance
p oac i ely (Hamdan e al. 2024). This no only minimizes down ime, bu also op imizes
esou ce u iliza ion, ul ima ely imp o ing he o e all p oduc i i y (Phaladi e al. 2022).
7.1.2. Da a-D i en Insigh s and Decision Making
AI echnologies enable o ganiza ions o ha ness as amoun s o da a o gene a e
ac ionable insigh s and make in o med decisions (Majeed and Hwang 2021). By le e aging
machine lea ning algo i hms, AI sys ems can analyze complex da ase s, iden i y pa e ns,
and p o ide aluable ecommenda ions o suppo s a egic decision making. Access o
da a-d i en insigh s empowe s o ganiza ions o an icipa e ma ke ends, iden i y oppo u-
ni ies o g ow h, and mi iga e isks mo e e ec i ely. In heal hca e, o ins ance, AI-d i en
p edic i e analy ics ools can analyze pa ien da a o iden i y indi iduals a high isk o
de eloping ch onic diseases. Heal hca e p o ide s can use his in o ma ion o implemen
p oac i e in e en ions and pe sonalized ea men plans, ul ima ely imp o ing pa ien
ou comes and educing heal hca e cos s (Majeed and Hwang 2021).
7.1.3. Pe sonalized Cus ome Expe iences
AI echnologies enable o ganiza ions o deli e pe sonalized cus ome expe iences
by analyzing cus ome da a and p e e ences in eal ime. Th ough echniques such as
na u al language p ocessing and ecommenda ion algo i hms, AI sys ems can ailo p od-
uc s, se ices, and ma ke ing messages o mee he unique needs o indi idual cus ome s
(Wan e al. 2020). Pe sonaliza ion enhances cus ome sa is ac ion, loyal y, and e en ion
by demons a ing an unde s anding o cus ome s’ p e e ences and deli e ing ele an
o e s and ecommenda ions. E-comme ce pla o ms, o example, use AI-powe ed ecom-
menda ion engines o sugges p oduc s based on cus ome s’ b owsing his o y, pu chase
beha io , and demog aphic in o ma ion (Chand a e al. 2022). By p esen ing ele an
p oduc ecommenda ions, hese pla o ms inc ease con e sion a es and a e age o de
alues, ul ima ely d i ing e enue.
7.1.4. Inno a i e Business Models and Re enue S eams
The in eg a ion o AI echnologies enables o ganiza ions o explo e inno a i e business
models and e enue s eams ha we e p e iously una ainable (Fa ayola e al. 2023). By
le e aging AI capabili ies such as p edic i e analy ics, au oma ion, and pe sonaliza ion,
o ganiza ions can c ea e new alue p oposi ions and mone ize hei da a asse s in no el
ways (Enholm e al. 2022). Inno a i e business models and e enue s eams di e si y
o ganiza ions’ sou ces o income and inc ease hei esilience o ma ke dis up ions. Ride-
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