INTERNATIONAL JOURNAL OF MULTIDISCIPLINARY RESEARCH AND ANALYSIS
ISSN(p in ): 2643-9840, ISSN(online): 2643-9875
Volume 08 Issue 10 Oc obe 2025
DOI: 10.47191/ijm a/ 8-i10-28, Impac Fac o : 8.266
Page No. 5788-5797
IJMRA, Volume 08 Issue 10 Oc obe 2025 www.ijm a.in Page 5788
Adop ion o A i icial In elligence in Nige ian Ho els: A Pa hway o Enhanced
Cus ome Expe ience and Ope a ional E iciency
NWEKE, Chiedozie Cyp ain1, P o . D . Dhaki Abbas Ali2
1Lincoln Uni e si y College, Malaysia
2Depu y Dean o Pos g adua e S udies.
ABSTRACT: The adop ion o A i icial In elligence (AI) in he ho el indus y in Nige ia has expe ienced d ama ic g ow h o e he
yea s in di e en a eas, including echnology. The in eg a ion o echnology has o ally changed cus ome expe ience and
ope a ional e iciency. The applica ion o AI in he ho el indus y comes wi h bene i s and challenges, wi h emphasis on bo h
cus ome expe ience and ope a ional e iciency. The oles o AI in he ho el indus y includes enhanced cus ome se ice,
ope a ional e iciency, pe sonal expe ience, e enue managemen , and secu i y and sa e y. Applica ions o AI in he ho el indus y
includes cha bo s and i ual assis an , sma ooms and pe sonalized expe ience, and au oma ed check-ins and check-ou s. The
impo ance o cus ome expe ience impac s he ho els epu a ion, p o i abili y and compe i i e s anding, and ac o s in luencing
i includes se ice quali y, echnology and con enience, cleanliness and com o , pe sonaliza ion, and secu i y and sa e y.
Ope a ional key indica o s a e cos managemen , s a p oduc i i y, gues sa is ac ion sco e, au oma ion and echnology
u iliza ion, supply chain and in en o y managemen , and ene gy and esou ce e iciency. The challenges o ope a ional e iciency
in Nige ian ho els includes high ope a ional cos , skills gap and wo k challenges, limi ed adop ion o echnology, inconsis en
powe supply, and supply chai dis up ion. The ac o s impac ing adop ion o AI a e cos , in as uc u e and echnology eadiness,
egula o y and da a p i acy conce ns, echnical expe ise o skills gaps, cus ome accep ance and us . The bene i s o AI
in eg a ion include compe i i e ad an age and inno a ion, da a d i en decision making, enhanced cus ome se ice and
pe sonaliza ion, enhanced secu i y and sa e y, imp o ed e enue managemen , and inc eased ope a ional e iciency. A quali a i e
me hodology app oach in o m o sys ema ic e iew has been used. Findings and esul s clea ly shows he e a e only a hand ul o
ho els using AI powe ed solu ions, bu he e is high po en ial o imp o emen in he indus y.
KEYWORDS: Cus ome Expe ience, Ope a ional E iciency, Vi ual Assis an s, Facial Recogni ion, Se ice Quali y, Secu i y and
Sa e y, Supply Chain
1.0 INTRODUCTION
The Nige ian hospi ali y indus y has wi nessed ema kable g ow h o e he yea s, ueled by inc easing domes ic and in e na ional
a el, apid u baniza ion, and economic expansion. Key ci ies such as Lagos, Abuja, and Po Ha cou ha e seen a p oli e a ion
o ho els, anging om budge - iendly lodgings o high-end luxu y es ablishmen s (Majebi, 2024). This sec o plays a c ucial ole
in he na ion’s economy by gene a ing employmen and boos ing ou ism. Howe e , Nige ian ho els con inue o g apple wi h
challenges ela ed o se ice e iciency, high ope a ional cos s, and main aining se ice quali y, making he adop ion o inno a i e
solu ions essen ial o sus aining compe i i eness (Akin ade e al, 2025)
The in eg a ion o echnology has e olu ionized se ice deli e y in he hospi ali y sec o , signi ican ly enhancing bo h cus ome
expe ience and ope a ional e iciency. Many ho els in Nige ia ha e emb aced digi al inno a ions such as online booking pla o ms,
mobile applica ions, and au oma ed check-in/check-ou sys ems o s eamline p ocesses (Ib ahim e al, 2024). Howe e , he
g owing global adop ion o A i icial In elligence (AI) is d i ing a mo e p o ound ans o ma ion in he indus y. AI-powe ed
solu ions, including cha bo s o cus ome suppo , sma oom au oma ion, p edic i e analy ics o demand o ecas ing, and
acial ecogni ion o secu i y, a e eshaping he ho el expe ience by making se ices mo e e icien and pe sonalized (Adaobi e
al, 2024)
Wi h inc easing compe i ion and e ol ing cus ome expec a ions, he adop ion o AI in Nige ian ho els is becoming inc easingly
ele an . AI no only enhances ope a ional e iciency by minimizing human e o s and op imizing esou ces bu also imp o es
Adop ion o A i icial In elligence in Nige ian Ho els: A Pa hway o Enhanced Cus ome Expe ience and Ope a ional
E iciency
IJMRA, Volume 08 Issue 10 Oc obe 2025 www.ijm a.in Page 5789
gues expe iences h ough pe sonalized in e ac ions (Kekeocha and Ejiogu, 2025). Despi e i s ad an ages, AI implemen a ion in
Nige ia emains in i s ea ly s ages, hinde ed by challenges such as high cos s, inadequa e in as uc u e, and a sho age o skilled
p o essionals. This s udy examines he cu en s a e o AI adop ion in Nige ian ho els, i s impac on cus ome expe ience and
ope a ional pe o mance, and he obs acles p e en ing widesp ead implemen a ion (Adim and Mezeh, 2020)
2.0 LITERATURE REVIEW
2.1 O e iew and Concep o AI in Nige ian Ho els
In he hospi ali y indus y, A i icial In elligence (AI) in ol es he use o compu e sys ems o execu e asks ha adi ionally ely
on human in elligence, such as lea ning, p oblem-sol ing, and decision-making (Osada e e al, 2024). The main ole o AI in he
hospi ali y indus y is o sys ems capable o analyzing da a, lea ning om i , and u ilizing ha knowledge o au oma e p ocesses
and imp o e expe iences. In he ho el indus y, his means le e aging algo i hms o s eamline ope a ions and ailo gues
in e ac ions (Igani, 2023).
Howe e , he main ole o a combina ion o speci ic oles o AI in he hospi ali y indus y, which includes enhanced cus ome
se ice, ope a ional e iciency, pe sonal expe ience, e enue managemen , as well as secu i y and sa e y (Benjamin and Cyn hia,
2025). When i comes o enhanced cus ome se ice, AI-d i en cha bo s and i ual assis an s deli e immedia e cus ome se ice,
managing inqui ies, bookings, and pe sonalized sugges ions, he eby minimizing wai imes and maximizing gues sa is ac ion
h ough 24/7 suppo (Hussaini and Gaji, 2024)
Conside ing ope a ional e iciency, AI s eamlines ho el ope a ions by au oma ing check-in/ou , housekeeping schedules, and
in en o y, eeing s a o ocus on complex, cus ome -cen ic asks, he eby enhancing bo h se ice quali y and p oduc i i y
(O uedon e al, 2025). When delibe a ing on pe sonal expe ience, AI uses da a analy ics o pe sonalize gues expe iences by
unde s anding hei p e e ences, enabling ailo ed oom se ings, dining, and ac i i y ecommenda ions o a mo e enjoyable s ay
(Akin ade e al, 2025)
In conside a ion o e enue managemen , AI-d i en e enue managemen analyzes booking da a, compe i o p icing, and ma ke
ends o op imize oom a es, enabling ho els o emain compe i i e and inc ease p o i abili y h ough maximized occupancy
(Adim and Mezeh, 2020). Conside ing secu i y and sa e y, AI-d i en su eillance and acial ecogni ion p o ide eal- ime secu i y
enhancemen s by de ec ing anomalies and iden i ying po en ial h ea s, p e en ing unau ho ized access and ensu ing a sa e
en i onmen (Oluwagbaemi and Adeyemo, 2023)
Implemen ing AI in hei daily ope a ions allows Nige ian ho els o boos e iciency, enhance gues expe iences, and main ain a
compe i i e edge in he e ol ing digi al hospi ali y sec o .
2.2 AI Applica ions in he Ho el Indus y
The concep o AI in he ho els in Nige ia desc ibes he applica ions o AI in he ho el indus y, and he alue i b ings o i s daily
ope a ions. The ho el indus y is unde going a ans o ma ion h ough AI in eg a ion, wi h inno a ions like cha bo s, acial
ecogni ion, sma ooms, and au oma ed check-ins imp o ing e iciency, secu i y, and o e all gues sa is ac ion.
2.2.1 Cha bo s and Vi ual Assis an s
AI-powe ed cha bo s and i ual assis an s a e inc easingly i al in ho el cus ome se ice. These sys ems ins an ly espond o
gues inqui ies, acili a e bookings, p o ide pe sonalized ecommenda ions, and manage complain s. Unlike human agen s,
cha bo s ope a e a ound he clock, ensu ing gues s ecei e imely assis ance a any hou . This minimizes wai imes and
signi ican ly enhances he o e all gues expe ience (Pillai and Si a hanu, 2020)
2.2.2 Facial Recogni ion Technology
Facial ecogni ion echnology is imp o ing secu i y and op imizing ho el ope a ions. Many con empo a y ho els employ AI-d i en
acial ecogni ion sys ems o acili a e seamless check-ins, elimina ing he need o physical iden i ica ion documen s. This
inno a ion also s eng hens secu i y by es ic ing access o designa ed a eas o au ho ized pe sonnel only. Mo eo e , i can
iden i y e u ning gues s, allowing ho els o o e pe sonalized se ices ailo ed o hei p e e ences (Xu e al, 2021)
2.2.3 Sma Rooms and Pe sonalized Expe iences
AI is ans o ming gues expe iences h ough sma oom au oma ion. In elligen sys ems can egula e ligh ing, empe a u e, and
en e ainmen se ings acco ding o indi idual p e e ences. Voice-ac i a ed assis an s like Amazon Alexa o Google Assis an
enable gues s o adjus oom ea u es e o lessly using oice commands, enhancing com o and con enience (A apou and Kapiki,
2023). Addi ionally, by analyzing p e ious p e e ences, AI can u he cus omize he s ay by p o iding pe sonalized
ecommenda ions o dining, ac i i ies, and ho el se ices (Das, 2023)
Adop ion o A i icial In elligence in Nige ian Ho els: A Pa hway o Enhanced Cus ome Expe ience and Ope a ional
E iciency
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2.2.4 Au oma ed Check-Ins and Check-Ou s
Con en ional check-in and check-ou p ocedu es can be leng hy, equen ly esul ing in long wai imes. AI-powe ed au oma ed
sys ems simpli y his p ocess by enabling gues s o check in h ough mobile apps o sel -se ice kiosks. U ilizing acial ecogni ion,
QR codes, o mobile key access, hese sys ems minimize physical in e ac ion, making he p ocess quicke and mo e e icien
(Ma ques, 2019).
AI adop ion allows ho els o achie e signi ican gains in e iciency, secu i y, and cus ome sa is ac ion, ensu ing hei long- e m
success in he dynamic hospi ali y indus y.
2.3 Cus ome Expe ience in he Nige ian Ho els
2.3.1 De ini ion o Cus ome Expe ience in Hospi ali y
In he hospi ali y indus y, cus ome expe ience e e s o gues s' o e all pe cep ion and le el o sa is ac ion based on hei
in e ac ions wi h a ho el o se ice p o ide . I includes e e y s age o hei jou ney, om booking and check-in o in- oom
ameni ies, dining, and pos -s ay engagemen (Kandampully e al, 2018). Deli e ing a posi i e cus ome expe ience enhances gues
sa is ac ion, p omo es epea isi s, and s eng hens b and loyal y, making i a i al componen o success in he hospi ali y sec o
(Godo ykh and Tasci, 2020)
2.3.2 Impo ance o Cus ome Expe ience in Hospi ali y
Cus ome expe ience is a co ne s one o he hospi ali y indus y, as i signi ican ly a ec s a ho el’s epu a ion, p o i abili y, and
compe i i e s anding. Gues s who ha e a posi i e expe ience a e mo e likely o lea e a o able e iews, ecommend he ho el o
o he s, and e u n o u u e s ays (Kandampully e al, 2018). Subsequen ly, a nega i e expe ience can esul in poo e iews,
dec eased cus ome e en ion, and inancial se backs. In oday’s digi al landscape, online e iews and social media play a c ucial
ole in shaping booking decisions, making excep ional cus ome se ice a op p io i y o ho els (Veloso and Gomez-Sua ez, 2023)
Addi ionally, deli e ing an ou s anding cus ome expe ience enhances ope a ional e iciency. Ho els ha p oac i ely an icipa e
and ul ill gues expec a ions h ough seamless se ices, pe sonalized in e ac ions, and swi issue esolu ion can op imize
esou ces and imp o e s a p oduc i i y (Rahimian e al, 2020). P io i izing cus ome sa is ac ion also con ibu es o inc eased
e enue, as sa is ied gues s a e mo e inclined o spend on p emium se ices such as ine dining, spa ea men s, and luxu y oom
upg ades (Alnawas and Hemsley-B own, 2019)
2.3.3 Fac o s In luencing Cus ome Expe ience in Ho el Indus y in Nige ia
Va ious ac o s in luence he o e all cus ome expe ience in he hospi ali y indus y, di ec ly a ec ing gues sa is ac ion, loyal y,
and a ho el's epu a ion. Key aspec s include se ice quali y, echnological con enience, cleanliness, pe sonaliza ion, and secu i y.
1. Se ice Quali y
The p o essionalism, wa m h, and a en i eness o ho el s a a e essen ial in shaping gues expe iences. Pe sonalized se ice,
cou eous in e ac ions, and swi issue esolu ion g ea ly enhance gues sa is ac ion. Well- ained employees who an icipa e
gues needs and deli e excep ional se ice con ibu e o a welcoming and pleasan a mosphe e, encou aging epea isi s
(Gawuna, 2019)
2. Technology and Con enience
The adop ion o ad anced digi al echnologies has e olu ionized ho el ope a ions, p o iding gues s wi h a mo e seamless
and e icien expe ience. Inno a ions such as mobile check-ins, AI-powe ed cha bo s o ins an assis ance, sma oom
con ols, and au oma ed concie ge se ices enhance con enience and minimize wai imes. These solu ions no only imp o e
gues com o bu also enable ho els o s eamline ope a ions and maximize e iciency (Osada e e al, 2024)
3. Cleanliness and Com o
Gues s an icipa e impeccable cleanliness and well-main ained accommoda ions. P is ine ooms, esh linens, and sani a y
public spaces enhance hei o e all expe ience. On he o he hand, inadequa e hygiene, ou da ed acili ies, o poo
main enance can c ea e a nega i e imp ession, de e ing epea isi s and damaging a ho el's epu a ion (Ogbunankwo e
al, 2020)
4. Pe sonaliza ion
Tailo ing se ices o ma ch gues p e e ences enhances hei s ay wi h a pe sonalized ouch. Cus omized dining choices,
p e e ed oom se ings, ailo ed ac i i y sugges ions, and loyal y pe ks c ea e a sense o alue and exclusi i y. By le e aging
AI and da a analy ics, ho els can an icipa e gues needs, deli e ing unique and memo able expe iences (Gioko e al, 2021)
5. Secu i y and Sa e y
Ensu ing a sa e and secu e en i onmen is a key p io i y o gues s. Ad anced secu i y ea u es, including su eillance sys ems,
keyless oom en y, biome ic au hen ica ion, and heal h sa e y p o ocols, enhance hei sense o secu i y. Ho els ha
Adop ion o A i icial In elligence in Nige ian Ho els: A Pa hway o Enhanced Cus ome Expe ience and Ope a ional
E iciency
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p io i ize s ong secu i y measu es p o ide a wo y- ee expe ience, os e ing g ea e us and sa is ac ion (Diminyi e al,
2020).
2.4 Ope a ional E iciency in Ho els
Ope a ional e iciency in he hospi ali y indus y e e s o a ho el's capabili y o op imize esou ces, minimize was e, and
s eamline se ice deli e y while upholding excep ional gues sa is ac ion. E icien ope a ions con ibu e o cos educ ion,
inc eased p o i abili y, and an enhanced gues expe ience (Ndu and Ajao, 2023). In Nige ia, whe e he ho el sec o is expanding
apidly, main aining ope a ional e iciency is essen ial o s aying compe i i e. Howe e , a ious challenges impede seamless
ope a ions.
2.4.1 Key Indica o s o Ope a ional E iciency in Ho els
2.4.1.1 Cos Managemen
Success ul ho els p io i ize cos educ ion while upholding excellen se ice quali y. This includes s a egic budge ing, e icien
esou ce alloca ion, and adop ing ene gy-e icien solu ions like sma ligh ing and wa e conse a ion. Addi ionally, implemen ing
was e educ ion s a egies, such as sus ainable p ac ices and s eamlined in en o y managemen , helps egula e expenses.
E ec i e cos managemen boos s p o i abili y and ensu es long- e m inancial s abili y wi hou diminishing he quali y o he
gues expe ience (Abdelmawgoud and Abd El Salam, 2022)
2.4.1.2 S a P oduc i i y
The e ec i eness o ho el employees is in luenced by ac o s such as se ice speed, s a - o-gues a io, and mul i asking abili ies.
Skilled and mo i a ed s a imp o e ope a ional e iciency by p o iding as , high-quali y se ice. Implemen ing egula aining
p og ams, pe o mance-based incen i es, and well-de ined oles enhances p oduc i i y. E ec i e wo k o ce managemen no
only op imizes ho el ope a ions bu also boos s gues sa is ac ion, esul ing in posi i e e iews and s onge cus ome loyal y
(Nikolskaya e al, 2018)
2.4.1.3 Gues Sa is ac ion Sco e
S ong cus ome sa is ac ion a ings a e a i al measu e o e ec i e ho el managemen . Me ics like online e iews, di ec gues
eedback, and Ne P omo e Sco es (NPS) o e aluable insigh s in o se ice quali y, s a e iciency, and o e all gues expe ience.
Posi i e a ings s eng hen a ho el's epu a ion, a ac new gues s, and os e epea business. Consis en ly enhancing se ice
deli e y and p o iding pe sonalized expe iences a e essen ial o main aining high sa is ac ion le els (Du ic and Po očnik Tople ,
2021)
2.4.1.4 Au oma ion and Technology U iliza ion
Implemen ing digi al solu ions such as AI-powe ed cha bo s, sma oom con ols, and au oma ed check-in sys ems g ea ly
imp o es ope a ional e iciency by educing manual wo kload and enhancing esponse imes. These inno a ions enhance gues
con enience, s eamline ho el ope a ions, and op imize esou ce managemen . By emb acing au oma ion, ho els can minimize
human e o s, imp o e se ice quali y, and deli e a seamless expe ience ha aligns wi h he g owing expec a ions o oday’s
a ele s (Gajić e al, 2024)
2.4.1.5 Supply Chain and In en o y Managemen
E icien p ocu emen , s ock con ol, and supplie coo dina ion a e c ucial o smoo h ho el ope a ions. By op imizing in en o y
le els and e ining supply chain p ocesses, ho els can a oid sho ages, minimize was e, and manage cos s e ec i ely. Le e aging
in en o y acking sys ems and os e ing s ong supplie ela ionships enhances ope a ional e iciency, ensu ing essen ial supplies
a e eadily a ailable. A well-s uc u ed supply chain suppo s consis en se ice quali y and ele a es o e all gues sa is ac ion (Tao
e al, 2024)
2.4.1.6 Ene gy and Resou ce E iciency
Adop ing e ec i e ene gy managemen s a egies is c ucial o bo h sus ainabili y and cos -e ec i e ho el ope a ions. The use o
sma ligh ing, wa e -sa ing ini ia i es, and enewable ene gy sou ces like sola powe helps minimize ene gy consump ion while
ensu ing gues com o . Addi ionally, e icien hea ing, en ila ion, and ai condi ioning (HVAC) sys ems op imize esou ce
u iliza ion. By emb acing eco- iendly p ac ices, ho els can educe ope a ional expenses, s eng hen hei commi men o
en i onmen al sus ainabili y, a ac eco-conscious gues s, and enhance hei o e all b and epu a ion (Pold ugo ac e al, 2016).
2.4.2 Challenges o Ope a ional E iciency in Nige ian Ho els
2.4.2.1 High Ope a ional Cos s
The hospi ali y indus y con ends wi h escala ing expenses d i en by ising ene gy p ices, high main enance cos s, and ola ile
exchange a es. These inancial p essu es inc ease o e all ope a ional expendi u es, impac ing p o i abili y and budge s abili y.
To add ess hese challenges, ho els mus implemen e ec i e cos managemen s a egies, including ene gy-e icien
Adop ion o A i icial In elligence in Nige ian Ho els: A Pa hway o Enhanced Cus ome Expe ience and Ope a ional
E iciency
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echnologies, p edic i e main enance, and s a egic inancial planning, ensu ing sus ainable ope a ions and long- e m business
success (Ahmodu e al, 2024)
2.4.2.2 Skill Gaps and Wo k o ce Challenges
Many ho els s uggle o main ain a skilled wo k o ce, leading o inconsis encies in se ice quali y and ope a ional ine iciencies.
Fac o s such as inadequa e aining, high employee u no e , and a sho age o specialized alen exace ba e hese issues. To
add ess hese challenges, ho els can in es in ongoing s a de elopmen , o e compe i i e wages, and implemen ca ee g ow h
ini ia i es o imp o e se ice s anda ds and ope a ional e ec i eness (Adeola and Ezenwa o , 2016)
2.4.2.3 Limi ed Adop ion o Technology
While he global hospi ali y indus y inc easingly adop s ad anced au oma ion, many Nige ian ho els s ill depend on manual
p ocesses due o inancial cons ain s and a lack o echnical expe ise. High implemen a ion cos s, inadequa e in as uc u e, and
esis ance o change u he slow echnological ad ancemen s. To b idge his gap, in es ing in cos -e ec i e digi al solu ions, s a
aining, and go e nmen suppo can d i e adop ion, imp o ing e iciency, se ice quali y, and indus y compe i i eness (Chikezie
e al, 2023)
2.4.2.4 Inconsis en Powe Supply
Regula elec ici y dis up ions pose a signi ican challenge o ho els, equi ing hem o ely on expensi e backup gene a o s o
sus ain ope a ions. This d i es up ene gy cos s, hampe s se ice e iciency, and diminishes gues com o . To add ess his issue,
ho els can in es in al e na i e ene gy solu ions like sola powe , ene gy-e icien echnologies, and eliable backup sys ems o
enhance ope a ional esilience and educe expenses (Akin ade e al, 2025)
2.4.2.5 Supply Chain Dis up ions
Ho els equen ly ace in en o y sho ages due o hei dependence on impo ed goods and challenges like anspo a ion delays
and luc ua ing exchange a es. These dis up ions impac se ice consis ency and he a ailabili y o essen ial supplies.
S eng hening local supplie ne wo ks and implemen ing e ec i e in en o y managemen s a egies can help minimize hese isks
and ensu e smoo h ope a ions (Pa a a and Milohnić, 2022)
2.5 Fac o s Impac ing he Adop ion o AI in he Ho el Indus y
The adop ion o A i icial In elligence (AI) in he ho el indus y is in luenced by a complex in e play o ac o s, impac ing i s speed
and scope.
2.5.1 Cos
Deploying AI solu ions, including ad anced cha bo s, acial ecogni ion sys ems, and sma oom echnologies, demands a
conside able ini ial in es men . Smalle ho els, in pa icula , mus ca e ully analyze he po en ial e u n on in es men (ROI) by
weighing ha dwa e, so wa e, in eg a ion, and main enance cos s agains expec ed imp o emen s in e iciency, e enue, and
gues sa is ac ion. The inancial isk associa ed wi h AI adop ion can o en ac as a majo ba ie (Nam e al, 2021)
2.5.2 In as uc u e and Technology Readiness
AI implemen a ion depends on a s ong digi al in as uc u e, including s able in e ne connec i i y, e icien da a s o age, and
ad anced p ocessing capabili ies. Many ho els, especially in de eloping egions, may s uggle wi h inadequa e in as uc u e o
suppo sophis ica ed AI applica ions. This challenge ex ends o bo h ha dwa e and so wa e. Addi ionally, seamless in eg a ion
wi h exis ing ho el managemen sys ems is essen ial o e ec i e AI adop ion and smoo h ope a ions (Rasheed e al, 2023)
2.5.3 Regula o y and Da a P i acy Conce ns
AI algo i hms ely on ex ensi e da a collec ion, s o age, and analysis o op imize gues expe iences, booking pa e ns, and
ope a ional p ocesses. The accu acy and comple eness o his da a a e c ucial, as poo -quali y da a can esul in ine ec i e AI-
d i en decisions. Addi ionally, da a p i acy and secu i y a e key conce ns, equi ing ho els o comply wi h egula ions while
esponsibly handling gues in o ma ion (Ezzaouia and Bulchand-Gidumal, 2020)
2.5.4 Technical Expe ise and Skills Gap
E ec i e AI implemen a ion depends on a skilled wo k o ce capable o managing and main aining AI sys ems. Howe e , many
ho els s uggle o ind and e ain employees wi h he equi ed echnical expe ise. T aining exis ing s a o wo k wi h AI-d i en
p ocesses is c ucial o smoo h adop ion. Skill sho ages can limi he e icien use o AI echnologies, p e en ing ho els om
maximizing hei bene i s (Gajić e al, 2024)
2.5.5 Cus ome Accep ance and T us
Al hough AI p o ides signi ican ad an ages, i s success ul adop ion depends on cus ome accep ance. Some gues s may be
eluc an o engage wi h AI-powe ed cha bo s o may ha e p i acy conce ns ega ding acial ecogni ion echnology. Ho els mus
implemen AI solu ions hough ully, ensu ing hey enhance a he han diminish he gues expe ience. T anspa ency, clea
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communica ion, and eassu ances abou da a secu i y a e essen ial o building us and add essing po en ial conce ns (S i as a a
e al, 2022)
2.6 Bene i s o AI In eg a ion in o Ho el Indus y
The bene i s o in eg a ion o AI in he ho el indus y in Nige ia canno be o e emphasized, hese bene i s add ess exis ing
challenges and enhances he o e all gues expe ience
2.6.1 Compe i i e Ad an age and Inno a ion
In eg a ing AI echnology posi ions Nige ian ho els as mode n and inno a i e, appealing o ech-sa y a ele s and se ing hem
apa om compe i o s. This can enhance b and loyal y and expand ma ke sha e, pa icula ly as he Nige ian middle class g ows
and in e na ional ou ism ises. Emb acing AI enables Nige ian ho els o align wi h global indus y s anda ds and imp o e hei
compe i i e edge (Jamshed e al, 2024)
2.6.2 Da a-D i en Decision Making
AI le e ages da a analy ics o gene a e aluable insigh s in o gues p e e ences and ope a ional e iciency. This empowe s ho els
o make da a-d i en decisions on se ice enhancemen s, ma ke ing s a egies, and esou ce managemen , ul ima ely imp o ing
business pe o mance and gues sa is ac ion (Vinnako a e al, 2022)
2.6.3 Enhanced Cus ome Se ice and Pe sonaliza ion
AI-d i en cha bo s and i ual assis an s deli e ound- he-clock cus ome suppo , e icien ly handling inqui ies, managing
ese a ions, and o e ing ailo ed ecommenda ions. By minimizing wai imes and enhancing esponsi eness, hese echnologies
imp o e gues expe iences and ca e o indi idual p e e ences. In a hospi ali y indus y whe e excep ional se ice is c ucial, AI
adop ion p o ides a s ong compe i i e ad an age (Joga ao, 2024)
2.6.4 Enhanced Secu i y and Sa e y
AI-d i en su eillance sys ems and acial ecogni ion echnology s eng hen secu i y by moni o ing eal- ime ac i i ies and
iden i ying po en ial h ea s. These solu ions help p e en unau ho ized access, enhance sa e y o gues s and s a , and add ess
secu i y challenges in high- isk a eas, ensu ing a mo e secu e ho el en i onmen (I ano and Webs e , 2017)
2.6.5 Imp o ed Re enue Managemen
AI-powe ed algo i hms assess ma ke ends, compe i o p icing, and booking pa e ns o dynamically adjus oom a es, ensu ing
op imal p icing s a egies. This da a-d i en app oach maximizes occupancy, enhances e enue managemen , and helps ho els s ay
compe i i e in an e e -changing ma ke . In Nige ia’s unp edic able economic landscape, le e aging AI o dynamic p icing enables
ho els o espond swi ly o demand luc ua ions, a ac mo e gues s, and imp o e o e all p o i abili y while main aining a
compe i i e edge (Abu aw e al, 2024)
2.6.6 Inc eased Ope a ional E iciency
AI s eamlines ou ine ope a ions such as check-in/check-ou , housekeeping scheduling, and in en o y managemen , educing
manual wo kload and imp o ing e iciency. By au oma ing hese asks, s a can dedica e mo e ime o pe sonalized gues
in e ac ions and complex se ice needs. This enhances esou ce u iliza ion and lowe s ope a ional expenses. Gi en he high cos
o ope a ions in Nige ia, AI-d i en au oma ion p o ides a signi ican ad an age by imp o ing p oduc i i y and o e all se ice
quali y while main aining cos -e ec i eness (Ca , 2024)
3.0 METHODOLOGY
This s udy employed a quali a i e esea ch me hodology, speci ically a sys ema ic li e a u e e iew, as he p ima y da a collec ion
me hod. This app oach was selec ed o gain a comp ehensi e unde s anding o exis ing knowledge wi hin he esea ch domain
(Aspe s and Co e, 2019). The sys ema ic li e a u e e iew ollowed a s uc u ed and igo ous p ocess o iden i ying, selec ing,
and analyzing ele an schola ly a icles. An ex ensi e sea ch ac oss academic da abases and esea ch eposi o ies ini ially yielded
26 a icles. Howe e , a e a ho ough sc eening p ocess, only 14 we e ound o be di ec ly ele an o he esea ch ocus, ensu ing
he inclusion o high-quali y and pe inen da a (Lame, 2019)
The da a collec ion p ocess adhe ed s ic ly o e hical guidelines, including p ope acknowledgmen o o iginal au ho s, accu a e
ep esen a ion o hei indings, and s ic a oidance o plagia ism. This me hodology emphasized objec i i y and unbiased da a
ex ac ion, main aining he in eg i y and eliabili y o he esea ch. By ollowing a sys ema ic app oach and upholding e hical
s anda ds, his s udy aimed o deli e a c edible and insigh ul analysis o he opic.
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4.0 FINDINGS AND RESULTS
The adop ion o A i icial In elligence (AI) in Nige ian ho els is s ill in i s nascen s age, wi h only a hand ul o p emium
es ablishmen s u ilizing AI-powe ed solu ions. While AI holds immense po en ial o e olu ionize he hospi ali y indus y, mos
ho els con inue o ely on manual ope a ions. Fac o s such as limi ed awa eness, high implemen a ion cos s, and in as uc u al
cons ain s ha e slowed AI in eg a ion. Howe e , as digi al ans o ma ion p og esses, he e is a g owing in e es in le e aging AI-
d i en au oma ion o enhance se ice e iciency and gues expe iences. (Nam e al, 2021)
Globally, AI is ans o ming ho el ope a ions and ele a ing cus ome expe iences. P ominen AI applica ions include cha bo s o
ins an cus ome suppo , acial ecogni ion o secu e check-ins, sma oom au oma ion o pe sonalized s ays, and p edic i e
analy ics o op imizing p icing and demand o ecas ing. Al hough hese echnologies a e widely emb aced in de eloped ma ke s,
Nige ian ho els ha e been slow o adop hem due o inancial limi a ions and echnical challenges (Pillai and Si a hanu, 2020)
Gues sa is ac ion in Nige ian ho els a ies signi ican ly, wi h equen complain s abou inconsis en se ice, p olonged wai
imes, and ine icien issue esolu ion. AI has he po en ial o add ess hese conce ns by enabling pe sonalized expe iences,
au oma ing cus ome in e ac ions, and s eamlining check-in and check-ou p ocedu es. Howe e , he slow adop ion o AI means
many ho els s uggle o mee e ol ing gues expec a ions (Das, 2023).
Ope a ional e iciency is i al o enhancing p o i abili y and se ice quali y in he hospi ali y sec o . AI-powe ed echnologies,
such as au oma ed in en o y managemen , in elligen scheduling, and ene gy-e icien sys ems, op imize esou ce u iliza ion and
minimize was e. While some Nige ian ho els ha e adop ed basic digi al ools, he widesp ead in eg a ion o AI emains cons ained
by in as uc u e de iciencies and a sho age o skilled pe sonnel (Abdelmawgoud and Abd El Salam, 2022)
Se e al challenges hinde ope a ional e iciency in Nige ian ho els, including high ene gy cos s, equen powe dis up ions,
wo k o ce skill sho ages, and ine icien supply chain p ocesses. Dependence on cos ly backup powe solu ions and ou da ed
manual ope a ions u he escala e expenses, educing o e all p o i abili y (Gajić e al, 2024)
Key obs acles o AI adop ion in Nige ian ho els include he high ini ial in es men equi ed, a lack o echnical expe ise, conce ns
abou da a p i acy, and esis ance o change. Addi ionally, un eliable in e ne connec i i y and inadequa e IT in as uc u e pose
signi ican ba ie s o seamless AI implemen a ion (Ahmodu e al, 2024)
The in eg a ion o AI in ho els o e s nume ous ad an ages, including enhanced cus ome se ice h ough AI-powe ed cha bo s,
imp o ed secu i y ia acial ecogni ion, dynamic p icing op imiza ion using p edic i e analy ics, and educed ope a ional cos s
h ough au oma ed ene gy managemen . As he indus y con inues o e ol e, emb acing AI can help Nige ian ho els emain
compe i i e, ele a e gues expe iences, and d i e sus ainable p o i abili y(Chikezie e al, 2023).
5.0 DISCUSSION
The s udy’s indings unde sco e bo h he po en ial bene i s and he challenges associa ed wi h AI adop ion in Nige ian ho els.
While AI p esen s an oppo uni y o e olu ionize he hospi ali y indus y by enhancing cus ome expe ience and op imizing
ope a ions, i s implemen a ion emains ela i ely low. This discussion looks in o key insigh s om he esea ch and hei b oade
implica ions o he indus y’s u u e.
The adop ion o AI in Nige ian ho els is s ill in i s ea ly s ages, la gely due o high ini ial in es men cos s, limi ed echnical
expe ise, and inadequa e in as uc u e. In con as o de eloped ma ke s whe e AI-d i en ools like cha bo s, acial ecogni ion,
and sma oom au oma ion a e commonplace, many Nige ian ho els s uggle wi h inancial and logis ical obs acles ha hinde
widesp ead adop ion. Howe e , wi h he ongoing push o digi al ans o ma ion, he e is inc easing ecogni ion o AI’s po en ial
o imp o e se ice deli e y, enhance esou ce managemen , and boos cus ome sa is ac ion (Godo ykh and Tasci, 2020)
One o he p ima y challenges Nige ian ho els aces is main aining consis en cus ome sa is ac ion. Many gues s exp ess conce ns
o e inconsis en se ice quali y, p olonged wai imes, and ine icien p oblem esolu ion. AI-powe ed solu ions, such as
au oma ed check-in p ocesses, pe sonalized gues in e ac ions, and p edic i e analy ics, ha e he po en ial o add ess hese
issues. By in eg a ing AI-d i en ools, ho els can enhance esponsi eness, imp o e se ice e iciency, and align wi h e ol ing
cus ome expec a ions (Du ic and Po očnik Tople , 2021)
Ano he key issue is ope a ional e iciency. Nige ian ho els con end wi h high ene gy cos s, equen powe dis up ions, and
ine icien supply chain managemen , all o which con ibu e o inc eased ope a ional expenses and educed p o i abili y. AI-based
echnologies, including sma ene gy managemen sys ems, p edic i e main enance, and au oma ed in en o y con ol, can help
mi iga e hese ine iciencies by op imizing esou ce u iliza ion and minimizing was e. Howe e , he lack o skilled pe sonnel and
eluc ance o in es in AI-d i en solu ions con inue o slow p og ess (Akin ade e al, 2025)
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Despi e hese ba ie s, he ad an ages o AI in eg a ion a e clea . AI can s eng hen secu i y h ough acial ecogni ion, e ine
p icing s a egies ia p edic i e analy ics, and educe cos s h ough au oma ion. Ho els ha emb ace AI will no only gain a
compe i i e edge bu also posi ion hemsel es as o wa d- hinking and cus ome - ocused es ablishmen s (Abu aw e al, 2024)
To accele a e AI adop ion, s akeholde s mus add ess key obs acles by in es ing in digi al in as uc u e, p o iding AI aining
p og ams o ho el s a , and explo ing cos -e ec i e AI solu ions. Wi h he igh app oach, Nige ian ho els can ha ness AI o
enhance gues expe iences, s eamline ope a ions, and d i e long- e m g ow h.
6.0 CONCLUSION
The in eg a ion o A i icial In elligence (AI) in Nige ian ho els o e s a signi ican oppo uni y o enhance cus ome expe ience
and ope a ional e iciency. Howe e , indings e eal ha AI adop ion is s ill in i s ea ly s ages, wi h only a hand ul o upscale ho els
u ilizing AI-d i en echnologies. Se e al challenges, including high implemen a ion cos s, limi ed echnical expe ise, and
inadequa e in as uc u e, con inue o impede widesp ead adop ion. Despi e hese hu dles, he e is inc easing awa eness o AI’s
po en ial o op imize se ice deli e y, s eamline ope a ions, and boos p o i abili y.
Globally, AI-powe ed solu ions such as cha bo s o eal- ime cus ome suppo , acial ecogni ion o seamless check-ins, and
sma oom au oma ion ha e ans o med he hospi ali y indus y. Nige ian ho els, i able o o e come inancial and echnical
cons ain s, s and o bene i immensely om AI adop ion. Implemen ing AI-d i en s a egies can add ess key ine iciencies such
as inconsis en se ice quali y, high ene gy cos s, and supply chain dis up ions, ul ima ely imp o ing ope a ional pe o mance and
gues sa is ac ion.
To accele a e AI in eg a ion, indus y s akeholde s mus ocus on in es ing in digi al in as uc u e, equipping ho el s a wi h AI
aining, and iden i ying a o dable AI solu ions ailo ed o he Nige ian ma ke . Addi ionally, os e ing pa ne ships be ween he
p i a e sec o , go e nmen , and echnology p o ide s can acili a e AI adop ion and d i e indus y inno a ion.
In conclusion, while AI adop ion in Nige ian ho els p esen s no able challenges, i s long- e m ad an ages a ou weigh he
d awbacks. Emb acing AI can enhance se ice e iciency, ele a e gues expe iences, and s eng hen he compe i i e posi ion o
Nige ian ho els in he e ol ing global hospi ali y landscape. A well-planned app oach o AI implemen a ion will ensu e sus ainable
g ow h and long- e m success.
REFERENCES
1) Abdelmawgoud, M. T., & Abd El Salam, M. A. E. M. E. (2022). Fac o s a ec ing ope a ional and inancial pe o mance
indica o s o ooms di ision in ou and i e-s a ho els in Cai o. ةلجملا ةيلودلا ثا ر
تلل ةحايسلاو ةفايضلاو , 16(3), 113-135.
2) Abu aw , M., Alawami, A., A a , M., Obaid, A. G., Alha bi, M., Alawami, M., ... & Al ahke, H. (2024). E alua ion o he Role
o A i icial In elligence on Cus ome Sa is ac ion as a Compe i i e Ad an age in he Hospi ali y Indus y in he Uni ed
S a es. Technology and In es men , 15(3), 135-144.
3) Adaobi, M. M., Nyangu, M., & Fook, H. S. (2024) The Role o A i icial In elligence in T ans o ming Cus ome Expe ience
in he Se ice Indus y in Nige ia.
4) Adeola, O., & Ezenwa o , K. (2016). The hospi ali y business in Nige ia: Issues, challenges and oppo uni ies. Wo ldwide
Hospi ali y and Tou ism Themes, 8(2), 182-194.
5) Adim, C. V., & Mezeh, A. A. (2020). Technological capabili y and o ganiza ional su i al o ho els in Po Ha cou , Ri e s
S a e, Nige ia. Academic Jou nal o Cu en Resea ch, 7(8), 86-100.
6) Adim, C. V., & Mezeh, A. A. (2020). Technological capabili y and o ganiza ional su i al o ho els in Po Ha cou , Ri e s
S a e, Nige ia. Academic Jou nal o Cu en Resea ch, 7(8), 86-100.
7) Ahmodu, A. O., A ibaba, F. O., Olayiwola, P. O., Ajayi, J. O., Lawal, N. A., & Egbewole, I. K. (2024). Human Resou ce
Managemen Cos P ac ice and Ope a ional E iciency o Hospi ali y Indus y in Ondo S a e, Nige ia. NIU Jou nal o
Humani ies, 9(3), 93-102.
8) Akin ade, E., Halidu, S., & Meduna, P. (2025, Feb ua y). Le e aging Machine Lea ning o Enhanced Hospi ali y Se ices
in Selec ed Ho els in Ondo S a e, Nige ia. In 8 h URSI-NG Annual Con e ence (URSI-NG 2024) (pp. 13-26). A lan is P ess.
9) Akin ade, E., Halidu, S., & Meduna, P. (2025, Feb ua y). Le e aging Machine Lea ning o Enhanced Hospi ali y Se ices
in Selec ed Ho els in Ondo S a e, Nige ia. In 8 h URSI-NG Annual Con e ence (URSI-NG 2024) (pp. 13-26). A lan is P ess.
10) Akin ade, E., Halidu, S., & Meduna, P. (2025, Feb ua y). Le e aging Machine Lea ning o Enhanced Hospi ali y Se ices
in Selec ed Ho els in Ondo S a e, Nige ia. In 8 h URSI-NG Annual Con e ence (URSI-NG 2024) (pp. 13-26). A lan is P ess.
11) Alnawas, I., & Hemsley-B own, J. (2019). Examining he key dimensions o cus ome expe ience quali y in he ho el
indus y. Jou nal o Hospi ali y Ma ke ing & Managemen , 28(7), 833-861.
Adop ion o A i icial In elligence in Nige ian Ho els: A Pa hway o Enhanced Cus ome Expe ience and Ope a ional
E iciency
IJMRA, Volume 08 Issue 10 Oc obe 2025 www.ijm a.in Page 5796
12) A apou, D., & Kapiki, S. (2023). Enhancing he Gues Expe ience in Hospi ali y Th ough Technology: An Ou look o he
Fu u e.
13) Aspe s, P., & Co e, U. (2019). Wha is quali a i e in quali a i e esea ch. Quali a i e sociology, 42, 139-160.
14) Benjamin, J. I., & Cyn hia, M. C. (2025) Web-Based Mapping o Tou is Facili ies in Owe i Municipal Using Remo e Sensing
and A i icial In elligence.
15) Ca , T. (2024). Cus ome pe cep ions o mode n echnology in eg a ion in he hospi ali y indus y. Zbo nik ado a
Veleučiliš a u Šibeniku, 18(1-2), 7-24.
16) Chikezie, J., Adedeji, E. O., Onihunwa, J. O., Meduna, P. N., & Joshua, D. A. (2023). Was e managemen p ac ices and
ope a ional pe o mance o ho els in Lagos S a e, Nige ia. Jou nal o Applied Sciences and En i onmen al
Managemen , 27(4), 781-785.
17) Das, M. P. (2023). Technology and Gues expe ience: inno a ions eshaping ho el managemen . In e na ional Jou nal o
Mul idimensional Resea ch Pe spec i es, 1(3), 76-95.
18) Diminyi, C. A., Deun, A. D., Ika a, I. I., Kpadji, O. L., Idam, A. O., & Anyanwu, D. E. (2020). The e ec o secu i y challenges
on gues loyal y: A s udy o selec ed ho els in Maku di, Nige ia. In e na ional Jou nal o Inno a i e Resea ch and
Ad anced S udies (IJIRAS), 7(10), 35-43.
19) Du ic, Z., & Po očnik Tople , J. (2021). The ole o pe o mance and en i onmen al sus ainabili y indica o s in ho el
compe i i eness. Sus ainabili y, 13(12), 6574.
20) Ezzaouia, I., & Bulchand-Gidumal, J. (2020). Fac o s in luencing he adop ion o in o ma ion echnology in he ho el
indus y. An analysis in a de eloping coun y. Tou ism Managemen Pe spec i es, 34, 100675.
21) Gajić, T., Pe o ić, M. D., Pešić, A. M., Conić, M., & Gligo ije ić, N. (2024). Inno a i e App oaches in Ho el Managemen :
In eg a ing A i icial In elligence (AI) and he In e ne o Things (IoT) o Enhance Ope a ional E iciency and
Sus ainabili y. Sus ainabili y, 16(17), 7279.
22) Gajić, T., Vukolić, D., Buga čić, J., Đoko ić, F., Spasoje ić, A., Kneže ić, S., ... & Dá id, L. D. (2024). The adop ion o a i icial
in elligence in Se bian hospi ali y: A po en ial pa h o sus ainable p ac ice. Sus ainabili y, 16(8), 3172.
23) GAWUNA, M. S. (2019). E ec o cus ome sa is ac ion on cus ome loyal y and he mode a ing ole o cus ome
expe ience in he Nige ian ho el indus y (Doc o al disse a ion, Doc o al disse a ion, Uni e si i U a a Malaysia].
h ps://e d. uum. edu. my/8101/1/s901645_01. pd ).
24) Gioko, S. M., Mukulu, E., & Oloko, M. (2021). The In luence o Elec onic Pe sonaliza ion on Pe o mance o Th ee o Fi e-
S a Ho els in Kenya.
25) Godo ykh, M., & Tasci, A. D. (2020). Cus ome expe ience in ou ism: A e iew o de ini ions, componen s, and
measu emen s. Tou ism managemen pe spec i es, 35, 100694.
26) Hussaini, I., & Gaji, A. A. M. A. A. (2024) A i icial In elligence (AI) Func ions on Co po a e Pe o mance in Nige ia: A c i ical
Analysis o Machine Lea ning.
27) Ib ahim, K. M., John, O. O., & Okeh, P. E. (2024). IMPACT OF ARTIFICIAL INTELLIGENCE ON OPTIMISING REVENUE
MANAGEMENT IN NIGERIA'S PUBLIC SECTOR. ANUK College o P i a e Sec o Accoun ing Jou nal, 1(1), 96-108.
28) Igani, D. C. (2023). A i icial in elligence and cus ome pa onage o ood and be e ages i ms in Po Ha cou . BW
Academic Jou nal, 9-9.
29) I ano , S. H., & Webs e , C. (2017). Adop ion o obo s, a i icial in elligence and se ice au oma ion by a el, ou ism
and hospi ali y companies–a cos -bene i analysis. A i icial in elligence and se ice au oma ion by a el, ou ism and
hospi ali y companies–a cos -bene i analysis.
30) Jamshed, K., Qu eshi, M. A., Kishwe , R., & Jamshaid, S. (2024). The bene i s and challenges o a i icial in elligence
applica ions in ou ism indus y: How he hospi ali y indus y in Japan is ans o ming. In The Role o A i icial In elligence
in Regene a i e Tou ism and G een Des ina ions (pp. 129-147). Eme ald Publishing Limi ed.
31) Joga ao, M. (2024). AI in he Hospi ali y Indus y: Re olu ionizing Gues Expe ience. In Technology and Luxu y
Hospi ali y (pp. 199-210). Rou ledge.
32) Kandampully, J., Zhang, T., & Jaakkola, E. (2018). Cus ome expe ience managemen in hospi ali y: A li e a u e syn hesis,
new unde s anding and esea ch agenda. In e na ional Jou nal o Con empo a y Hospi ali y Managemen , 30(1), 21-56.
33) Kandampully, J., Zhang, T., & Jaakkola, E. (2018). Cus ome expe ience managemen in hospi ali y: A li e a u e syn hesis,
new unde s anding and esea ch agenda. In e na ional Jou nal o Con empo a y Hospi ali y Managemen , 30(1), 21-56.
