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Effective leadership and organisational performance in technically demanding sectors increasingly depend on values-driven, human-centred approaches that extend beyond conventional managerial competencies. This qualitative study examines how workplace spirituality shapes leadership behaviour, organisational dynamics, employee development, and soft skill cultivation within a South African engineering organisation. Employing an interpretivist phenomenological design with fifteen purposively selected participants and inductive thematic analysis via Atlas.ti, six interrelated themes emerged: (1) understanding of spirituality; (2) challenges in employee development; (3) employee development strategies; (4) impact of spirituality on workplace dynamics; (5) spirituality and leadership decision-making; and (6) soft skills. Findings reveal that spirituality understood as connectedness, calling, integrity, and altruism enables transformational, servant, and spiritual leadership orientations that create psychologically safe, values-aligned environments. These environments demonstrably improve organisational commitment, ethical decision-making, human resource development outcomes, and soft skills formation, with direct implications for leadership strategy and organisational culture design. The study contributes to humanistic leadership and HRD scholarship in emerging economy engineering contexts, with practical implications for workforce transformation in post-apartheid South Africa.

This study investigates how a major South African private hospital group adopts and scales multiple renewable energy sources (MRES) within a mission-critical healthcare environment characterised by chronic grid instability. Using a qualitative single‑case study design, the research draws on semi-structured interviews with senior executives and technical managers, complemented by documentary analysis, to explore the barriers, enablers and governance mechanisms underpinning MRES adoption. The results reveal that financial and economic constraints, regulatory fragmentation, legacy infrastructure, and supply chain limitations constitute multidimensional barriers. In contrast, economic viability, executive leadership, risk-managed implementation, and energy-security imperatives serve as decisive enablers. The study demonstrates that effective adoption arises not from technology choices alone, but from an integrated organisational approach that combines diversified energy portfolios, phased implementation strategies, contractual procurement, and structured sustainability governance. The proposed Integrated MRES Adoption Framework synthesises these dimensions, offering a holistic model for energy transition in high-risk medical settings. The study concludes that hospitals can meaningfully advance renewable energy penetration when technical diversification is embedded within robust governance, financial feasibility assessments, and patient-safety-aligned risk management. Limitations include a single-case scope and senior-level perspectives; future research should compare public and private systems, evaluate long-term performance, and deepen inquiry into staff-level change processes.

Relational leadership is a key antecedent of employee attitudes and rewards perceptions. However, empirical evidence linking its specific dimensions to compensation outcomes within South Africa’s context remains limited. Drawing on social exchange and equity theories, this study examines how specific relational leadership dimensions influence compensation perceptions. Data was collected from (N = 122) permanently employed personnel at a South African organisation, using a quantitative, cross-sectional design and validated self-report measures. The data was analysed by using Pearson correlations and multiple regression to predict employee compensation through relational leadership. The ethical component emerged as the most consistent and dominant predictor of employee compensation across all models. The empowering component showed significance in one model, but the dimensions usually linked to RLP, including inclusive, caring, and visionary components, had no statistically significant impact on reward outcomes. These findings highlight a critical distinction between behaviours that foster a supportive climate and those that validate the structural legitimacy of reward systems. The study concluded that in socio-economically complex environments like South Africa, employees prioritise ethical governance and fairness over interpersonal warmth when evaluating compensation. Consequently, organisations should prioritise ethical decision-making and transparent accountability in LDPs to enhance satisfaction and perceived equity.

This systematic review examines how organisational culture (OC) influences organisational change in developing countries, addressing a literature gap concentrated in Western, high-income contexts. Following PRISMA 2020 guidelines, we analysed 35 studies published between 2000 and 2025, spanning healthcare, manufacturing, higher education, public administration, and finance across 15 developing nations. The synthesis employed thematic analysis guided by the Competing Values Framework and institutional theory. Results indicate that organisational culture operates as a contingent mediator rather than a uniform driver or barrier. Clan culture consistently facilitates change through empowerment, trust, and participative decision-making. Conversely, a hierarchy culture typically impedes implementation through centralised authority, information hoarding, and suppressed psychological safety. Adhocracy and market cultures produce context-dependent effects, moderated by sectoral constraints and managerial practices. National cultural dimensions, political interference, and resource scarcity significantly moderate these relationships, often neutralising formal change policies. The findings demonstrate that change management practices mediate the culture-outcome link but require multi-level alignment to succeed. This review contributes a contextual model for OC-change dynamics, extending Western frameworks by showing that hierarchy in developing contexts is frequently an institutionalised norm rather than a managerial preference. Practically, the study provides evidence-based guidance for diagnosing cultural fit, adapting change strategies to national realities, and addressing systemic resource constraints.

Financial institutions predict the probability of default when making lending decisions using conventional credit risk scoring models. However, in emerging economies, the underbanked, widows, small and medium enterprises owners and youth are not able to access traditional forms of collateral or identification required by financial institutions due to lack of data for them to get access to loans. Financial institutions cannot obtain much of the information required about an applicant and they use alternative data sources such as public data or social media to deal with the problems of information asymmetry, adverse selection and moral hazard. To eliminate such problems, credit risk assessment models must be built on the foundation of artificial intelligence and machine learning approaches in an effort to perform an accurate credit risk analysis, to properly assess the behaviour of the customers and subsequently perform a thorough verification of the potential of the applicant to repay the loan thereby allowing less privileged people to access credit. However, big data sourced from the internet and public data sources is characterized by huge volume, variety, veracity, the curse of dimensionality, class imbalance, concept drift and non-linearity among others. These challenges affect the generalization performance of credit risk assessment models used by most financial institutions. This paper proposes an efficient and effective credit risk assessment model capable of learning incrementally based on machine learning algorithm called Adaptive Heterogeneous Dynamic Ensemble Selection (AHDES) that uses big data from alternative sources for financial for the underbanked. The algorithm is agile and adaptive to unexpected world events, changes in customer behaviour and cognitively counter bias likely to be introduced by information asymmetry. Experimental results on four large credit datasets and five evaluation metrics show that our proposed algorithm performs better than other selected benchmark models allowing the underbanked and less privileged to access loans to stimulate economic growth.

Organisations in emerging markets, particularly on the African continent, are transitioning from linear value chains towards complex platform ecosystems, and Generative Artificial Intelligence is accelerating this shift. GenAI introduces new skill demands, hybrid human-machine roles, and the need for adaptive continuous learning. In the African context, leaders must navigate this alongside infrastructural brittleness, institutional voids, and the need for contextually grounded governance. This study explored how senior leaders in an African financial institution make sense of and navigate GenAI-enabled transformation. The study adopted a qualitative, exploratory, and constructivist case design, involving the purposive sampling of seven senior leaders from a financial institution, who were interviewed. Data was thematically analysed. The findings reveal that in some African emerging economies, financial institutions face transformational challenges stemming from strategic misalignment, capability fragmentation, and tensions between global technological pressures and locally rooted ethical expectations. The study provides a contextually grounded account of how senior leaders in an African financial institution interpret GenAI-enabled transformation amid infrastructural fragility and institutional voids, guiding executives and policymakers in creating sustainable value within GenAI-driven digital ecosystems. The value-add of the article lies in challenging the applicability of canonical Western-centric models to African contexts and in advancing a contextually grounded understanding of leadership sensemaking.    

How users perceive and respond to cybersecurity warning messages under cognitively demanding conditions can result in unintended cybersecurity failures. Digital banking environments can create cognitively demanding conditions, as users are required to make quick decisions while managing many other routine tasks. This can lead to cognitive overload and pressure to comply with cybersecurity warning messages. This study examined how cybersecurity messages are framed and how this framing could influence behavioural responses under cognitively demanding conditions. The study draws on behavioural and psychological perspectives, including the Cognitive Bias Theory, the Framing Effect, and the Cognitive Load Theory, offering critical insights into compliance cybersecurity behaviour. A quantitative survey was administered to 267 South African users in digital banking environments. Path analysis, an extension of multiple regression analysis, was used to examine the relationships among message framing, mental load, and familiarity bias, and how these factors influence behaviour, thereby impacting digital banking resilience. Findings showed that, for organisations in digital banking to be cybersecurity resilient, such resilience is largely shaped by message framing and cognitive processing load. This means message framing is a central behavioural mechanism that shapes behaviour and an organisation's overall cybersecurity posture. Similarly, mental load affects behaviour change, meaning that concerted cognitive pressures will influence users’ ability to engage with cybersecurity warnings. Familiarity bias was negatively associated with desired behaviour change, highlighting a risk of habitual reliance on familiar cybersecurity messages. The study contributes to ongoing cybersecurity research on aligning cybersecurity communication with users’ cognitive capacity, prompting institutions to rethink and redesign clear, cognitively efficient security messages that support decision-making under pressure.

The COVID-19 pandemic accelerated hybrid work adoption, essentially altering line managers' roles as they navigate supervising geographically dispersed teams. Despite widespread implementation, limited qualitative research examines how managers adapt their leadership practices within this evolving work model. This study explored the perceived challenges, opportunities, and leadership adaptations amongst line managers in hybrid settings, aiming to reveal factors that enhance leadership capability, team performance, and strategic HR practices. Inadequate understanding of managerial perceptions hinders evidence-based leadership development tailored for hybrid contexts. Line managers experience increased stress managing distributed teams whilst balancing flexibility with accountability, yet empirical research focusing on their experiences remains scarce. Adopting an interpretivist paradigm, this generic qualitative study conducted semi-structured interviews with 12 line managers from diverse sectors possessing at least two years of managerial experience supervising hybrid teams. Manual thematic analysis following Braun and Clarke's (2006) framework identified recurring patterns. Four themes emerged: challenges characterised by a trust-visibility paradox requiring structured communication and output-based monitoring; leadership opportunities demanding trust-based, emotionally intelligent, digitally fluent approaches; transformed practices shifting from presence-based to performance-based supervision; and critical organisational support needs including emotional intelligence training and clear hybrid policies.  Organisations must implement targeted interventions including hybrid-specific leadership development programmes, formalised communication protocols, output-based performance systems, and systematic wellbeing support.

The study investigates governance challenges in South Africa’s state-owned entities (SOEs) by assessing disclosures provided in SOEs’ annual reports and financial statements regarding fraud, unauthorised expenditure, irregular expenditure, and fruitless and wasteful expenditure between 2022 and 2024, in line with section 55 of the Public Finance Management Act (PFMA) No. 1 of 1999. Adopting an interpretivist research philosophy, the study utilizes qualitative methods through a content analysis of the annual reports and financial statements of the five sampled SOEs. The analysis revealed that, although the selected SOEs demonstrated partial compliance with Section 55 of the PFMA, significant governance and reporting shortcomings persist. While most SOEs maintained records and produced financial statements, none provided evidence of submitting these reports within the required timeframes, and one entity had not produced its 2024 reports by the cut-off date of 10 October 2025. The financial statements frequently lacked a fair and accurate reflection of each SOE’s financial position and performance. Disclosures related to financial misconduct were particularly weak and inconsistent, with irregular, fruitless, and wasteful expenditure reported more often than cases of fraud or unauthorised expenditure, which were largely omitted. These disclosure shortcomings suggest that compliance among SOEs remains superficial and procedural rather than substantive, undermining accountability, transparency and the overall integrity of financial reporting.

Cybersecurity threats pose a growing challenge for organizations in digitally dependent economies, with South African organizations facing increasing incidents of data breaches and ransomware, among other threats. This study investigates how organizations can enhance cybersecurity resilience by aligning data privacy regulations with business resilience strategies. A quantitative survey of 201 professionals across multiple industries in South Africa was conducted, guided by Protection Motivation Theory (PMT), Diffusion of Innovation Theory (DIT), and Resilience Theory. Analysis revealed that while organizations perceive the severity of cyber threats, internal threat perception alone does not drive innovation. Instead, external regulatory and institutional pressures emerged strong driver of cybersecurity innovation, which in turn strengthens cybersecurity resilience. Based on these insights, a Cybersecurity Resilience Model was developed as a defence mechanism against cybersecurity threats and attacks.

Entrepreneurship policy occupies a significant role in the economic and social development policies of BRICS Plus states, but its efficacy is still debated. This study seeks to analyse the congruence between entrepreneurship policy frameworks, institutional conditions, and the realities of entrepreneurial ecosystems in situations where entrepreneurship is extensively advocated as a catalyst for job creation, poverty alleviation, and inclusive growth. This study employs a systematic literature review framework based on PRISMA principles, utilising peer-reviewed research from entrepreneurship, public policy, and development studies to examine the influence of policy instruments and institutional arrangements on entrepreneurial activity and development outcomes. The analysis indicates a continual disparity between policy intentions and actual implementation, marked by the prevalence of formal, organization-focused, and growth-driven policy assumptions that insufficiently address the informal, hybrid, and collective entrepreneurial practices common in BRICS Plus environments. Key findings (i) reveal inadequate integration of community-level ecosystems, (ii) institutional complexity hindering policy implementation, and (iii) misalignment between entrepreneurship policy objectives and inclusive development as well as Sustainable Development Goal (SDG) outcomes. The study proposes a policy-ecosystem alignment framework that redefines entrepreneurship policy as an adaptive, multi-tiered process situated within intricate institutional contexts. The research proposes a Policy–Ecosystem Alignment Framework that synthesises policy orientation, institutional conditions, ecosystem dynamics, and development results to elucidate disparities in entrepreneurial policy efficacy among BRICS Plus nations. The study suggests that achieving more inclusive and context-sensitive entrepreneurship outcomes in BRICS Plus nations necessitates policy frameworks that acknowledge entrepreneurial variety, institutional diversity, and ecosystem dynamics.

The Fourth Industrial Revolution (4IR) altered how institutions and people interact and operate in various contexts. Technological advancements through e-government have resulted in more responsible, transparent, effective, and efficient governance and service delivery in Lesotho. The adoption of e-government and its influence on service delivery in Lesotho are examined in this study using a systematic scoping review process guided by the PRISMA 2020 framework. Using the Technology Acceptance Model (TAM) as its theoretical lens, the study argues that citizen adoption is dependent on perceived usefulness and ease of use, both of which are significantly hindered by local constraints. The evaluation acknowledges gains made through programmes such as the 2013 e-Government Infrastructure Project, which has increased efficiency and transparency, particularly in metropolitan areas such as Maseru. Nevertheless, it also draws attention to a notable implementation gap, with a sizable urban-rural digital divide that marginalises rural residents due to inadequate infrastructure, expensive ICT, and restricted coverage. Serious accessibility issues are also exacerbated by inadequate digital literacy and the predominance of English over Sesotho on government websites. According to the study, resolving these problems calls for a multifaceted strategy. Investing in rural digital infrastructure, lowering access fees, requiring multilingual and accessible digital content, and starting national digital literacy initiatives are all part of this strategy to transform e-government into a tool for equitable service delivery and inclusive development for all Basotho.

The nexus of Artificial Intelligence (AI) and indigenous knowledge systems (IKS) rarely features as a viable intervention in African food system policy and academic debates. This has created knowledge and practical gaps with policy and practice implications. This article argues that leveraging the AI-IKS nexus has significant potential to transform African food systems currently in crisis. This conceptual article explores the importance of IKS in Sub-Saharan Africa (SSA) and examines how AI solutions can transform regional food systems. The article shows that harnessing the AI-IKS nexus entails merging traditional, generational ecological wisdom with modern technology to enhance food security, sustainability, and resilience. Key applications include using AI to analyse indigenous drought-prediction techniques alongside meteorological data, identifying climate-resilient indigenous crops, and deploying Computer Vision and Natural Language Processing to digitise and disseminate traditional knowledge in local languages. The article argues that this synergy has the potential to enhance climate resilience, boost yields through precision agriculture, reduce post-harvest losses, and promote sustainable resource management, ultimately strengthening food security.

The global skills gap is the foremost obstacle to business transformation. Across sectors and regions, established forms of expertise are being reshaped or rendered insufficient, creating widespread uncertainty about the durability of existing skill sets. This condition, often described as skill instability, reflects a growing need for continual learning and adaptation as occupational demands evolve. This study employs a critical analysis of data from leading international organizations to map the distinct nature of this challenge across the world’s regions and industries. The study demonstrates that its nature differs fundamentally between regions and sectors. In advanced economies, the crisis is a shortage of specialized digital and green skills. In developing regions, the deficits are more foundational, rooted in basic digital literacy and technical-vocational training. Everywhere, however, a structural mismatch is worsening economies are creating complex new jobs faster than they are training workers for them, even as automation displaces lower-skilled roles. To navigate this dual challenge, we argue that technology, especially AI, must be seen as a tool to augment human potential. The solution is a decisive strategic pivot: from reactive hiring to proactive human capital development. This requires nuanced, region-specific policies and a foundational corporate commitment to lifelong learning to build a resilient and inclusive future workforce.

Climate change poses significant risks to rural livelihoods in semi-arid regions such as Bikita District, Zimbabwe, where recurrent droughts, erratic rainfall, rising temperatures, and water scarcity undermine food security and socio-economic stability. This study examines the climate-related risks faced by rural households, identifies the coping and adaptation strategies they employ, and assesses the effectiveness and sustainability of these responses. A qualitative case study design, guided by the Sustainable Livelihoods Framework, was adopted. Data were collected through in-depth interviews (n = 30), focus group discussions (two groups), and direct observations involving households, traditional leaders, and local stakeholders. Thematic analysis was used to identify patterns in risks, coping strategies, and institutional constraints. The findings show that households employ diverse strategies, including crop diversification, cultivation of drought-resistant small grains, water harvesting, livestock downsizing, livelihood diversification, horticulture, and reliance on social networks. However, many of these responses remain short-term coping mechanisms rather than sustainable adaptation strategies. Structural barriers, including limited access to credit, weak extension services, poor infrastructure, and inadequate market systems, constrain their effectiveness. In addition, some practices, including deforestation and over-reliance on food aid, are maladaptive, providing immediate relief while undermining long-term resilience. The study concludes that although rural households demonstrate significant adaptive capacity, their transition from short-term coping to sustainable adaptation is limited by systemic and institutional constraints. It highlights the need for integrated policy interventions that strengthen livelihood assets, enhance institutional support, improve access to finance and markets, and integrate indigenous knowledge with climate-smart practices. These findings contribute to climate adaptation scholarship and provide policy-relevant insights for building long-term resilience in rural Zimbabwe.

This study examined the effect of organisational culture on employees' readiness towards change at two Eswatini state-owned enterprises. Guided by a positive research philosophy, the study adopted a quantitative, cross-sectional research design. Daya was collected from a stratified sample of 543 permanent employees using the Organisational Culture Assessment Instrument (OCAI) and the Readiness Toward Change Scale (RTCS). Reliability was assessed by using Cronbach's alpha, while confirmatory factor analysis, correlation analysis, and multiple regression were employed to examine the relationship and predictive effects among the variables. The results revealed a positive and statistically significant relationship between organisational culture and readiness towards change. Market culture emerged as the strongest predictor of readiness towards change, followed by hierarchical culture, Adhocracy culture, and clan culture. These findings suggest that performance orientation, structural clarity, adaptability, and relational cohesion jointly contribute to enhancing employee readiness for organisational change. From the business ecosystem and strategic management perspective, the findings highlight the importance of cultivating an adaptive organisational culture as a key enabler of sustainable performance, ethical governance, and stakeholder trust. At a broader socio-economic level, strengthening organisational culture and employee readiness for change within state-owned enterprises can enhance productivity, promote social equity, and support inclusive growth, reinforcing Eswatini's business and socio-economic ecosystem.

This study’s main goal is to find out how blockchain technology may improve food safety and quality management in supply chains serving emerging markets. The increasing pressure on the global food supply chain to ensure the safety and quality of food products served is the driving force behind this study, particularly in poorer countries where infrastructure and regulatory oversight may be less developed. The information asymmetry, weak traceability systems, and fragmented structures that often define supply chains in emerging markets provide significant challenges to food safety and quality control activities. In recent years, blockchain technology has emerged as a potential solution to these problems. The study employed qualitative research approach using a qualitative data analysis programme, ATLAS. ti 23. Having embraced the interpretivist paradigm, about 25 supply chain professionals were purposefully selected for this study. Following thematic analysis, the following themes emerged from the primary data: Blockchain technology fundamentals, challenges in emerging market supply chains, blockchain applications and mechanisms, benefits and challenges of blockchain adoption, policy and regulatory considerations, socio-economic impacts. Using blockchain technology will enable real-time tracking of agricultural goods from farm to consumer in supply chains in emerging markets, like South Africa. Better traceability is ensured, allowing businesses to promptly pinpoint the cause of contamination or quality problems. This reduces the likelihood of widespread foodborne illnesses and recalls. By making sure that all parties involved farmers, suppliers, distributors, and retailers are held responsible for upholding safety and quality standards, this can lessen fraud and tampering. Blockchain technology is becoming more and more popular in developed market supply chains, but its potential in emerging countries is still limited, especially when it comes to food safety and quality control. This study offers fresh perspectives on how blockchain might be tailored to these regions’ particular opportunities and problems, like disjointed supply chains, constrained infrastructure, and inconsistent regulations.

Customers’ demand for printing industry to be more productive and compete globally in relation to delivery, cost, quality and use of technological factors is one of the factors which have a possible impact on productivity. Printing establishments through the South African printing industry have a major role to play in the country’s economy. Printing industry is characterised by overloading, inefficiency and ineffectiveness affecting overall organisational performance. The purpose of this study is to examine the factors influencing productivity improvement practices and develop productivity improvement model to improve printing division. This study follows a qualitative research approach as it is an exploratory research technique used to understand the underlying reasons, perceptions and motivations of individuals in solving a problem. A sample of Government Printing Works’ (GPW) employees directly involved in the printing, finishing and packaging of Higher Education and Training examination question papers located in Pretoria, City of Tshwane municipality participated in this study. A number of critical success and barriers to productivity improvement practices are identified.  Barriers factors include poorly designed process; poorly designed layout; poor quality materials; lack of effective maintenance plans; unsatisfactory planning; supplier inefficiencies and customer inefficiencies were the major causes of low productivity in the GPW. This comprehensive and holistic framework can assist government printing employees’ and lean practioners’ in their lean manufacturing implementation journey systematically and improve the organisation’s performance.

The swift proliferation of Artificial Intelligence (AI) and algorithmic technologies in the criminal justice system and legal profession is apparent worldwide. Machine learning algorithms are currently impacting sentencing determinations in multiple jurisdictions globally. Artificial intelligence, in contrast to the organic intelligence of humans and animals, possesses the ability to learn, adapt, and evolve through the assimilation of knowledge and new information. AI software can independently learn and enhance its performance based on the data it acquires. These algorithms can identify trends, elaborate on them, and discover more effective methods for executing specific activities via automation. Human fallibility necessitates the integration of AI as an essential instrument in judicial decision-making, especially in criminal sentencing, thereby aiding judges in achieving more precise and efficient outcomes, which permits them to concentrate on other matters. This paper assesses the application of artificial intelligence in criminal sentencing within the judicial system from a comparative standpoint. A mixed-method approach was utilised, integrating qualitative and quantitative techniques for data collecting, encompassing in-person interviews and surveys. The research demonstrated that AI systems can swiftly analyse extensive amounts of legal language, facilitating tasks such as transcription, document summarisation, and legal research. AI employs diverse algorithms to address a multitude of problems through pattern recognition and the execution of precise instructions. Through the analysis of huge datasets, AI can deliver impartial recommendations, resulting in more uniform sentence outcomes for analogous situations. Artificial intelligence can evaluate an offender's likelihood of recidivism by analysing variables such as age and educational background, thereby aiding courts in making educated sentence decisions. The study indicated that the risks and obstacles linked to AI in sentencing encompass prejudice amplification, potential coercion of judges to conform to AI suggestions, and ethical issues related to transparency and human rights. To alleviate these hazards, transparency mandates are crucial for enabling judges to comprehend the elements evaluated by AI systems. Stringent data-quality criteria must be established to avert the recurrence of inequitable sentencing practices. Proactive supervision and regulation of AI are essential, accompanied by rigorous legislation overseeing the design and development of algorithms. Consistent auditing, targeted AI training, and instruction for judges and legal practitioners are essential for the proper integration of AI in the criminal justice system..    

The research focused on the contribution of forensic accounting to the detection and prevention of money laundering in Zimbabwe. It sought to find out how forensic accounting methods are implemented, evaluate their effectiveness in ensuring compliance with the recommendations of the Financial Action Task Force (FATF), assess the contribution of forensic accountants to the activities of the Financial Intelligence Unit (FIU), understand the institutional challenges of implementation, and create an integrated forensic accounting model. The researchers used a mixed-methods design. Quantitative data were gathered through 235 structured questionnaires, and qualitative data were obtained from 15 purposively selected key informants. Quantitative data were processed using descriptive statistics, correlation, and multiple regression techniques in SPSS. Qualitative data were analysed thematically to determine the main themes and stakeholder views. The results showed that forensic accounting techniques, such as transaction tracing, risk-based auditing, and the use of technology, are extensively practised and, thus, significantly facilitate the identification of suspicious transactions. These activities positively influence the compliance of the FATF, primarily through regular audits and reporting. Nevertheless, limited funding, lack of sufficient training, and poor cooperation between agencies were some of the challenges that prevented the agency's effectiveness. The regression results reveal that the use of forensic accounting techniques, compliance with FATF standards, contributions from the FIU, and technological integration are factors that significantly improve the effectiveness of AML. On the other hand, institutional challenges have a negative impact on the effectiveness of AML, thus the need for a coordinated approach is confirmed. The study recommends integrating the use of technology, joint training, and regulatory compliance into a comprehensive forensic accounting model.