This study investigates the potential of Artificial Intelligence (AI) technologies to enhance the distribution and allocation of social grants in South Africa, addressing inefficiencies, high costs, and administrative complexities. Social grants are vital for reducing poverty and improving welfare, but the current system faces challenges such as lengthy processing times, inconsistent data, and limited accessibility. A qualitative research design was employed, utilising semi-structured interviews with 20 stakeholders, including policymakers, officials from the South African Social Security Agency (SASSA), and beneficiaries. Data analysis used thematic analysis to assess the feasibility of AI integration. Pilot studies of Electronic Know Your Client (EKYC) and biometric verification across select provinces provided empirical insights.
In order to enhance decision-making, lower fraud, expedite beneficiary verification, and optimise resource allocation within South Africa's social grant ecosystem, this study explores the potential applications of artificial intelligence (AI) technologies, including machine learning, predictive analytics, natural language processing, automated document verification, and anomaly detection. The study looks at international best practices, assesses the possible advantages and disadvantages of integrating AI in South Africa, and reviews policy preparedness in light of the nation's larger Fourth Industrial Revolution (4IR) goal.
Findings reveal that AI technologies could mitigate inefficiencies by automating data verification, enhancing fraud detection, and streamlining decision-making processes. Pilot implementations of Electronic Know Your Client (EKYC) and biometric systems across Gauteng, Eastern Cape, and North West provinces demonstrated varied outcomes. Gauteng saw a 5% improvement in fraud detection but faced challenges with system integration. The Eastern Cape struggled with downtimes, while the North West achieved a 10% reduction in identity theft but encountered transaction inaccuracies.
This research contributes a comprehensive AI integration model tailored to South Africa’s socio-economic context, providing actionable recommendations for policymakers. Key considerations include robust infrastructure, workforce training, regulatory updates, and ethical safeguards to ensure fair and inclusive AI deployment. The study advances the discourse on AI in public administration,
offering practical insights for achieving greater efficiency, transparency, and equity in social grant distribution.
Lolu cwaningo luhlola ukuhlanganiswa kobuchwepheshe be-Artificial Intelligence (AI) ohlelweni lokusabalalisa izibonelelo zenhlalakahle eNingizimu Afrika ukuze kuthuthukiswe ukusebenza kahle, kuncishiswe ukukopela, futhi kwandiswe ukufinyeleleka. Uhlelo lwezibonelelo zenhlalakahle lwaseNingizimu Afrika, olulawulwa yi-South African Social Security Agency (SASSA), lubalulekile ekunciphiseni ububha nasekuthuthukiseni inhlalakahle yezenhlalo. Nokho, izinselelo ezinjengokungasebenzi kahle kokuphatha, ukukopela, nokulinganiselwa kwezinsiza kuthinta ukusebenza kahle kwalo hlelo.
Lolu cwaningo lusebenzisa indlela yokucwaninga yekhwalithethivu, lusebenzisa izingxoxo ezihlelekile neziphathimandla ezibalulekile, okuhlanganisa izikhulu ze-SASSA, abenzi benqubomgomo, nabathola izibonelelo. Ukuhlaziywa kwezindikimba zedatha, okuhlangene nocwaningo lwamapayona lwe-Electronic Know Your Client (EKYC) kanye nebiometric verification ezifundazweni ezikhethiwe, kuhlaziywe imiphumela yocwaningo. Ucwaningo lwapayona lubonise amandla e-AI ekutholeni ukukopela, kwathi eGauteng kwaba nokwehla ngo-5% kokukopela, kwathi eNyakatho Ntshonalanga kwaba nehlazo lokuncipha kuka-10% ekuntshontshweni kobunikazi. Nokho, izinselelo ezifana nokwehla kwezinhlelo zesistimu nokungahlangani kahle kwezinhlelo eMpumalanga Kapa ziveza isidingo sokuthuthukiswa kwezingqalasizinda.
Imiphumela ikhombisa ukuthi i-AI ingathuthukisa kakhulu ukuphathwa kwezibonelelo zenhlalakahle ngokuzenzekelayo ekuqinisekisweni kwabamukeli, ekunciphiseni izikhathi zokucubungula, nasekukholeni ukusebenza kwamasistimu atholayo. Nokho, ukuthuthukiswa kwe-AI okuphumelelayo kudinga ingqalasizinda eqinile, ukuqeqeshwa kwabasebenzi, kanye nokuqapha kwezomthetho ukuze kuqinisekiswe ukusetshenziswa okuzuzisayo nokulungile. Lolu cwaningo lunikeza isibonelo sokuqaliswa kwe-AI esenzelwe isimo seNingizimu Afrika, lunikeza izincomo ezisebenzayo kubenzi benqubomgomo.
Ucwaningo lufaka isandla engxoxweni enkulu mayelana nokwethulwa kwe-AI ezinsizeni zomphakathi, lugqamisa isidingo sendlela elinganiselayo eqhathanisa izinzuzo zokusebenza kahle kanye nemithelela yesimilo nezenhlalo. Ngokubhekana nezinselelo zokwethulwa kwe-AI, lolu cwaningo lunikeza isiqondiso sendlela yokusebenzisa i-AI ukwenza uhlelo lwezibonelelo
zenhlalakahle eNingizimu Afrika lube olusebenzayo, olungcono, nolungagwegwesi.
Patlisiso ena e hlahloba ho kenyelletsoa ha mahlale a Artificial Intelligence (AI) tsamaisong ea kabo ea meputso ea sechaba Afrika Boroa ho ntlafatsa ts'ebetso, ho fokotsa bomenemene, le ho ntlafatsa phihlello. Tsamaiso ea meputso ea sechaba ea Afrika Boroa, e tsamaisoang ke South African Social Security Agency (SASSA), e bohlokoa ho fokotseng bofuma le ho ntlafatsa boiketlo ba sechaba. Leha ho le joalo, mathata a kang ho se sebetse hantle tsamaisong, bomenemene, le mefokolo ea lisebelisoa a sitisa katleho ea tsamaiso ena.
Patlisiso ena e sebelisa mokhoa oa lipatlisiso tsa boleng bo phahameng, e sebelisa lipuisano tse hlophisitsoeng le ba boholong, ho kenyeletsoa liofisiri tsa South African Social Security Agency (SASSA), ba etsang melao, le ba amohelang meputso ea sechaba. Tlhatlhobo ea data e entsoeng ka ho sekaseka lihlooho tsa bohlokoa, hammoho le teko ea pele ea Electronic Know Your Client (EKYC) le biometric verification liprofinseng tse ling, e fana ka leseli ka bokhoni ba AI tsamaisong ena. Teko ena e bontšitse hore AI e ka fokotsa bomenemene, moo Gauteng ho bileng le phokotso ea 5% ea bomenemene, ha Profense ya North West e bone phokotso ea 10% bosholu ba boitsebiso. Leha ho le joalo, mathata a kang ho putlama ha tsamaiso le mathata a kopano ea sistimi Profinseng ea Eastern Cape a bontša tlhoko ea lintlafatso tsa motheo.
Liphuputso li bontša hore AI e ka ntlafatsa tsamaiso ea meputso ea sechaba ka ho nolofatsa ts'ebetso ea netefatso ea ba amohelang meputso, ho fokotsa nako ea ts'ebetso, le ho ntlafatsa lits'ebetso tsa tlhahlobo ea bomenemene. Leha ho le joalo, katleho ea AI e hloka hore ho be le motheo o tiileng oa meaho, koetliso ea basebetsi, le taolo e matla ho netefatsa hore AI e sebelisoa ka toka le ka nepo. Patlisiso ena e fana ka mohlala oa ho kenya AI ts'ebetsong ka mokhoa o lumellanang le maemo a Afrika Boroa, e fana ka likhothaletso tse sebetsang ho ba etsang melao le ba ikarabellang ho tsamaiso ea meputso ea sechaba.
Patlisiso ena e kenya letsoho lipuisanong tse pharalletseng mabapi le AI le lits'ebeletso tsa sechaba, e hatisa tlhokahalo ea mokhoa o leka-lekaneng o hlahlobang melemo ea ts'ebetso hammoho le litlamorao tsa boitšoaro le tsa sechaba. Ka ho sebetsana le mathata a kenyelletsong ea AI, patlisiso ena e fana ka tataiso ea ho sebelisa AI ka tsela e ntlafatsang le e lumellanang le litlhoko tsa sechaba tsa Afrika Boroa.
