THE IMPACT OF ARTIFICIAL INTELLIGENCE ON CONSUMER BEHAVIOR

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Volume – III Issue -V (Sep embe -Oc obe ) 2025
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THE IMPACT OF ARTIFICIAL INTELLIGENCE ON CONSUMER BEHAVIOR
Doina Gu iţă
Depa men o Ma ke ing, Facul y o Law, Economy, Poli ical and Adminis a i e Sciences Uni e si y Pe e And ei o
Iaşi 700479, Iaşi Romania ORCHID ID: 000-0008-5920-838X
| Recei ed: 03.08.2025 | Accep ed: 09.08.2025 | Published: 06.10.2025
*Co esponding au ho : Doina Gu iţă
Depa men o Ma ke ing, Facul y o Law, Economy, Poli ical and Adminis a i e Sciences Uni e si y Pe e And ei o
Iaşi 700479, Iaşi Romania ORCHID ID: 000-0008-5920-838X
1. Re iew o he scien i ic li e a u e
The pu pose o he pape "The Impac o A i icial In elligence on
Consume Beha io " is o in es iga e and analyze how he use o
AI echnologies in luences pu chasing decisions and consume
beha io . Wi h he ad ancemen o a i icial in elligence (AI),
signi ican changes in how companies communica e wi h
cus ome s a e becoming mo e appa en . In his con ex , he need o
implemen an explicable AI capable o p o iding pe sonalized
shopping expe iences inc eases (Popescu, 2002). Explainable AI
b ings conside able po en ial by p o iding shopping expe iences
ailo ed o indi idual cus ome needs and p e e ences. I is
cha ac e ized by he abili y o explain he decisions made and he
esul s p oduced, which is becoming inc easingly impo an in he
con ex o pe sonalized shopping expe iences.
Abs ac
The pu pose o he pape "The Impac o A i icial In elligence on Consume Beha io " is o in es iga e and analyze how he use o
AI echnologies in luences pu chasing decisions and consume beha io . This pu pose may in ol e: explo ing beha io al changes,
s udying how AI in luences consume p e e ences, decisions and expe iences in he pu chase p ocess, iden i ying ad an ages and
disad an ages, analyzing he bene i s and isks o using a i icial in elligence in ela ion o he consume pu chase expe ience,
unde s anding u u e ends, p ojec ing possible di ec ions o consume beha io and how AI echnology will con inue o shape
pu chasing p ocesses in he u u e, ma ke and indus y sugges ions: p o iding ecommenda ions and s a egies o he indus y o
adap and g ow acco dingly wi h he changes d i en by he use o a i icial in elligence in he comme cial en i onmen .
Keywo ds:
E-comme ce, pe sonalized shopping expe iences, p edic i e analy ics, cus ome beha io , p e e ences, ma ke ing
e ec i eness.
JEL classi ica ion: D12, M31, O33
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AI explainable bene i s o pe sonalized shopping expe iences a e
a ied, i allows cus ome s o eel mo e in o med and con iden in
hei pu chase decisions. Mo eo e , companies can adjus hei
ecommenda ions in a mo e p ecise way, leading o an inc eased
le el o cus ome sa is ac ion and a highe likelihood o e u n. The
e hical aspec o AI also p o ides a sa e way o use cus ome da a,
he eby building us be ween consume s and companies (B adlow
e al., 2017).
As explainable AI becomes an essen ial ool o companies looking
o deli e pe sonalized shopping expe iences, unde s anding he
decisions made by AI becomes c ucial o cus ome s. This gi es
cus ome s no only an in o ma i e expe ience, bu also a sense o
secu i y in he pu chasing p ocess. In addi ion, he e hical use o
cus ome da a is becoming a hallma k o companies ha wan o
build s ong ela ionships wi h hei cus ome s.
In e ms o p edic i e analysis o shopping pa e ns, e aile s a e
inc easingly adop ing explainable AI o gain a deepe
unde s anding o cus ome beha io and p e e ences. This allows
hem o be e an icipa e u u e ends and op imize ma ke ing
s a egies o a ge cus ome s mo e e ec i ely (Le inson, 1993).
By in eg a ing AI in o p edic i e analy ics (Ka al e al., 2016),
e aile s can pe sonalize o e s and campaigns, he eby inc easing
he ele ance and e ec i eness o hei ac ions (Ca e & Tessa,
1991).
In conclusion, deploying explainable AI and using i o p edic i e
analy ics a e signi ican s eps owa ds deli e ing pe sonalized and
e icien shopping expe iences. These echnologies b ing bene i s
o bo h cus ome s and companies h ough inc eased in o ma ion,
inc eased us and op imiza ion o ma ke ing p ocesses (Magh oui
& Belghi h, 2019).
In he e a o as echnology and cons an inno a ions, A i icial
In elligence (AI) is becoming mo e and mo e p esen in ou daily
li es (Kaplan & Haen ein, 2019). I s impac on consume beha io
is a opic o inc eased in e es , as AI decisi ely in luences how we
in e ac wi h he p oduc s and se ices a ound us (B adlow e al.,
2017).
One o he mos ob ious aspec s o he impac o A i icial
In elligence is he inc eased pe sonaliza ion o he consume
expe ience. AI-powe ed ecommenda ion sys ems analyze use
beha io al pa e ns, o e ing pe sonalized sugges ions and p oduc s
ailo ed o indi idual p e e ences. Thus, consume s a e exposed o
a wide ange o ele an op ions, which can lead o g ea e b and
sa is ac ion and loyal y (Radu, 2017).
Howe e , his inc eased pe sonaliza ion may also aise p i acy
ques ions. The ex ensi e collec ion o pe sonal da a o eed AI
algo i hms may aise conce ns abou he p o ec ion o indi idual
p i acy (Shneide man, 2016). I is c ucial o businesses o s ike a
balance be ween pe sonaliza ion and espec o p i acy in o de o
build us among consume s (Balau e, 2016).
Ano he signi ican in luence o A i icial In elligence on
consume beha io can be seen in he ield o e-comme ce. AI-
powe ed cha bo s p o ide eal- ime suppo , enhancing he online
shopping expe ience (Malk idakis, 2018). They can quickly answe
cus ome ques ions, p o ide p oduc in o ma ion and guide he
pu chasing p ocess. In addi ion, AI algo i hms can analyze use s'
b owsing beha io o an icipa e hei p e e ences and imp o e
online in e ac ion (Gay e al., 2007).
Howe e , excessi e implemen a ion o cha bo echnologies can
lead o a loss o he human elemen in cus ome in e ac ion. I is
impo an o businesses o s ike a balance, ensu ing ha AI
complemen s and enhances se ices wi hou comple ely eplacing
human con ac (Ca e & Tessa, 1991).
In he ad e ising sec o , A i icial In elligence also plays an
essen ial ole. Ad anced algo i hms can analyze online consume
beha io o c ea e pe sonalized and ele an ad e ising
campaigns. This a ge ed app oach can maximize he impac o
you ads and inc ease con e sion a es.
Howe e , he e is a isk ha excessi e pe sonaliza ion will lead o
consume ad a igue. I ad e ising messages become oo in asi e
o oo equen , consume s may de elop a esis ance o hem and
he e ec i eness o ad e ising campaigns may dec ease (Dob e,
2006).
Ano he a ea whe e A i icial In elligence is undamen ally
changing consume beha io is in he heal hca e sec o . AI-
powe ed apps and de ices moni o and analyze use s' heal h da a,
p o iding pe sonalized heal hy li es yle ecommenda ions. These
echnologies can imp o e awa eness and engagemen in hei own
heal h, mo i a ing consume s o make heal hie choices.
Howe e , conce ns abou he secu i y o heal h da a and he co ec
in e p e a ion o in o ma ion p o ided by AI de ices a e c i ical
opics. I is essen ial o ha e igo ous egula ion and high s anda ds
o ensu e he quali y and p i acy o heal h da a (Feng & Fay,
2020).
Ano he c ucial aspec o he impac o A i icial In elligence on
consume beha io is he inc eased eliance on echnology. Wi h
he e e -wide in eg a ion o AI in o e e yday li e, consume s a e
becoming mo e dependen on echnology o ul ill hei needs and
wan s. This addic ion can ha e men al heal h consequences and
can aise conce ns abou he loss o essen ial human skills.
As echnology ad ances, i is impe a i e ha socie y emains
igilan in moni o ing and egula ing he use o AI o maximize
bene i s and minimize po en ial isks. Inc eased pe sonaliza ion,
e iciency in e-comme ce, a ge ed ad e ising and imp o ed
heal h a e jus a ew aspec s o he signi ican changes ha
A i icial In elligence is b inging o he way we consume and
in e ac wi h he wo ld a ound us (Ge lick & Liozu, 2020).
A i icial In elligence explains and helps e aile s be e unde s and
consume buying beha io s and ends. Wi h his echnology,
e aile s can gain deepe insigh in o hei cus ome s' p e e ences,
enabling hem o make sma e decisions and d i e g ea e
cus ome sa is ac ion.
Explainable AI is a echnology ha allows compu e s o explain
hei decision-making p ocesses o humans. Th ough his
echnology, e aile s can be e unde s and how and why hei
cus ome s make ce ain decisions. Fo example, AI-based models
can p edic cus ome g ow h a es and analyze cus ome buying
pa e ns o iden i y he mos popula p oduc s (Kuma e al., 2017).
This da a can hen be used o in o m p oduc ecommenda ions,
o e pe sonalized discoun s and c ea e mo e e ec i e ma ke ing
campaigns (G ewal e al., 2017).
Explainable AI also gi es e aile s a be e unde s anding o how
cus ome beha io s change o e ime (Inman & Nikolo a, 2017).
By acking and analyzing cus ome in e ac ions ac oss mul iple
channels, e aile s can gain a be e unde s anding o cus ome
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p e e ences and ends. This da a can hen be used o de elop new
s a egies o a ge cus ome s and imp o e cus ome se ice
(Huang & Rus , 2018).
Ul ima ely, explainable AI helps e aile s be e unde s and
cus ome shopping beha io s and ends. Using his echnology,
e aile s can gain a deepe unde s anding o hei cus ome s,
enabling hem o make sma e decisions and leading o g ea e
cus ome sa is ac ion (Holmq is e al., 2017).
Figu e 1. Explo ing he bene i s o explainable AI o he shopping
expe ience
Theo ies used in he accep ance o echnologies
The UTAUT model (Uni ied Theo y o Accep ance and Use o
Technology) is a model ha explains he in en ions o use s who
in e ac wi h in o ma ion sys ems ( igu e 2). The model was
de eloped by Venka esh e al. (2003) and con ains ou majo
ac o s:
 pe o mance expec ancy: e e s o he ex en o which a
use belie es ha he use o echnology o a compu e
sys em will help him ob ain ad an ages in he
pe o mance o wo k asks.
 e o expec a ion: he deg ee o ease wi h which he
compu e sys em is used.
 social in luence: he deg ee o which a use belie es ha
o he people wan him o use he sys em in ques ion and
ha i is impo an o do so.
 a o able condi ions: he deg ee o which an indi idual
belie es ha his o ganiza ion has he necessa y esou ces
o suppo he use o he sys em.
Figu e 2. The UTAUT model
2. Theo y o Ra ional Ac ion (TRA)
The heo y o a ional ac ion explains he ela ionship be ween
indi iduals' a i udes and hei beha io s, wi h he au ho s Fishbein
and Ajzen (1975) emphasizing ha a i udes explain human
ac ions. TRA highligh s how a i udes and beha io s co ela e wi h
he indi idual's in en ions in ca ying ou an ac ion. An indi idual's
in en ion o pe o m a ce ain beha io is a de e mining ac o o
he ac ion, and he a i ude owa ds a beha io and he subjec i e
no m a e ac o s o he beha io al in en ion ( igu e 3).
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Figu e 3. Theo y o a ional ac ion
Ad an ages and disad an ages o using AI.
The able below highligh s he ad an ages and disad an ages o
using a i icial in elligence:
Table 1. Ad an ages and disad an ages o using a i icial
in elligence
Ad an ages o using A i icial
In elligence
Disad an ages o using
A i icial In elligence
Au oma e epe i i e p ocesses
and edious wo k.
The isk o job losses in
ce ain sec o s.
Imp o ing accu acy and
e iciency in decision-making
p ocesses.
Dependence on accu a e da a
and i s quali y o he p ope
unc ioning o AI.
Pe sonalizing use expe iences
and ecommenda ions.
Da a secu i y and p i acy
issues.
Inc easing inno a ion and he
abili y o sol e complex
p oblems.
The possibili y o pe pe ua ing
o ampli ying biases in he
da a used.
Op imizing cos s and imp o ing
ope a ional e iciency.
The need o unde s anding
and clea egula ions o he
e hical use o AI.
Accele a ing and imp o ing
machine lea ning p ocesses.
High implemen a ion and
main enance cos s o complex
AI echnologies.
These a e jus a ew examples o ad an ages and disad an ages o
a i icial in elligence, and he e a e many mo e depending on he
speci ic ield o con ex o applica ion. E alua ing he p os and
cons o AI mus conside i s impac ac oss a wide ange o sec o s
and aspec s o li e.
Yes, he adap a ion o online shopping is one o he ob ious ends
in sales in Romania and can be impo an o consume s ega dless
o he en i onmen , whe he u al o u ban. He e a e some key
poin s:
3. Inc ease in online shopping in
Romania.
Digi iza ion end: Romania is expe iencing a s eady inc ease in
in e ne access and sma phone usage, leading o g ea e exposu e
and adop ion o online shopping.
Accessibili y and Con enience: Online shopping o e s 24/7
accessibili y and a wide ange o p oduc s, as well as a con enien
shopping expe ience wi hou he need o physically a el.
Online Deals and P omo ions: Online e aile s o en o e
p omo ions, discoun s and special o e s ha a ac consume s and
encou age hem o pu chase he p oduc s online.
Use expe ience: Online pla o ms in es in imp o ing use
expe ience by p o iding easy na iga ion, a ings, e iews and
cus ome suppo , which can encou age consume s o buy online.
Consume Adap a ion.
Con idence in secu i y: Consume s a e becoming inc easingly
awa e o he secu i y o da a and online paymen s, which imposes
he need o e aile s o ensu e a secu e and us ed en i onmen .
Educa ion and us : Mo e educa ion is needed among consume s,
especially in u al a eas, o unde s and he bene i s and how online
shopping wo ks.
In as uc u e and In e ne access: To suppo he g ow h o
online shopping in u al a eas, he e is a need o in es men in
digi al in as uc u e and he acili a ion o high-speed In e ne
access (Rowan, 2016).
Adap a ion o online shopping in Romania will con inue o be a
p ocess, wi h an emphasis on us , educa ion and accessibili y. I is
essen ial ha bo h consume s and e aile s adap o his digi al
e olu ion o enjoy he bene i s o online shopping.
The pu pose, objec i es and hypo heses o he esea ch
The pu pose o he pape "The Impac o A i icial In elligence on
Consume Beha io " is o in es iga e and analyze how he use o
AI echnologies in luences pu chasing decisions and consume
beha io .
The objec i es o he esea ch a e:
1. Cla i ying he objec i es o he in e iew o unde s and
how AI in luences consume beha io , how hey adjus
hei expec a ions and p e e ences in he con ex o hese
echnologies.
2. Iden i ying Consume Types: De ining he consume
segmen s you wan o explo e in e ms o hei
in e ac ion wi h AI in he buying p ocess.
The esea ch hypo heses a e:
Hypo hesis H1: The use o a i icial in elligence in pe sonalized
ecommenda ions leads o an inc ease in he equency and a e age
alue o pu chases.
Hypo hesis H2: The con enience and accessibili y o online
shopping wi h he help o a i icial in elligence causes a signi ican
shi in consume p e e ences in a o o online o e o line.
Hypo hesis H3: The use o a i icial in elligence in cus ome
suppo se ices leads o imp o ed cus ome sa is ac ion and
inc eased b and loyal y.
Hypo hesis H4: Exposu e o dynamic p icing algo i hms causes a
change in consume beha io , including when and how hey make
pu chases.
Hypo hesis H5: Inc easing he le el o awa eness and educa ion
abou he ope a ion o a i icial in elligence in luences he us and
adop ion o his echnology in he pu chase p ocess.
These hypo heses can o m he basis o in es iga ing and
e alua ing he impac o a i icial in elligence on consume
beha io . They can be es ed and analyzed h ough an empi ical
s udy o esea ch in ol ing da a analysis and di ec in e ac ion
wi h consume s o ob ain conc e e esul s and ele an insigh s
(Robe s & Be ge s, 1999).
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4. Resea ch me hodology
The esea ch design was ca ied ou h ough a ques ionnai e,
inspi ed by he posi i is esea ch philosophy, adop ed h oughou
he en i e s udy. Using his design, da a collec ion was es ablished
only a he buye le el.
The analysis was based on 137 esponden s in a wo kshop held a
he Pe e And ei Uni e si y in Iasi, on he same heme o he
in luence o AI on consume beha io .
A quan i a i e esea ch me hodology was used in he esea ch,
because quali a i e esea ch echniques canno be used o quan i y
a iables (Gu iţă, 2023). The ques ionnai e me hod was used. The
ques ionnai e is one o he popula esea ch me hods cha ac e ized
by e iciency, simplici y and e ec i eness.
The ques ionnai e included ques ions abou a i icial in elligence.
These ques ions a e adap ed and adjus ed acco ding o he speci ic
objec i es and assump ions o he ques ionnai e and he de ails we
wan o ob ain om he esponden s. The ques ions we e quan i ied
using he 5-poin Linke scale: 1= o al disag eemen ; 2= do no
ag ee; 3= nei he ag ee no disag ee; 4= ag ee; 5= o ally ag ee. In
able 2 we ind he ques ions o he ques ionnai e.
Table 2. Ques ionnai e ques ions
N .
C .
Ques ion
1
How is a i icial in elligence (AI) in luencing you
pu chasing decisions?
2
Wha aspec s o AI do you alue mos du ing he buying
p ocess?
3
Ha e you no iced changes in you buying p e e ences
since using AI? I so, wha a e hey?
4
How do you hink AI is pe sonalizing you shopping
expe ience?
5
Wha a e he bene i s you pe cei e in using AI in you
buying p ocess?
6
Is he e a speci ic AI ea u e you'd like o see imp o ed in
you shopping expe ience?
7
Ha e you e e expe ienced di icul y o us a ion using
AI while shopping? I so, wha we e hey?
8
How do you hink AI could imp o e he o e all shopping
expe ience?
9
Ha e you no iced any impac o using AI on you
pu chasing decisions in e ms o quan i y o equency o
pu chases?
10
Do you eel mo e con iden in you pu chasing decisions
hanks o AI assis ance?
11
How do you hink AI is in luencing you unde s anding o
he p oduc s/se ices you in end o pu chase?
12
Do you ha e any p i acy o secu i y conce ns abou using
AI in shopping?
13
Ha e you no iced any change in he le el o loyal y
owa ds ce ain b ands o s o es due o in e ac ion wi h AI
while shopping?
14
How do you hink AI migh in luence consume buying
beha io in he u u e?
Analysis o esponden s' p o iles
1. Dis ibu ion o esponden s acco ding o gende
The i s pa ame e o in e es was he gende o he esponden s.
The aim was o dis ibu e he esponden s acco ding o whe he
hey a e male o emale. The esul s indica ed ha emale
esponden s domina ed he sample wi h 58.3% while male
esponden s accoun ed o 41.7%. Table 3 illus a es he
dis ibu ion o esponden s by gende .
2. Dis ibu ion o esponden s acco ding o age
The second pa ame e o in e es was he esponden s' income. The
esul s showed ha he g oup wi h he mos esponden s had people
be ween he ages o 26-30, cons i u ing 43%. The g oup was
ollowed by esponden s aged 31-40, which cons i u ed 24.9%. The
g oup wi h he ewes esponden s was people o e 50,
ep esen ing only 5.1% o he o al. Table 3 illus a es he
dis ibu ion o esponden s by age.
Table 3. Demog aphic cha ac e is ics
Demog aphic
pa ame e s
F equency
Pe cen age (%)
Demog aphic
pa ame e s
F equency
Pe cen age (%)
Demog aphic
pa ame e s
F equency
Pe cen age (%)
Kind
Kind
Kind
Men 57 41.7
Men 57 41.7
Men 57 41.7
Women 80 58.3
Women 80 58.3
Women 80 58.3
Age
Age
Age
18-25 23 16.7
18-25 23 16.7
18-25 23 16.7
26-30 59 43
26-30 59 43
26-30 59 43
31-40 34 24.9
31-40 34 24.9
31-40 34 24.9
41-50 14 10.3
41-50 14 10.3
41-50 14 10.3
>50 7 5.1
>50 7 5.1
>50 7 5.1
5. Resea ch esul s
Fo almos all ques ions, 82% o he esponden s answe ed ha
hey ag ee ha a i icial in elligence has changed he buying
beha io and ha i is bes o buy online because i is easie and
makes hinking and wo king easie .
Mos esponden s indica ed ha AI had a signi ican impac on
hei pu chasing beha io , inding online pu chasing mo e
con enien and AI making decision-making and wo k easie . I is
in e es ing o obse e how echnology has in luenced consume
p e e ences and pe cep ions.
I 's ue ha wi hou an in e iew o ma ke esea ch we can'
igu e ou how much AI is wo h. Assessing he alue o a i icial
in elligence (AI) o en equi es de ailed esea ch, an in e iew
p ocess o ma ke analysis o uly unde s and he impac and
bene i s i b ings o a pa icula ield o indus y. The alue o AI
can a y depending on he con ex o i s applica ion, he e iciency
o i s implemen a ion, and how i bene i s use s o businesses.
Beyond simply e alua ing p ice, he alue o AI can be measu ed
by mul iple aspec s, such as:
Ope a ional e iciency: How does AI imp o e exis ing p ocesses
and ope a ions? Reducing cos s and inc easing e iciency can b ing
signi ican alue.

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127
Use Expe ience: The impac ha AI has on use o cus ome
expe ience can be measu ed by he deg ee o pe sonaliza ion, ease
o in e ac ion, and use sa is ac ion.
Re enue g ow h and inno a ion: AI can b ing alue by
acili a ing inno a ion, iden i ying new business oppo uni ies, and
gene a ing addi ional e enue by imp o ing p oduc s o se ices.
Imp o ed decision-making: I AI helps make be e and as e
decisions, i can be conside ed a signi ican added alue.
Assessing alue: AI o en equi es a complex and holis ic
app oach, conside ing he mul iple aspec s o i s use and
implemen a ion in a gi en con ex o domain. I is impo an o
conduc case s udies, impac analyzes and in e iews o ully assess
he alue ha AI b ings o a speci ic o ganiza ion o ma ke .
Hypo hesis H1: The use o a i icial in elligence in pe sonalized
ecommenda ions leads o an inc ease in he equency and a e age
alue o pu chases – alida ed
Hypo hesis H2: The con enience and accessibili y o online
shopping wi h he help o a i icial in elligence causes a signi ican
change in consume p e e ences in a o o he online en i onmen
a he expense o he o line one – alida ed
Hypo hesis H3: The use o a i icial in elligence in cus ome
suppo se ices leads o imp o ed cus ome sa is ac ion and
inc eased b and loyal y. – alida ed
Hypo hesis H4: Exposu e o dynamic p icing algo i hms causes a
change in consume beha io , including when and how hey make
pu chases. - alida ed
Hypo hesis H5: Inc easing he le el o awa eness and educa ion
ega ding he ope a ion o a i icial in elligence in luences he us
and adop ion o his echnology in he pu chase p ocess - alida ed.
As a esul , all hypo heses we e alida ed.
One o he p oblems will be ha o he i ms i hey a e all
p epa ed o mee he needs and demands o he consume s in he
ma ke o else he demand o supply o goods is g ea e han he
demand. The e o e, adap ing companies o he demands and needs
o consume s on he Romanian ma ke is an impo an aspec and
can be a c i ical ac o in hei long- e m success. In gene al, he e
a e some aspec s o conside :
Adap a ion o supply and demand:
Unde s anding consume demands: Companies need o
unde s and changes in consume beha io and p e e ences in o de
o p o ide p oduc s and se ices ha mee hei demands.
Flexibili y o o e : The abili y o quickly adjus o e s and
se ices acco ding o changes in he ma ke o consume demands
is c ucial o emain compe i i e in he ma ke .
In en o y and Supply Chain Managemen : I is impo an o
ha e e ec i e in en o y and supply chain managemen o mee
consume demand wi hou incu ing losses due o excess o
sho age o p oduc s.
In es men in echnology: Implemen ing echnologies ha suppo
a be e unde s anding o consume beha io , such as da a
analy ics, can help i ms ailo hei o e ings o ma ch demands
(Nis o eanu, 2002).
Assessmen o abili y o mee demand
Resou ces and in as uc u e: Fi ms need o ha e adequa e
esou ces and a well-de eloped in as uc u e o mee he inc eased
demand wi hou comp omising he quali y o se ices o e ed.
S a egic planning: A well-c a ed s a egic plan ha includes
assessmen and p edic abili y o u u e demand can help i ms
p epa e o mee inc eased demand.
Adap abili y and inno a ion: The abili y o quickly adap o ma ke
changes and inno a e in o e ings o s a egies can be a majo
ad an age in mee ing consume demands (P iyada shi e al., 2019).
6. Conclusions
In conclusion, he impac o a i icial in elligence on consume
beha io is p o ound and cons an ly e ol ing. While i b ings
signi ican bene i s in p o iding mo e pe sonalized and e icien
expe iences o consume s, he e is a need o ind a balance
be ween inno a ion and da a p o ec ion o main ain consume us
and loyal y. I is also essen ial ha i ms a e lexible, esponsi e o
change and ha e he abili y o adap o mee he luc ua ing
demands and needs o consume s, whe he i is demand o supply
in he ma ke .
The u u e o sales in Romania and consume s mus adap o online
shopping whe he in u al o u ban a eas. This analysis highligh s
he majo aspec s o he in luence o a i icial in elligence on
consume beha io , co e ing bo h he ad an ages and conce ns
associa ed wi h he use o his echnology in he company-
consume ela ionship. The impac o AI on consume beha io is
signi ican and di e se, wi h a - eaching consequences o he
ma ke place and shopping expe ience.
No able indings include:
Pe sonaliza ion and adap abili y: The use o AI enables he
deli e y o pe sonalized shopping expe iences based on indi idual
consume da a and p e e ences. This adap abili y leads o inc eased
cus ome sa is ac ion.
Inc ease e iciency and p ocesses: A i icial in elligence op imizes
pu chasing and ma ke ing p ocesses by p o iding mo e de ailed
in o ma ion and analysis, which can lead o mo e in o med
decisions o businesses.
Imp o ing cus ome se ice: AI-powe ed cha bo s and i ual
assis an s p o ide as and pe sonalized esponses, imp o ing he
cus ome expe ience and speeding up esolu ion o cus ome
issues.
Changing he way people buy: A i icial in elligence is in luencing
consume beha io , d i ing hem owa ds online pu chases,
especially h ough pe sonalized ecommenda ions and ease o
pu chase.
C edibili y and us : Building us wo hy algo i hms and making
AI p ocesses anspa en a e c i ical o gaining consume us in
hese echnologies.
Re olu ionizing Ma ke ing: Da a collec ed and analyzed wi h he
help o AI allows companies o adjus hei ma ke ing s a egies o
be e adap o consume needs and p e e ences.
O e all, he in eg a ion o a i icial in elligence in o ma ke ing and
sales is ha ing a signi ican impac on how consume s make
pu chasing decisions and in e ac wi h b ands. Pe sonaliza ion,
e iciency and inno a ion hus become key pilla s in o e ing an
op imized shopping expe ience gea ed owa ds indi idual needs.
Copy igh © ISRG Publishe s. All igh s Rese ed.
DOI: 10.5281/zenodo.17276153
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