Sousa, Ana Elisa; Ca doso, Paula; Dias, F ancisco
A icle
The use o a i icial in elligence sys ems in ou ism and
hospi ali y: The ou is s' pe spec i e
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Ci a ion: Sousa, Ana Elisa, Paula
Ca doso, and F ancisco Dias. 2024.
The Use o A i icial In elligence
Sys ems in Tou ism and Hospi ali y:
The Tou is s’ Pe spec i e.
Adminis a i e Sciences 14: 165.
h ps://doi.o g/10.3390/
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adminis a i e
sciences
A icle
The Use o A i icial In elligence Sys ems in Tou ism and
Hospi ali y: The Tou is s’ Pe spec i e
Ana Elisa Sousa 1, Paula Ca doso 1,2,* and F ancisco Dias 1
1School o Tou ism and Ma i ime Technology, CiTUR, Poly echnic Uni e si y o Lei ia,
2411-901 Lei ia, Po ugal; [email p o ec ed] (A.E.S.); [email p o ec ed] (F.D.)
2Labo a o y o Dis ance Educa ion and e-Lea ning, Uni e sidade Abe a, 1250-100 Lisboa, Po ugal
*Co espondence: paula.ca [email p o ec ed]
Abs ac :
A my iad o ypes o a i icial in elligence (AI) sys ems—namely AI-powe ed si e sea ch,
augmen ed eali y, biome ic da a ecogni ion, booking sys ems, cha bo s, d ones, kiosks/sel -se ice
sc eens, machine ansla ion, QR codes, obo s, i ual eali y, and oice assis an s—a e being used
by companies in he ou ism and hospi ali y indus y. How a e consume s eac ing o hese p o ound
changes? This s udy aims o add ess his issue by iden i ying he ypes o AI sys ems ha a e used by
ou is s, he pu poses hey a e used o in he p esen , and how likely hey a e o be used in he u u e.
This s udy also aims o iden i y he ypes o emo ions (posi i e s. nega i e) ha ou is s associa e
wi h he use o AI sys ems, as well as he ad an ages and disad an ages hey a ibu e o hem.
Conside ing he explo a o y na u e o he esea ch, da a we e collec ed h ough an online su ey
sha ed on social media, which was a ailable om Sep embe o Decembe 2023. Resul s show ha
mos esponden s ha e al eady used se e al AI sys ems, assign mo e ad an ages han disad an ages
o hei use, and ha he emo ions hey associa e wi h hei use a e signi ican ly posi i e. Mo eo e ,
compa ed o he small numbe o esponden s (13.7%) who associa e nega i e emo ions wi h he use
o AI sys ems, esponden s who claim o eel posi i e emo ions when using AI sys ems also e alua e
hem mo e posi i ely in e ms o hei use ulness o ou ism and hospi ali y. They iden i y mo e
ad an ages, use a g ea e di e si y o AI sys ems, and admi ha hey would use a mo e di e se
ange o AI sys ems in ou ism con ex s in he u u e.
Keywo ds:
a i icial in elligence; AI sys ems in ou ism; emo ions; pe cei ed ad an ages; pe cei ed
disad an ages; ou ism and hospi ali y
1. In oduc ion
The new indus ial e olu ion spea headed by he de elopmen s o a i icial in elli-
gence (AI) is al eady ha ing a p o ound impac on all indus ies, including ou ism and
hospi ali y (Samala e al. 2022). AI can be desc ibed as he de elopmen o compu e sys-
ems ha can pe o m asks and ac i i ies which equi e human in elligence (Russell and
No ig 2016). Al hough AI is a e y ecen esea ch opic, a 2018 s udy by Ta a Consul ancy
Se ices (TCS) al eady epo ed ha 85% o a el and ho el se ice p o ide s use AI in
hei business (Anu ag 2018).
AI has ga ne ed conside able a en ion wi hin he ou ism and hospi ali y domain
(Knani e al. 2022) and as a consequence o he massi e adop ion o AI sys ems by compa-
nies, a el planning is now easie han e e be o e. AI p o ides pe sonalized, au oma ed,
and in elligen a el se ices and makes i easie o lea n he ou is s’ beha io , choices,
and p e e ences, and o p o ide hem wi h a pe sonalized expe ience.
The p o ound change ha se ice indus ies, including ou ism, a e unde going is due
o he apid p og ess made in a wide a ie y o echnological applica ions ha inco po a e
AI, namely AI-powe ed si e sea ch sys ems, augmen ed eali y, biome ic da a ecogni ion,
booking sys ems, cha bo s, d ones, kiosks/sel -se ice sc eens, machine ansla ion, QR
Adm. Sci. 2024,14, 165. h ps://doi.o g/10.3390/admsci14080165 h ps://www.mdpi.com/jou nal/admsci
Adm. Sci. 2024,14, 165 2 o 23
codes, obo s, i ual eali y, and oice assis an s (Gajdošík and Ma ciš 2019;Knani e al.
2022;Reis e al. 2020;Samala e al. 2022). Fo example, obo s can pe o m a ious asks
in ou ism and hospi ali y, including on line se ices (Knani e al. 2022;Reis e al. 2020;
Samala e al. 2022). Vi ual a el agen s and cha bo s wi h oice ecogni ion capabili ies
can o e online in o ma ion assis ance 24 h a day, 365 days a yea (Gajdošík and Ma ciš
2019). Likewise, i ual eali y and augmen ed eali y applica ions a e used o inc ease he
isual and emo ional in ol emen o ou is s, helping o inc ease he compe i i eness o
des ina ions (Cla e ia e al. 2020;Ma asco e al. 2018).
Conside ing he implica ions o he in oduc ion o a ious AI sys ems o he ou ism
indus y, i is impo an o esea ch he pe spec i es o he end use s hemsel es: he
clien s/ ou is s. Wha is he posi ion o ou is s in he ace o he p o ound and di e se
changes aking place in he echnological ecosys em o he ou ism and hospi ali y indus y?
A e hey eage , desi ous, o a leas willing o use and adop he inno a i e solu ions made
a ailable o hem by companies? Which AI sys ems a e hey mos willing o use? And,
conside ing he whole “ ou is jou ney”, in which ac i i ies do hey ind he use o AI
sys ems mo e use ul? Wha ad an ages and disad an ages do hey associa e wi h hei
use? And how do hey eac emo ionally o he use o hese new sys ems o media ing he
ou is expe ience?
This s udy is an explo a o y app oach o his complex issue, a emp ing o asce ain
how ecep i e ou is s a e o he new AI sys ems used in ou ism and hospi ali y. In
o de o de elop he s udy, a li e a u e e iew was ca ied ou o iden i y he a ious AI
sys ems ha a e cu en ly being implemen ed in ou ism and hospi ali y, he ad an ages
and disad an ages ha ha e been men ioned in empi ical s udies on his subjec , as well as
he emo ional implica ions o using AI sys ems.
2. Li e a u e Re iew
2.1. De ining A i icial In elligence (AI)
Despi e he inc eased in e es in AI om academia, indus y, and public ins i u ions,
he e is no s anda d de ini ion o wha AI ac ually is. AI has been desc ibed by ce ain
app oaches in ela ion o human in elligence, o in elligence in gene al. John McCa hy
(2007), he men o o AI, s a es he ollowing de ini ion: “A i icial In elligence is he science
and enginee ing o making in elligen machines, especially in elligen compu e p og ams”.
Gene ally, he e m “AI” is used when a machine simula es unc ions ha humans associa e
wi h o he human minds, such as lea ning and p oblem sol ing. Ki il and A¸skun (2021)
s a e ha “AI unc ions simila ly o a human b ain as i hinks, lea ns, makes decisions and
in e ences h ough gi en da a by using in elligen machines; he main pu pose o AI is o
enable machines o comple e asks au oma ically wi hou needing a human b ain” (p. 206).
One o he majo challenges wi h hese de ini ions o AI is ha hey o en de ine AI
as machines ha beha e like humans o a e capable o ac ions ha equi e in elligence
(McCa hy 2007;Nilsson 1998;Russell and No ig 2016). As human in elligence is di icul
o measu e, he objec i e de ini ion o some hing as subjec i e as in elligence gi es he
imp ession o some hing ha is impossible o achie e (Kaplan 2016). Ne e heless, i is
impo an o dwell on how AI has been de ined in he mos ecen s udies, which ollow
he e olu ion o he concep .
Despi e he ac ha AI is desc ibed di e en ly by each au ho , he e a e poin s o
con e gence in he de ini ions p esen ed. Thus, i is unde s ood ha AI is a science ha
in ol es he use o machines, so wa e, and/o algo i hms capable o de eloping asks
au onomously and wo king wi h a la ge olume o da a in o de o p omo e he bes
decisions and he mos e icien esul s.
A i icial in elligence is commonly cha ac e ized as a collec ion o echnologies capable
o eplica ing human in elligence when add essing p oblem-sol ing asks
(Lai and Hung 2018).
Indeed, wi hin he domain o a i icial in elligence, nume ous eme ging echnologies
ha e been de eloped, playing a c ucial ole in deli e ing a no el and essen ial expe ience
o ou is s.
Adm. Sci. 2024,14, 165 3 o 23
2.2. A i icial In elligence Technologies
In he age o digi iza ion, he use o a i icial in elligence echnologies has come o be
used by mos indus ies, including he ou ism and hospi ali y sec o . These a i icial in el-
ligence echnologies allow he sec o o o e ou is s a new expe ience
(Samala e al. 2022).
Some o he AI echnologies include language ansla o s, cha bo s and i ual assis-
an s, AI-powe ed si e sea ch, kiosks/sel -se ice sc eens, i ual eali y and augmen ed
eali y, booking sys ems, biome ic da a ecogni ion, QR codes, and d ones and obo s
(Bulchand-Gidumal 2022;Dobo jeh e al. 2021;Huang e al. 2021;Samala e al. 2022;Sha ma
e al. 2022).
2.2.1. Cha bo s and Vi ual Assis an s
Con e sa ional sys ems a e some imes e e ed o as cha bo s o i ual agen s (Buhalis
e al. 2019). They in ol e echnologies such as na u al language p ocessing (NLP) and
speech ecogni ion and a e cu en ly ubiqui ous. They exis as pe sonal assis an s in
sma phones and home speake s and as ex ual cha bo s in websi es and kiosks.
Cha bo s a e ypically compu e so wa e machines, which a e p e-p og ammed o
answe he simple ques ions aised by he cus ome s (Oh e al. 2017). The e a e p ima ily
wo ca ego ies: ex -based cha bo s and oice-based cha bo s. Tex -based cha bo s p o ide
message se ices o he que ies o cus ome s in he o m o ex messages. Voice-based
cha bo s p o ide message se ices o he que ies o he cus ome s in he o m o oice-based
messages (Kuma e al. 2018).
Cha bo s and con e sa ional oice o ma s would enable isi o s o agen s o discuss
p e e ences and op ions (Yada e al. 2021). Voice-based cha bo s p o ide a high-p o ile
pe sonalized se ice o hei cus ome s. They se e he cus ome s by o e ing a wide ange
o se ices like o de ing ood se ices, cab se ices, eading ou messages, scheduling
asks and appoin men s, se ing up ala ms, oom se ices, house-keeping se ices, and
in o ming abou he ho el acili ies, among o he s. (Gajdošík and Ma ciš 2019).
2.2.2. Language T ansla o s
A i icial in elligence ha is empowe ed by machine lea ning and NLP is helping he
de elopmen o au oma ic ansla ion applica ions and simul aneous ansla ion sys ems.
Engaging in a el and ou ism ypically en ails encoun e ing di e se languages. Au oma ic
ansla ion can acili a e he ou is s’ na iga ion o he des ina ion, allowing hem o explo e
and engage in all ypes o ac i i ies.
Language ansla o s can be ex emely use ul when a elling, as hey allow a ele s
o speak in hei own language and eco d a oice message, which is hen ansla ed in o
he a ge language (local language). Then, he ansla ion is dic a ed in he a ge language,
he eby con eying he a ele s’ message o he local people (Azis e al. 2011). While
pe sonaliza ion aids ou is s in disco e ing no el loca ions (Ma asco e al. 2018), au oma ed
ansla ion can simpli y ou is s’ na iga ion o he des ina ion, enabling hem o explo e
and pa icipa e in a ious ac i i ies whe e language ba ie s could be a challenge.
2.2.3. AI-Powe ed Si e Sea ch
AI-enhanced websi e sea ch belongs o he use o a i icial in elligence echnologies
in websi e sea ch unc ionali ies o imp o e he sea ch expe ience and p o ide use s
wi h mo e p ecise and pe inen sea ch esul s. This in ol es employing sophis ica ed
algo i hms, na u al language p ocessing (NLP), machine lea ning, and o he AI echniques
o comp ehend use que ies, in e p e he con ex , and gene a e in elligen sea ch ou comes
(Me ill 2023).
This echnology makes i possible o ecei e esul s based on p e ious sea ches, which
gene ally s em om he use ’s p e e ences and needs. Thus, use s ecei e, o ins ance, p ice
upda es, a el guides, and p omo ions, among o he s, esul ing in a mo e pe sonalized
and ele an deli e y o he use o hese pla o ms.
Adm. Sci. 2024,14, 165 4 o 23
2.2.4. Vi ual Reali y and Augmen ed Reali y
Vi ual eali y (VR) echnology ypically employs VR headse s o gene a e a simula ed
en i onmen , p o iding use s wi h an imme si e i ual eali y expe ience. Th ough his
echnology, cus ome s can ex ensi ely engage wi h a h ee-dimensional, digi al wo ld,
enhancing hei o e all expe ience (Gu en ag 2010).
Vi ual eali y allows he isual p esen a ion o ou is spo s and ho el loca ions by
using 3D ideos. This echnology helps ho elie s o desc ibe hei ho el on hei websi e,
c ea e a i ual ho el ou , i ual a el expe iences, and a i ual booking in e ace (Samala
e al. 2022).
The e a e a ious i ual eali y applica ions used in he ou ism and ho el indus y. A
ew o hem a e i ual ho el ou s, i ual a el expe iences, and i ual booking in e aces.
Vi ual ho el ou s include he isual p esen a ion o he ho el en i onmen and i s acili ies
in he o m o 3D ideos. Vi ual eali y echnologies a e pe ec ga eways o a el and
explo e he unseen loca ions be o ehand.
Augmen ed eali y (AR) is a digi al echnology ha al e s an indi idual’s pe cep ion
o he physical su oundings when obse ed h ough a speci ic de ice. While sha ing
simila i ies wi h i ual eali y, AR does no subs i u e he eal-wo ld en i onmen ; ins ead,
i enhances i by supe imposing digi al elemen s (Ba en 2023).
The in eg a ion o augmen ed eali y allows ho els and compa able businesses o
deli e ins an , on-demand access o addi ional in o ma ion o hei cus ome s.
The a el sec o is ac i ely c ea ing augmen ed eali y applica ions, enabling ou is s
o use hei sma phones o ga he eal- ime in o ma ion abou buildings o landma ks by
simply poin ing he de ice a hem.
2.2.5. Biome ic Da a
Biome ic da a a e a ype o pe sonal in o ma ion ha can be used o uniquely
iden i y an indi idual. They a e usually collec ed as a pa o a digi al iden i y e i i-
ca ion p ocess. Biome ic da a can include inge p in s, oicep in s, i is scans, and acial
ecogni ion sys ems.
In he ou ism indus y, he mos widely used is ace ecogni ion. This echnology can
be used in he check-in p ocess, bo h in ho els and ai po s, bu also o coun he numbe o
people in a gi en a ea and de ec emo ions in people as hey go h ough a ce ain poin , o
ins ance, he happiness o hose lea ing he b eak as bu e (Bulchand-Gidumal 2022).
2.2.6. Robo s
A obo is an au onomous machine (a physical objec ) ha includes AI and senses
he en i onmen , bo h o which allow he obo o make decisions and pe o m ac ions
(Bulchand-Gidumal 2022).
These echnologically d i en assis an s le e age he In e ne o Things (IoT) echnology
o pe o m basic asks, such as ac i a ing bed oom ligh s, powe ing down he ele ision, au-
oma ing luggage check-in p ocesses, and welcoming gues s o a ho el
(Samala e al. 2022).
The e a e wo ypes o se ice obo s: p o essional se ice obo s and pe sonal se ice
obo s (Li e al. 2019). These obo s a e used o simpli y p ocesses and imp o e asks ha
we e no mally ca ied ou by ho el employees.
2.2.7. D ones
D ones a e unmanned, ae ial de ices used o a a ie y o pu poses (Mehme Tu˘g ul
2023). When hey we e i s de eloped, hese de ices we e manually and emo ely con-
olled. Now, howe e , d ones o en inco po a e a i icial in elligence, au oma ing some o
all o hei ope a ions.
The inco po a ion o AI enables d one endo s o use da a om senso s a ached o
he d one o collec and implemen isual and en i onmen al da a. These da a enable
au onomous o assis ed ligh , making d one ope a ion easie and inc easing accessibili y.
Adm. Sci. 2024,14, 165 5 o 23
D ones equipped wi h AI can p ocess and analyze da a in eal- ime, making hem
mo e e icien o applica ions like su eillance and moni o ing.
Wi hin he ou ism sec o , d ones can be u ilized o o e li e i ual ou s o open-space
ou is des ina ions, con ibu ing o inno a i e and en i onmen ally iendly p ac ices
(Elkhwesky e al. 2024). Ano he use o d ones is he deli e y o a se ice, o example, he
deli e y o ood o he cus ome ’s selec ed loca ion (Snead and Seible 2017).
2.2.8. Kiosks/Sel -Se ice Sc eens
The in eg a ion o a i icial in elligence (AI) ele a es sel -se ice kiosks om s a ic
machines o in elligen and in e ac i e assis an s. AI-powe ed kiosks analyze cus ome
beha io and p e e ences, enabling highly pe sonalized ecommenda ions and o e s.
A sel -se ice kiosk e e s o a e minal, allowing cus ome s o in e ac wi h a compu e
sys em o access in o ma ion. These e sa ile de ices suppo di e se unc ions, including
menu na iga ion, a el i ine a y checks, in en o y inqui ies, and mo e. Fu he mo e, hese
kiosks se e as sel -se ice checkpoin s o managing queues, in addi ion o acili a ing
o de placemen and paymen ansac ions (Vi uBox In o ech P L d. 2023).
2.2.9. Booking Sys ems
Booking sys ems wi h a i icial in elligence can help educe cos s, au oma e asks,
educe e o s, and op imize esou ces. Wha is mo e, AI can imp o e he cus ome ex-
pe ience wi h pe sonalized in e ac ions, o e s and ewa ds, as well as as e and easie
bookings. “Sma S ay”, o ins ance, is an AI-d i en ho el booking pla o m ha unde -
s ands a ele s’ p e e ences, such as ameni ies, oom ypes, and loca ions. I uses machine
lea ning o ecommend he mos sui able accommoda ion o each use , enhancing hei
o e all a el expe ience (Ba en 2023).
2.2.10. QR Codes
A QR code is a wo-dimensional ma ix ba code capable o encoding da a in ou
di e en ways: nume ic, alphanume ic, bina y, and kanji (Jaesny 2023). This ype o QR
code can be c ea ed using a simple QR code gene a o a ailable online.
Nowadays, ad anced QR code so wa e can gene a e a QR code wi h a sho URL
leading o an online page ha can hos iles like images, documen s, audio iles, and ideos.
a i icial in elligence can be an asse when in eg a ed in o QR codes, because i has he abili y
o imp o e eading accu acy and imp o e image quali y o as e ecogni ion. As i is also
able o lea n om he da a i collec s, i can de ise ways o coun e ac eading challenges.
AI can analyze no only he ex ual con en o a QR code, bu also explo e i s con ex
and unde lying meaning, hanks o na u al language p ocessing. NLP algo i hms allow AI
o be e unde s and he pu pose o a QR code. Beyond simple cha ac e ecogni ion, NLP
also analyzes he meaning and con ex o he da a (Jaesny 2023).
AI in eg a ed in o QR codes makes i possible o c ea e pe sonalized expe iences
because his echnology can analyze ou is s’ beha io and p e e ences. Ano he ad an age
o his in eg a ion is ela ed o secu i y, since AI can de ec he con en o he QR code and
wa n you i i con ains a phishing link o leads o a malicious websi e.
In he ou ism indus y, he QR code has been used o issue icke s, p o ide addi-
ional in o ma ion a ai po s, ou is si es, and accommoda ion, among o he s, and o
con ac less paymen s.
The ac ha AI is in eg a ed in o di e en echnological solu ions means ha he
simple use is o en unawa e o i s p esence. Does a QR code use ealize ha i has AI
in eg a ed? O when asked i hey would use a QR code in an AI s udy, do hey answe
a i ma i ely because hey ha e al eady used he QR code, wi hou aking AI in eg a ion
in o accoun ? The in isibili y o AI in eg a ion in di e en echnological solu ions o he
common eye can make i di icul o ecognize i s p esence and he e o e i s use.
Adm. Sci. 2024,14, 165 6 o 23
2.3. AI Sys ems in Tou ism and Hospi ali y
A i icial in elligence (AI) has ga ne ed conside able ocus wi hin he ou ism and
hospi ali y domain (Knani e al. 2022), expe iencing exponen ial g ow h in i s applica ion
wi hin his sec o in ecen yea s. The in eg a ion o obo s, a i icial in elligence (AI), and
se ice au oma ion in he hospi ali y and ou ism indus y has been le e aged o enhance
cus ome expe iences, imp o e se ice quali y, and s eamline ope a ions. S udies ha e
highligh ed he impac o AI on a ious aspec s o he indus y, such as cus ome se ice,
decision-making, and se ice eco e y (Xu e al. 2024;Kong e al. 2024;Ghesh e al. 2024).
Addi ionally, he use o AI echnologies like Cha GPT has been explo ed o applica ions in
ou ism, wi h a pa icula emphasis on he bene i s, isks, and implica ions o s akeholde s
(Ca alho and I ano 2024).
The in eg a ion o AI has enhanced se ice e iciency and op imized he o e all ou ism
expe ience. As an illus a ion, obo s ha e been employed ac oss a ious oles wi hin
he ou ism and hospi ali y sec o , including on line se ices (Reis e al. 2020). The
esea ch conduc ed by hese au ho s unde sco es he in eg a ion o obo s in he ield
o hospi ali y, encompassing asks such as ecep ion du ies, gues se ices, and cleaning.
Addi ionally, he au ho s showcase examples such as a s a iona y obo ic a m esponsible
o anspo ing and s o ing luggage, as well as he implemen a ion o ending machines
wi hin ho els o o e a ious ameni ies. Fu he mo e, obo s play a ole in anspo ing
gues s’ luggage o hei ooms. The s udies conduc ed by Reis e al. (2020), Samala
e al. (2022), and Knani e al. (2022) emphasize an addi ional applica ion o obo s wi hin
gues ooms. These obo s espond o oice commands and u ilize AI echnology such
as speech ecogni ion o manage a ious ameni ies, like con olling he ele ision, ligh s,
empe a u e, and mo e, based on gues s’ eques s. Ce ain obo s possess he abili y o
o e ins an aneous esponses o inqui ies, ecommend no ewo hy a ac ions, iden i y
he bes local es au an s and au onomously enhance hei pe o mance h ough lea ning.
No ably, wi hin ai po en i onmen s, obo s a e inc easingly being deployed as guides
and assis an s.
An al e na i e me hod o inco po a ing AI-enabled echnologies in he hospi ali y
indus y in ol es deploying i ual agen s and cha bo s. These en i ies u ilize speech
ecogni ion o assis gues s in eques ing oom se ices, o e ing online in o ma ion as-
sis ance, and ope a ing seamlessly a ound he clock, se en days a week. As p e iously
men ioned, he AI cha bo se es mul iple pu poses in a el planning, p o iding an a ay
o se ices such as a anging ood and cab se ices, eading messages aloud, scheduling
asks and appoin men s, se ing ala ms, coo dina ing oom and housekeeping se ices,
and in o ming gues s abou ho el acili ies, as indica ed by Gajdošík and Ma ciš (2019).
Fu he mo e, In an e e al. (2021) indica e ha a i icial in elligence plays a pi o al ole
in a ious se ices, wi h po en ial exclusi e applica ions in he u u e, including check-
in, check-ou , ecep ion asks, meal se ices, accommoda ion p ocedu es, ale pa king,
communica ion ia cha bo s o cha blogs o di ec in e ac ion wi h cus ome s, and he
p o ision o oom se ices di ec ly h ough mobile de ices. O he schola s also highligh
he use o AI o ac i i ies such as oom ese a ions, esponding o cus ome que ies,
add essing common issues, and p o iding assis ance wi h a ious ho el se ices. This
echnological app oach con ibu es o ailo ing he ho el gues expe ience, as emphasized
by Ci ak e al. (2021), I ano e al. (2020), and Yang and Chew (2020). Hwang e al.
(2021) unde sco e he po en ial signi icance o d ones in he ou ism and hospi ali y sec o ,
pa icula ly in esponse o he g owing need o an e icien and apid deli e y sys em, as
no ed by (Snead and Seible 2017).
A p e alen applica ion o AI in he hospi ali y indus y in ol es ha nessing i ual
eali y (VR) o c a imme si e a el expe iences h ough 360-deg ee ideo echnology.
This echnology, as highligh ed by Ci ak e al. (2021), has he capabili y o eplica e a ious
ace s o a el, spanning om he jou ney i sel o he des ina ion, showcasing key sigh s.
Addi ionally, i is employed o illus a e ou is spo s and ho el loca ions h ough 3D ideos.
Adm. Sci. 2024,14, 165 7 o 23
This echnology is ideal o p e iewing un amilia loca ions in ad ance. A i ual
booking in e ace enables cus ome s o ha e a eal- ime, simula ed walk h ough o an
ai c a , acili a ing he selec ion o sea s. Addi ionally, cus ome s can choose ancilla y
se ices such as a cab se ice and comple e he paymen p ocess, as ou lined by Samala
e al. (2022).
Using i ual eali y and augmen ed eali y applica ions p esen s a simula ed depic-
ion o au hen ic expe iences, enhancing bo h isual and emo ional engagemen . This
heigh ened engagemen con ibu es o he inc eased compe i i eness o des ina ions, mak-
ing hem mo e appealing o ou is s and ele a ing he likelihood o hei isi , as no ed by
Ma asco e al. (2018) and Cla e ia e al. (2020).
The impo ance o acial ecogni ion echnology lies in i s abili y o ecognize he
aces o ou is s, c oss- e e ence hem wi h he de ails in hei documen s, and simpli y he
check-in p ocedu e. This pionee ing me hod enables ou is s o na iga e h ough ai po
and s a ion check-ins e o lessly, e adica ing he need o manual documen e i ica ions
by au ho i ies such as immig a ion and cus oms, as highligh ed by (Samala e al. 2022).
A i icial in elligence o e s a signi ican ad an age in p o iding pe sonalized se ices
o cus ome s, which include cap u ing and s o ing hei loca ion and hei in e es s and
p e e ences online, as discussed in s udies by Yada e al. (2021), Pei and Zhang (2021), and
Samala e al. (2022).
Blockchain echnology enhances he ou is expe ience by p o iding pe sonalized
solu ions wi h minimized isks o da a misuse, g ea e use con ol wi hin a secu e ecosys-
em, ins an aneous in e na ional emi ances, dec eased exchange ansac ion cos s, and
eal- ime ansac ions, e en in emo e loca ions lacking eadily a ailable banking acili ies.
Addi ionally, he inhe en ad an ages o sma ou ism include cos -e ec i e ebooking o
ho el ooms and he elimina ion o double bookings, sol ing issues ela ed o double spend-
ing h ough he in eg a ion o all a el means on a uni ied pla o m (Va elas e al. 2019).
Tou ism and hospi ali y companies le e age AI wi h he goal o enhancing compe i-
i eness h ough he accumula ion and analysis o ex ensi e da a, as ou lined by Köseoglu
e al. (2019).
2.4. Ad an ages and Disad an ages o Use o A i icial In elligence in Tou ism and Hospi ali y
The main s udies on he use o a i icial in elligence in ou ism and hospi ali y epo
ha AI-based echnologies allow an imp o emen in he e iciency o se ices and mee ing
cus ome needs (Ci ak e al. 2021;In an e e al. 2021;G undne and Neuho e 2021;Knani
e al. 2022;Lalicic and Weismaye 2021;Pei and Zhang 2021;Samala e al. 2022;Sha ma
e al. 2022;Song e al. 2022;Zhang e al. 2022;Yada e al. 2021). A i icial in elligence also
makes i possible o pe sonalize and en ich cus ome expe iences (Knani e al. 2022;Lalicic
and Weismaye 2021;Pei and Zhang 2021;Samala e al. 2022;Zhang e al. 2022;Yada e al.
2021), since mo e cu en and eal in o ma ion abou each cus ome can be ob ained and
hei needs can be me in a mo e di ec and conc e e way, o e ing he p oduc s/se ices
hey a e looking o and need (Knani e al. 2022;Samala e al. 2022).
Fo hospi ali y and ou ism wo ke s, AI can be an asse in he sense ha i akes away
he espec i e and s anda dized wo k ha some machines o obo s can pe o m (Sha ma
e al. 2022) and hus, s a can ocus hei a en ion on o he ac i i ies and on he cus ome
expe ience (In an e e al. 2021;Samala e al. 2022), as hey can ha e mo e ime and ene gy o
p o ide pe sonalized se ices (Song e al. 2022). By eeing up s a o o he mo e complex
ac i i ies and mo e cus ome in e ac ion, i is hen possible o o e mo e pe sonalized
se ices, adap ed o he cus ome and wi h be e quali y (Song e al. 2022), as i allows
hem o o e a mo e humanized se ice (Pei and Zhang 2021).
The applica ion o AI can also help imp o e alue co-c ea ion (Knani e al. 2022) and
c ea e alue o cus ome s by de eloping inno a i e se ices ha ha e se e al ad an ages,
such as con enience, ime e iciency, ubiqui y (always a ailable), se ice, unc ionali y,
ease o use, be e han o he cu en o ma s ( ela i e ad an age), and a high le el o
pe sonaliza ion and lexibili y (Lalicic and Weismaye 2021).
Adm. Sci. 2024,14, 165 8 o 23
Fo ou is s, one o he main bene i s o using a i icial in elligence is being able o
na iga e unknown en i onmen s wi hou ea and anxie y, as hey bene i om he help o
AI. This can help de elop new memo able expe iences (Li e al. 2019).
On he o he hand, he main isks o using AI ha ou is s ha e iden i ied a e ela ed
o ea o su eillance, lack o equal access o all, and a socie y en i ely dependen on AI.
In he ini ial scena io, conce ns a ise ega ding he po en ial p i acy h ea s posed
by AI sys ems, as hey accumula e ex ensi e da a ha can disce n pa e ns and ex ac
in o ma ion om he ga he ed da ase s (G e zel 2011;Tussyadiah and Mille 2019). In
a socie y wi hou equal access o echnologies, hei use can be jeopa dized by a lack o
knowledge and skill in using AI. Also, he ea o human labo being eplaced by machines
means ha he e is a ea o job losses (Li e al. 2019).
Al hough his in elligence has inc eased he e iciency o ansac ions o some ex en ,
he main s udies on he use o a i icial in elligence sys ems in ou ism and hospi ali y
epo ha p i acy, secu i y, and da a managemen issues a e he main conce ns (In an e
e al. 2021;Knani e al. 2022;Samala e al. 2022;Yada e al. 2021;Hawli schek e al. 2018).
I is also necessa y o conside p oblems o us in in e media ies. Some s udies also poin
ou he alue o he in es men as a disad an age, which is expensi e and complex (In an e
e al. 2021;Yada e al. 2021).
Ano he majo disad an age o he use o a i icial in elligence sys ems in ou ism
and hospi ali y is ha , when compa ed o humans, obo s, e en wi h he inco po a ion o
AI echnologies, a e s ill e y limi ed in e ms o so skills such as empa hy—an essen ial
compe ence o mee cus ome needs—and communica ion, which may lead o inco ec
o misleading in o ma ion (In an e e al. 2021;Reis e al. 2020). Acco ding o Chan and
Tung (2019), se ice obo s p o ide high le els o senso y and in ellec ual expe iences, bu
low le els o a ec i e expe ience. As a consequence o hese disad an ages, ano he one
a ises, which is he isk o ce ain ypes o posi ions and posi ions being equi ed om
s a (In an e e al. 2021). Despi e he apid e olu ion o a i icial in elligence, a signi ican
cons ain pe sis s in i s adop ion by indi iduals lacking digi al li e acy skills (Reddy 2006;
Samala e al. 2022).
A s udy conduc ed by Lalicic and Weismaye (2021) ein o ces he a o emen ioned
disad an ages. When asked by he au ho s o indica e he easons why hey would no
use AI cha bo s in hei ip planning, he op ou easons indica ed by ou is s we e as
ollows: “di icul y o use”; “lack o con idence in AI echnology”; “p i acy conce ns”; and
he “need o pe sonal in e ac ion”.
Recen esea ch on AI iden i ies po en ial nega i e impac s, such as employees’ ea o
losing hei jobs, changing employee oles and asks, and educed social in e ac ions (Li
e al. 2019;Reddy 2006). These ac o s may esul in inc eased employee s ess and anxie y,
nega i e a i udes, lack o us , educed p oduc i i y, and co-des uc ion o alues (Yada
e al. 2021;Pe ei a e al. 2021).
Al hough a i icial in elligence sys ems ha e bene i s, bo h mone a y, by eplacing
employees, and non-mone a y, by p o iding a unique cus ome expe ience, hey canno
ye su pass human in elligence, as AI is s ill an eme ging a ea (Lau en e al. 2015;Samala
e al. 2022). Fu he mo e, cha bo s a e cu en ly s ill limi ed, as hey can only answe
simple ques ions (Samala e al. 2022). Mo eo e , when he e is an eme gency and a
complex p oblem o be sol ed, cus ome s s ill p e e pe sonal in e ac ion (Li e al. 2019;
Samala e al. 2022).
G undne and Neuho e (2021) p opose a heo e ical model called ‘The Realms o
AI Tou is Expe iences’. The model has wo axes: he i s ep esen s he axis o posi i e
and nega i e alue o ma ion, mani es ed as alue co-c ea ion and alue co-des uc ion.
The second axis shows AI in e ac ion and co-c ea ion, as well as AI and he ou is expe-
ience, whose op laye consis s o h ee sub-dimensions: in o ma ion, pe sonaliza ion,
and in eg a ion.
Thus, he au ho s’ s udy (G undne and Neuho e 2021) highligh s he impac o
a i icial in elligence on he ou is expe ience in he in o ma ion sub-dimension, s a ing ha
Adm. Sci. 2024,14, 165 15 o 23
a ac ions (54.6%), and anspo a ion (50%). The ollowing ac i i ies show mo e mod-
es use a es: ou guides (33.1%), ou ope a o s (26.2%), and a el agencies (23.5%).
When compa ing gende s, he e is only one s a is ically signi ican di e ence in ela ion
o ca e ing: emale esponden s use AI sys ems mo e o en han male esponden s in
ca e ing/ es au an s (63.8% s. 45%).
Rega ding he ime when AI sys ems a e used du ing he ou is expe ience, some
esponden s say hey a e used “be o e he ip” (38.1%) and o he s say hey a e used
“du ing he ip” (33.8%). Howe e , an e en g ea e numbe o esponden s epo ed using
hem “a all s ages o he ip” (47.3%). Howe e , only 1.5% o esponden s explici ly
men ion using AI “a e he ip”.
Rega ding he ypes o ac i i ies in which esponden s plan o use AI in he u u e,
ou indings show ha AI is seen as mo e ele an in hose ac i i ies ha con ibu e mo e
di ec ly o a el planning and/o se e as acili a o s/op imize s o he ou is expe ience,
namely “ ansla ing om o he languages” (74.6%), “using maps/na iga ion sys ems”
(68.8%), “planning i ine a ies” (66.5%), and “making a el ese a ions” (56.2%).
I is impo an o no e ha he p edisposi ion o use AI sys ems in he u u e is much
s onge among emale esponden s. Women mo e equen ly designa e hei in en ion
o use AI sys ems in he ollowing con ex s: “ ansla ion in o o he languages” (78.8% s.
68.0%), “use o maps/na iga ion sys ems (74.4% s. 60.0%), “ a el booking” (61.9% s.
47.0%), “pe sonalized ecommenda ions” (41.3% s. 28.0%), and “pho o and ideo cap u e”
(36.9%). In con as , male esponden s epo a g ea e endency o use AI sys ems when
“ isi ing ou is a ac ions” (58.1% s. 30.0%).
4.3. Pe cep ions and Emo ions Rela ed o AI Sys ems in Tou ism and Hospi ali y
Wi h ega d o he ad an ages and disad an ages associa ed o he use o AI sys ems
in ou ism and hospi ali y (Table 4below), i can be no ed ha esponden s iden i y he
ollowing as he main ad an ages: “ease o access o in o ma ion” (80%), which clea ly
s ands ou , along wi h “simple booking p ocesses” (45%) and “sho e wai ing imes”
(38%). O he ad an ages ela ed o he quali y o he ou is expe ience a e men ioned less
equen ly, namely “mo e e icien se ices” (21.9%), a “be e ou is expe ience o e all”
(16.9%), “mo e e icien communica ion” (16.2%), wi h “mo e pe sonalized in o ma ion”
(14.6%), and “mo e accu a e and comple e in o ma ion” (13.8%). When compa ing he
gende s o he esponden s, he e we e no s a is ically signi ican di e ences.
I is impo an o no e ha when compa ing he ad an ages and disad an ages o using
a i icial in elligence sys ems in ou ism and hospi ali y, he esponden s men ioned he
ad an ages much mo e o en. Among he disad an ages, he p oblems o “da a p i acy and
secu i y” (52.3%) and “high dependence on echnology” (40.8%) clea ly s and ou . “Loss
o au hen ici y” (25.4%), “ ulne abili y o cybe a acks” (25.0%), and “possible echnical
p oblems” (15.8%) a e also on he lis o disad an ages ecognized by esponden s. Wi h
ega d o gende di e ences, male esponden s seem o be mo e app ehensi e han emale:
he o me mos equen ly iden i y he op ions “loss o au hen ici y”, “e hical issues”, and
“dec ease in human in e ac ion”. On he o he hand, emale esponden s mos equen ly
iden i y echnical issues, namely “ ulne abili y o cybe a acks” and “di icul y in using
AI solu ions”.
The esponden s’ o e all op imism ega ding he bene i s o using AI in ou ism and
hospi ali y ( he idea ha he ad an ages ou weigh he disad an ages) is consis en wi h
hei answe s o he ques ion “How do you eel when in e ac ing wi h A i icial In elligence
solu ions?”. Responden s had o choose one ou o nine emo ions, i e o which we e
nega i e (bo ed; melancholic; despe a e; dissa is ied; ang y) and ou posi i e ( elaxed;
hope ul; sa is ied; amused). As shown in Table 3, only 8.8% o esponden s associa e a
nega i e emo ion wi h he use o a i icial in elligence, compa ed o 86.2% who indica e
posi i e emo ions, namely “sa is ied” (53.5%), “amused” (15.4%), “hope ul” (10%), and
“ elaxed” (7.3%). I should be no ed ha he le el o sa is ac ion wi h he use o AI is mo e
equen among emale esponden s (58.8%) compa ed o male esponden s (45%).
Adm. Sci. 2024,14, 165 16 o 23
Table 4. Pe cep ions and emo ions associa ed wi h he use o AI in ou ism and hospi ali y (%).
To al
Sample
Female
(n = 160)
Male
(n = 100) χ2Sig.
Ad an ages o AI solu ions
Quick access o use ul in o ma ion 80.0 83.1 75.0 2.54
0.111
Simple p ocesses 45.0 45.0 45.0 0.00
1.000
Sho e wai ing/se ice imes 38.5 40.0 36.0 0.42
0.519
Mo e e icien se ices 21.9 21.9 22.0 0.01
0.981
Be e ou is expe ience 16.9 14.4 21.0 1.92
0.166
Mo e e icien communica ion 16.2 15.0 18.0 0.41
0.523
Mo e pe sonalized in o ma ion 14.6 16.9 11.0 1.70
0.192
Mo e accu a e and comple e in o ma ion 13.8 18.8 14.0 0.01
0.955
Be e quali y o se ice 9.6 9.4 10.0 0.03
0.868
Disad an ages o AI solu ions
Da a p i acy and secu i y 52.3 54.4 49.0 0.71
0.399
High dependence on echnology 40.8 43.1 37.0 0.96
0.328
Loss o au hen ici y 25.4 21.3 32.0 3.76
0.053
Vulne abili y o cybe a acks 25.0 28.7 19.0 3.12
0.077
Mo e echnical p oblems 15.8 16.3 15.0 0.07
0.788
Di icul y using AI solu ions 7.3 10.6 2.0 6.76
0.009
Lack o anspa ency 6.2 5.0 8.0 0.96
0.327
E hical issues 5.4 2.5 20.0 6.99
0.030
Dec ease in human in e ac ion 5.4 2.5 20.0 6.99
0.030
Takes oo long o use 2.3 1.3 4.0 2.06
0.151
Nega i e emo ions ela ed o he use o AI
1. Bo ed 4.6 3.8 6.0 0.71
0.400
2. Melancholic 1.2 1.3 1.0 0.03
0.854
3. Despe a e 1.2 0.6 2.0 1.02
0.312
4. Dissa is ied 0.8 0.0 2.0 3.23
0.073
5. Ang y 1.2 1.3 1.0 0.03
0.854
Nega i e emo ions (1 + 2 + 3 + 4 + 5) 8.8 6.9 12.0 0.20
0.157
Posi i e emo ions ela ed o he use o AI
6. Relaxed 7.3 6.3 9.0 0.69
0.407
7. Hope ul 10.0 8.8 12.0 0.72
0.395
8. Sa is ied 53.5 58.8 45.0 4.68
0.031
9. Amused 15.4 13.8 18.0 0.85
0.355
Posi i e emo ions (6 + 7 + 8 + 9) 86.2 87.5 84.0 0.63
0.427
To summa ize, his s udy shows ha he use o AI in ou ism and hospi ali y is
cu en ly e y well accep ed by he ou is s su eyed, and is undamen al in ou ism
ma ke ing, bo h as a esea ch ool on ou is des ina ions and p oduc s, as well as a
communica ion ool and acili a o o ou is expe iences. The pe cei ed ad an ages
o using AI a ou weigh i s disad an ages and i s use induces p edominan ly posi i e
emo ions in i s use s.
Table 5below summa izes he esponden s’ deg ee o in ol emen in using AI sys ems,
concep ualized as he a e age numbe o i ems iden i ied by esponden s in esponse o ou
ques ions: “Numbe o di e en AI solu ions al eady used”, “Numbe o di e en ac i i ies
in which I would use AI”, “Numbe o ad an ages o using AI solu ions”, and “Numbe o
disad an ages o using AI solu ions”. Only in he a iable “Numbe o di e en ac i i ies
in which I would use AI” is he e a signi ican mean di e ence be ween gende s: emale
esponden s show a p opensi y o use AI sys ems in a g ea e numbe o ac i i ies in he
con ex o he ou is expe ience han male esponden s (M = 5.29 s. M = 4.29).
As shown in Table 6below, he expe ience o using AI sys ems is posi i ely co ela ed
wi h he p opensi y o use AI in di e en ou is ac i i ies ( = 0.47, p< 0.001), and bo h o
hese a iables a e posi i ely co ela ed wi h he numbe o ad an ages associa ed wi h i s
use ( espec i ely: = 0.28, p< 0.001 and = 0.32, p< 0.001).
Adm. Sci. 2024,14, 165 17 o 23
Table 5. Deg ee o in ol emen in using AI sys ems.
O e all
Means
Female
Means
Male
Means Sig.
No. o AI solu ions al eady used 4.80 4.84 4.72 0.37 0.714
No. o ac i i ies in which I would use AI 4.90 5.28 4.29 3.14 0.002
No. o ad an ages o using AI solu ions 2.57 2.59 2.52 0.73 0.465
No. o disad an ages o using AI solu ions
3.64 3.50 3.81 1.74 0.083
Table 6.
Co ela ions be ween he a iables numbe o AI sys ems al eady used, numbe o ac i i ies
in which you would use AI, numbe o ad an ages, and numbe o disad an ages.
1 2 3 4
1. No. o AI solu ions al eady used 1.00
2. No. o ac i i ies in which I would use AI 0.47 ** 1.00
3. No. o ad an ages o using AI solu ions 0.28 ** 0.32 ** 1.00
4. No. o disad an ages o using AI solu ions
0.02 0.12 0.18 ** 1.00
** Co ela ion is signi ican a 0.001 le el.
AI sys ems ha e eme ged in he con ex o he digi al ecosys em, so i is e y plausible
ha he le el o digi al li e acy o consume s/ ou is s di ec ly in luences hei beha io
and a i udes owa ds using hese sys ems. This s udy does no di ec ly include he “digi al
li e acy” a iable, bu i does include h ee sociodemog aphic a iables ha a e di ec ly
associa ed wi h i , namely “age”, “schooling”, and “income le el”.
In he ligh o he da a p esen ed in Table 7below, we can say ha “age” has a
signi ican e ec on he numbe o ac i i ies in which esponden s admi hey could use AI
and on he numbe o disad an ages associa ed wi h AI sys ems. Speci ically, i is young
esponden s unde he age o 27 who epo he lowes numbe o ac i i ies in which hey
plan o use AI sys ems; howe e , i is esponden s in he 43–58 age b acke who associa e
he highes numbe o disad an ages wi h he use o AI.
Table 7. E ec s o he “Age” a iable.
Up o 27
(n = 103)
27–42
(n = 49)
43–58
(n = 96)
>58
(n = 14) Z Sig.
Pe cep ion o IA use ulness in T&H 3.80 4.16 3.88 3.64 1.89 0.132
No. o AI solu ions al eady used 4.73 5.27 4.67 4.50 0.74 0.530
N. o ac i i ies in which I would use AI 4.29 5.44 5.23 5.21 3.57 0.015
No. o ad an ages o using AI solu ions 2.58 2.65 2.55 2.29 0.81 0.489
No. o disad an ages o using AI solu ions 3.44 3.35 4.01 3.50 3.65 0.013
Rega ding he e ec o he “educa ion” a iable (Table 8), i is no iceable ha he
“Numbe o AI solu ions al eady used” a iable shows highe alues among he espon-
den s wi h a uni e si y deg ee and pos -g adua es (means o 5.15 and 4.99 espec i ely)
han among he esponden s wi h only seconda y educa ion (3.81). I is possible o obse e
a simila esponse pa e n ega ding he “Numbe o ac i i ies in which you would use AI”
a iable: he highe he educa ional le el, he mo e ou is ac i i ies he esponden s admi
ha hey would use AI wi h in he u u e.
Table 8. E ec s o he “Educa ion” a iable.
Seconda y
(n = 58)
Uni. Deg ee
(n = 111)
Pos -g adua e
(n = 93) Z Sig.
Pe cep ion o IA use ulness in T&H 3.79 3.84 4.03 1.46 0.235
No. o AI solu ions al eady used 3.81 5.15 4.99 6.17 0.002
N. o ac i i ies in which you would use AI 3.95 5.11 5.25 5.71 0.004
No. o ad an ages o using AI solu ions 2.55 2.64 2.49 0.87 0.419
No. o disad an ages o using AI solu ions 3.53 3.45 3.93 3.05 0.049
Adm. Sci. 2024,14, 165 18 o 23
Las ly, he “Income” a iable (Table 9) has a signi ican e ec on he esponses o wo
a iables: “Pe cei ed use ulness o AI in Tou ism and Hospi ali y” and “No. o ad an ages
a ibu ed o AI”. Bo h ha e highe a e ages in he “EUR 1001–2000” income b acke and
lowe a e ages in he “EUR < 500 ” b acke .
Table 9. E ec s o he “Income” a iable.
EUR < 500
(n = 38)
EUR 501–1000
(n = 70)
EUR 1001–2000
(n = 109)
EUR 2001–4000
(n = 20) Z Sig.
Pe cep ion o IA use ulness in T&H 3.68 3.73 4.09 3.75 2.85 0.038
No. o AI solu ions al eady used 4.53 4.63 5.12 4.80 0.80 0.495
N. o ac i i ies in which you would use AI 4.55 4.99 5.15 5.30 0.63 0.600
No. o ad an ages o using AI solu ions 2.29 2.54 2.69 2.40 2.65 0.049
No. o disad an ages o using AI solu ions
3.32 3.67 3.81 3.85 1.18 0.319
In he ligh o hese da a, we can say ha he h ee sociodemog aphic a iables only
pa ially co obo a e he hypo heses ha he highe he le el o educa ion and income, and
he lowe he age, (a) he lowe he use o AI sys ems, (b) he g ea e he p opensi y o
use hem in a wide ange o ou is ac i i ies, (c) he g ea e he numbe o ad an ages
associa ed wi h hei use and, con e sely, (d) he lowe he numbe o disad an ages
a ibu ed o hem.
I was men ioned p e iously ha esponden s ha e a e y posi i e iew o he use ul-
ness and ad an ages o using AI in ou ism and hospi ali y and ha his iew is concomi an
wi h he exp ession o posi i e emo ions du ing i s use. The e o e, in o de o es he
hypo hesis ha he e is a s ong connec ion in consume / ou is beha io be ween he
emo ions expe ienced by esponden s du ing he use o AI sys ems and he o he con-
s uc s o his s udy (pe cei ed use ulness, pe cei ed ad an ages, equency o use, and
p edisposi ion o he use AI in di e en ac i i ies), we compa ed he a e ages be ween he
g oup o esponden s who epo ed eeling nega i e emo ions (n = 36) and he esponden s
who epo ed posi i e emo ions (n = 226).
As Table 10 below shows, he di e ences a e qui e clea . Compa ed o esponden s who
epo nega i e emo ions, he majo i y o esponden s who epo posi i e emo ions ha e a
mo e posi i e pe cep ion o he use ulness o AI in ou ism and hospi ali y
(4.60 s. 2.97),
use o ha e used a g ea e numbe o AI solu ions (4.92 s. 4.90), admi o using AI in
a g ea e numbe o ac i i ies (5.15 s. 3.33), and associa e i wi h a g ea e numbe o
ad an ages (2.69 s. 1.81).
Table 10. E ec s o emo ions (posi i e and nega i e).
Global
Mean
Posi i e
Emo ions
(n = 226)
Nega i e
Emo ions
(n = 36)
Sig.
Use ulness o AI in ou ism and hospi ali y 3.90 4.60 2.97 7.33 0.000
No. o AI solu ions al eady used 4.78 4.92 4.00 2.90 0.003
No. o ac i i ies in which you would use AI 4.90 5.15 3.33 4.71 0.000
No. o ad an ages a ibu ed o AI 2.57 2.69 1.81 8.45 0.000
No. o disad an ages a ibu ed o AI 3.64 3.60 3.83 0.82 0.414
Finally, he e a e he e hical issues inhe en o using AI solu ions. When ques ioned
di ec ly on he subjec , only 27.3% o esponden s admi ed o he exis ence o associa ed
e hical p oblems (see Table 11), wi h no s a is ically signi ican di e ences in esponses
based on gende .
Responden s who belie e he e a e e hical p oblems in using AI solu ions (27.3%
o o iginal sample) we e asked o lis he e hical p oblems hey had in mind, which a e
summa ized in Table 12. The mos ele an conce ns we e, on he one hand, he o eseeable
impac o AI on ede ining labo ela ions and he ex inc ion o many jobs ( he classic p ob-
Adm. Sci. 2024,14, 165 19 o 23
lem always inhe en o any echnological e olu ion), and on he o he hand, he p oblems
o p i acy, da a p o ec ion, and con iden iali y, he la e being a ela i ely ecen p oblem
which a ose in he 21s cen u y and could jeopa dize ci izens’ cons i u ional eedoms.
Table 11. E hical p oblems wi h he use o AI solu ions in ou ism and hospi ali y.
To al Sample Female (n = 160) Male
(n = 100) χ2Sig.
Yes, AI poses e hical p oblems 27.3 26.3 29.0 0.23
0.628
Table 12. Responden s’ spon aneous esponses o e hical p oblems.
# E hical P oblems A ising om he In oduc ion o AI in Tou ism and Hospi ali y
27 Job cu s and loss o labo igh s
16 P i acy, da a p o ec ion and con iden iali y
5 Lack o pe sonal con ac and lack o empa hy
3 Manipula ion o in o ma ion
3 Reduc ion in consume igh s
3 Loss o au hen ici y
3 Dis espec o human digni y
2 Disc imina ion
2 Viola ion o hi d-pa y in ellec ual p ope y igh s
2 Consume manipula ion
5. Conclusions
One o he main objec i es o he cu en esea ch was o iden i y he ypes o a i icial
in elligence sys ems used by ou is s and he pu poses hese a e used o in he p esen .
Wi h he da a ob ained, we a e able o conclude, simila ly o wha was concluded by
au ho s such as Gajdošík and Ma ciš (2019), In an e e al. (2021), Ci ak e al. (2021), I ano
e al. (2020), Yang and Chew (2020), and Samala e al. (2022), ha he sampled ou is s
use a mul i ude o AI- ela ed sys ems, namely QR codes, au oma ic ansla ion, cha bo s,
and oice assis an s. Also, simila o he p e ious au ho s’ conclusions, hese se ices a e
used o a mul i ude o pu poses in he di e en s ages o he ip (be o e, du ing and
a e he ip), mainly allowing ou is expe iences o be ailo ed o hei di e se needs
and p e e ences.
A second goal o he esea ch was o iden i y he ypes o emo ions ha ou is s
associa e wi h he use o AI sys ems, as well as he ad an ages and disad an ages hey
a ibu e o hem. Judging by he da a ob ained in his s udy, we may conclude ha he
in oduc ion o AI sys ems o ou ism and hospi ali y can be pe cei ed a o ably by ou is s.
This s udy epo s a high p edominance o posi i e emo ions o e nega i e ones. In ac ,
he numbe o esponden s who associa e a posi i e emo ion wi h he use o AI (n = 226,
i.e., 86.3%) is immeasu ably highe han he numbe o esponden s who associa e nega i e
emo ions wi h his p ac ice (n = 36; 13.7%). Fo mos esponden s, he use o AI sys ems
in ou ism and hospi ali y makes hem eel sa is ied (53.5%), amused (15.4%), hope ul
(10%), o elaxed (7.3%). Only a small numbe o esponden s eel uncom o able wi h
he inno a ions in oduced by AI in ou ism and hospi ali y. Fu he mo e, as migh be
expec ed, his s udy also shows ha hose who associa e posi i e emo ions wi h he use
o AI sys ems no only ind hem mo e use ul and a ibu e mo e ad an ages o hem, bu
also use hese echnologies mo e widely and a e mo e p edisposed o using hem in a mo e
di e se ange o ou is se ices.
Ano he ele an inding o his s udy is ha esponden s associa e mo e ad an ages
han disad an ages o he use o AI sys ems in ou ism and hospi ali y. The main pe cei ed
ad an ages include quick access o use ul in o ma ion, simple p ocesses, sho e wai ing
imes and mo e e icien se ices. In o he wo ds, pe cei ed use ulness, p agma ism and
e ec i eness a e he main easons o using AI sys ems in ou ism and hospi ali y, om
a ou is s’ pe spec i e. On he o he hand, he main ac o s ha end o inhibi he use o
Adm. Sci. 2024,14, 165 20 o 23
AI sys ems in ou ism and hospi ali y a e da a p i acy and secu i y, high dependence on
echnology, loss o au hen ici y, and ulne abili y o cybe a acks. In o he wo ds, some
o he main pe cei ed disad an ages o using AI sys ems in ou ism and hospi ali y can
also be o e come i he o ganiza ions supplying AI echnologies o e gua an ees o g ea e
da a secu i y and p i acy.
S ill, on he subjec o he disad an ages o using AI sys ems in ou ism and hospi ali y,
i should be no ed ha only 5.4% o esponden s iden i ied “e hical issues” as one o he
disad an ages. Howe e , he pe cen age o a i ma i e answe s o “Do you hink ha he
use o AI solu ions in Tou ism and Hospi ali y poses e hical p oblems?” was signi ican ly
highe (27.3%). I can hus be concluded ha mo e han wo- hi ds o esponden s do
no associa e any e hical p oblems wi h he use o AI sys ems in ou ism and hospi ali y
and only a small p opo ion o he mino i y o esponden s who ecognize ha he e
a e e hical p oblems (i.e., 5.4%) conside e hical p oblems o be a disad an age o using
AI sys ems in ou ism and hospi ali y. I is also signi ican ha he main ype o e hical
p oblem, spon aneously indica ed by 27 esponden s (“job cu s and loss o labo igh s”),
canno e en be conside ed an e hical p oblem in he s ic sense, bu a he a challenge ha
echnological inno a ion poses o he labo ma ke .
Also no ewo hy is he ac ha hose wi h highe le els o educa ion use AI solu ions
mo e in ensi ely and a e mo e p edisposed o adop ing hem in a mo e di e se ange o
ou ism ac i i ies in he u u e. This s udy he e o e p o ides use ul clues o ou ism and
hospi ali y en ep eneu s and companies, encou aging hem o in es in he echnological
mode niza ion o hei p oduc ion p ocesses by in oducing AI sys ems in he cus ome
in e ace, since consume s ( ou is s) a e clea ly p edisposed o inco po a ing hese sys ems,
conside ing hem globally as a means o op imizing he consume expe ience.
The implica ions o unde s anding people’s emo ional eac ions o AI wi h mind-
like cha ac e is ics a e mul i ace ed and span ac oss se e al domains, including e hical
design, he philosophy o mind, social in e ac ions, as well as he psychological and mo al
consequences. Unde s anding emo ional eac ions can guide designe s in c ea ing AI
sys ems ha a e mo e accep able and less likely o cause ea o discom o among use s.
This could in ol e designing AI wi h ce ain emo ional exp essi eness o human-like
cha ac e is ics o os e us among ou is s. Fu he mo e, unde s anding emo ional
esponses can shape he de elopmen o social obo s and i ual assis an s, ensu ing
ha hey in e ac in ways ha a e socially and emo ionally app op ia e, os e ing posi i e
human–AI ela ionships.
Employmen issues we e also a main conce n and he ea o job displacemen due o
AI is a classic conce n wi h echnological ad ancemen s. The implica ions include he need
o policies ha add ess wo k o ce ansi ion, e aining p og ams, and economic measu es
o mi iga e he impac on displaced wo ke s.
Con e sely, conce ns abou p i acy, da a p o ec ion, and con iden iali y emphasize he
need o obus legal and egula o y amewo ks, which include upda ing and en o cing
da a p o ec ion laws o ensu e ha AI sys ems handle pe sonal da a esponsibly; ensu -
ing ha AI sys ems ope a e anspa en ly, wi h clea accoun abili y o da a b eaches o
misuse; and building and main aining public us in AI sys ems h ough e hical p ac ices
and anspa ency.
O e all, hese implica ions highligh he impo ance o conside ing emo ional, e h-
ical and social ac o s in he de elopmen and deploymen o AI echnologies, namely
in he ou ism and hospi ali y sec o , o ensu e hey bene i socie y while minimizing
po en ial ha ms.
Au ho Con ibu ions:
Concep ualiza ion, A.E.S. and P.C.; me hodology, F.D., A.E.S. and P.C.; so -
wa e, F.D.; alida ion, A.E.S. and P.C.; o mal analysis, F.D.; in es iga ion, P.C., A.E.S. and F.D.;
esou ces, P.C.; da a cu a ion, A.E.S.; w i ing—o iginal d a p epa a ion, P.C., A.E.S. and F.D.;
w i ing— e iew and edi ing, P.C., A.E.S. and F.D.; isualiza ion, F.D.; supe ision, F.D.; p ojec
adminis a ion, P.C.; unding acquisi ion, F.D. and A.E.S. All au ho s ha e ead and ag eed o he
published e sion o he manusc ip .
Adm. Sci. 2024,14, 165 21 o 23
Funding:
This esea ch was unded by Eu opean unds h ough Agenda ATT—PRR (Reco e y and
Resilience Plan), wi hin he scope o he p ojec FAST (Tools o Suppo ing Sus ainabili y in Tou ism),
de eloped by CITUR. h ps://doi.o g/10.54499/UIDB/04470/2020 (accessed on 28 July 2024).
Ins i u ional Re iew Boa d S a emen : No applicable.
In o med Consen S a emen : No applicable.
Da a A ailabili y S a emen : Da a a e con ained wi hin he a icle.
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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