AI-Powered Smart Ledgers and Hassle-Free Bookkeeping in SMES: Effects on Automation, Error Reduction, and Real-Time Compliance

ABSTRACT:

Introduction: This study aimed to analyse how the integration of AI-enabled smart ledgers impacts three major dimensions of bookkeeping, such as error reduction, automation, and real-time compliance monitoring in the case of UK SMEs.

Methodology: The current study used structured surveys and statistical data analysis to apply a primary quantitative research design. The study used a 5-point structured survey questionnaire with 383 SME representatives to collect a dataset. Further, the data were analysed using Partial Least Squares-Structural Equation Modelling (PLS-SEM).

Results: The findings showed a significant, positive predictive association between Smart Ledger adoption and Automation (β = 0.555; p = 0.001), Error Reduction (β = 0.479; p = 0.001), and Real-Time Compliance and Monitoring (β = 0.459; p = 0.001). In terms of mediation, Hassle-Free Bookkeeping was positively related with Smart Ledger adoption (β = 0.245; p = 0.001) and partially mediated its relationship with Automation (β = 0.307; p = 0.001) and Error Reduction (β = 0.174; p = 0.002); on the other hand, partially mediating the association with Real-Time Compliance and Monitoring (β = 0.321; p = 0.001).

Conclusion: The findings imply that the adoption of smart ledgers substantially reduces accounting errors, enables automated, hassle-free bookkeeping, and guarantees real-time compliance and monitoring of the financial reporting process in UK SMEs. The partial mediating role of hassle-free bookkeeping also underscores its substantiality in streamlining accounting and reporting processes, reducing complexity, and enhancing decision-making, which can guide policymakers and SMEs.

Keywords: Smart ledgers, hassle-free bookkeeping, error reduction, automation, real-time compliance, AI-powered.

1. INTRODUCTION

In contemporary times, where business sustainability is defined by financial and accounting agility, small and micro business enterprises (SMEs) continue to face the constraints of conventional bookkeeping and accounting practices. Notwithstanding the wider adoption and implementation of digital tools in large organizations, almost 81.30% of SMEs globally still rely on manual or traditional accounting systems, thereby increasing their susceptibility to lapses in regulatory compliance, human errors in recording transactions, and financial opacity (Darma et al., 2021). During the times when AI-enabled smart ledgers are reshaping industries, accounting processes, it’s potential to revolutionise bookkeeping in SMEs remains underexplored and underutilised (Pan & Lee, 2020). In the UK, (Mouka, 2025) notes that only 44% of SMEs use accounting software or an AI-driven ledger system, while 66% still rely on outdated systems. It leads to SMEs struggling to maintain accurate financial records and, thus, their tax returns. On the other hand, 82% of UK SMEs failed due to ineffective cash flow management driven by outdated ledger systems and financial reporting processes (Sanay, 2025).

In addition, the reason for specifically conducting this study among UK SMEs is a progressive focus on digitalization in response to surging regulatory complexities and requirements, as well as competitive market demands (Mouka, 2025). As the UK government has promoted digital transformation in reporting through initiatives such as Making Tax Digital (MTD), it has become a necessity for SMEs to adopt advanced financial reporting and recording technologies to improve financial transparency and efficiency (Bloom Financials, 2025). Therefore, by analysing and generating empirical evidence on the impact of AI-powered smart ledgers on improved, hassle-free bookkeeping, the study addresses a substantial need to automate accounting procedures and enhance financial transparency across SMEs in the UK. The findings of the current study will be beneficial to owners, accountants, and finance managers of SMEs in the UK, enabling them to adopt AI-powered smart ledgers to improve accounting processes, accuracy, and compliance with regulatory requirements in the UK business environment.

The process of bookkeeping is usually subject to administrative tasks and has now developed into a dynamic procedure that demands accuracy, speed, error detection, and compliance (Bawamohiddin et al., 2023). (Malik & Hussain, 2024) note that conventional tools, such as manual preparation of general ledgers and T-accounts, lack intelligence, adaptability, and scalability, which are required for error-free, hassle-free financial reporting and regulatory compliance. The evolution of AI-enabled, Smart or automated ledgers integrated with Machine Learning (ML) and distributed ledger systems provides a revolutionary, transformative alternative (Singh, 2025).

Smart Ledger in this study is operationally defined as an AI-based digital bookkeeping platform that combines automated data processing, error-detection algorithms, and real-time compliance monitoring features, and can be supported by underlying technologies like cloud computing, as well as blockchain-based verification where applicable (Noori Doabi, 2024; Weigel & Hiebl, 2023). Compared to conventional accounting solutions, Smart Ledgers allows for the recording, validation, and reporting of transactions autonomously with minimal human intervention. Although Smart Ledger involves blockchain, distributed ledger technology (DLT), big data analytics, or IoT integrations, this study conceptualizes Smart Ledger as an accounting application powered by AI, specifically, rather than an interchangeable construct, as suggested by (Kabir et al., 2025) as well.

At the time, the market for accounting technology was developing swiftly, with international spending on AI in accounting processes expected to surpass $6,389 billion by 2025 (Aarti, 2025), while the inclusion of SMEs in this digital revolution remains underexplored. In addition, Darma et al. (2021) also evidenced that practices of manual accounting, based on manual bookkeeping, not only burden SMEs with increased overhead costs and risks of error, but also inhibit their access to regulatory compliance, real-time access to accounting data, and the reduction of reporting errors. Therefore, the current article aims to fill this gap by empirically analysing how the integration of AI-enabled smart ledgers tends to impact three core aspects of bookkeeping, namely error reduction, automation, and real-time compliance monitoring. Unlike existing studies such as (Nofel et al., 2024; and Adekunle et al., 2023), which evaluated these variables in isolation or in a large-company context, this study investigates the relationships among the variables in the context of SMEs operating in the UK.

The proposed study has several major contributions, comprising theoretical, empirical, and practical contributions. In practical terms, the study is based on the Technology Acceptance Model (TAM) and associated accounting models, demonstrating how hassle-free bookkeeping mediates the relationships among smart ledger adoption, automation, error reduction, and real-time compliance monitoring. It provides valuable empirical evidence that the efficiency of the bookkeeping process increases significantly with the implementation of a smart ledger enabled by AI. This study contributes to the literature by jointly co-analysing the associations among smart ledger adoption, automation, reduced errors, and real-time compliance in UK SMEs, and by proposing a new mediating variable: hassle-free bookkeeping. The research provides context-specific insights into the role of AI-enabled accounting systems in streamlining processes and enhancing operational efficiency, with practical applicability for SME managers, accountants, and policymakers.

2. LITERATURE REVIEW

Theoretical Framework

The current study relies on both the Technology Acceptance Model (TAM) and the Resource-Based View (RBV) as theoretical rather than empirically tested prisms. According to (Noori Doabi, 2024), TAM clarifies the perceived usefulness and perceived ease of use, and how they influence users’ adoption of new technologies. The current study does not directly quantify these constructs; however, TAM provides an informative interpretative background for why accounting professionals in SMEs are willing to embrace AI-enabled smart ledger systems, especially when such systems maximize automation, accuracy, and compliance efficiency. Therefore, the use of TAM is to conceptualise the potential of technology acceptance behind adopting smart ledgers.

In a similar vein, the RBV, as presented by (Weigel & Hiebl, 2023), holds that competitive advantage is achieved when firms possess valuable, rare, and inimitable resources and capabilities. Although this research does not operationalize or measure specific RBV constructs, the theory provides an auxiliary insight into how smart ledgers powered by AI can be used as strategic organizational resources. Integration into bookkeeping processes can help increase operational efficiency, minimize errors, and improve compliance, contributing to better firm performance. Thus, both TAM and RBV are applied as explanatory frameworks to put the study’s findings in perspective, but not as tested theoretical frameworks.

Empirical Review

Due to rising concerns and limitations in traditional or manual accounting practices regarding the accuracy of accounting figures, error, and fraud detection, several studies have examined the benefits of automated procedures or smart ledgers in mitigating these risks (Elumilade et al., 2021). In coherence with these arguments, (Nofel et al., 2024) conducted the study to suggest a novel accounting system that is integrated with Internet of Things IoT, XBRL, and Blockchain. The researcher carried out interviews with 13 industry experts from IT, engineering, and financial systems. To analyse the data, NVivo software was used, which enabled transcribing interviews and developing relevant, codified themes aligned with the research objectives. As per findings of the study, the suggested system allows for automating the process of ledger preparation and accounting through IoT to collect accounting data, which is sent to blockchain-enabled ledgers, and acts as a database to develop automated journal entries using smart contracts XBRL, which was also reflected in the arguments made by (Sanad, 2024). The results of the study imply that Smart-contacts-based ledgers enable real-time capture of accounting data, enhance data accuracy, and ensure reliable recording of transactions and figures.

The above findings are consistent with (Roszkowska, 2021), who also stressed that IoT sensors and smart-contract-based ledgers enable the timely recording of accounting data, such as inventory, cash inflows and outflows, production, and depreciation, as journal entries. Similar findings were reported by (Kabir et al., 2025) in the United States, where the authors collected data from 194 professionals in the accounting domain using a structured survey questionnaire. The collected data were analyzed using Structural Equation Modeling (SEM) in SmartPLS. As per the study’s findings, IT adoption in the bookkeeping process, such as AI-enabled Smart ledgers, enhances the reliability, accuracy, and effectiveness of accounting data.

The above literature points out the potential of smart ledger to overcome the shortcomings of manual accounting, but also highlights certain weaknesses. (Nofel et al., 2024) proposed an IoT-XBRL-Blockchain framework based on a qualitative approach, collecting data through interviews and analyzing it using thematic analysis. The findings revealed the appropriateness of real-time information accuracy, but the proposed framework is not intended for use in the UK SME context, as the study focused on large firms, limiting the generalisability of the findings. Similarly, (Roszkowska, 2021) emphasized the use of IoT and smart contracts to enhance financial accounting procedures; however, the question of their real implementation was not addressed. The survey-based SEM by (Kabir et al., 2025) validated that the use of smart ledgers improves trustworthiness, but the sample (US) is limited to the generalisability to the UK SMEs. Considering these studies in the context of TAM, it can be inferred that perceived usefulness is the foundation of adoption, whereas RBV emphasises smart ledgers as strategic assets that develop accounting capacity. However, the insufficient exploration of intermediating processes, as well as the limitations peculiar to SMEs, suggests that it still requires additional empirical validation in many business settings.

Both studies, (Nofel et al., 2024; and Kabir et al., 2025), underscored the important role of AI-enabled Smart ledgers in improving the bookkeeping process through real-time data capture, enhanced accuracy, and automation. Both studies support the efficiency and dependability of the bookkeeping process driven by AI-enabled smart ledgers, but the main difference lies in the industrial context: industrial maturity and high adoption rates in the US lead to more consistent validation of the impacts of AI-enabled smart ledgers in improving the bookkeeping process across SMEs. The study by (Nofel et al., 2024) examines sector-specific hurdles and hesitancy to digital transformation, often due to financial constraints and the shortage of skilled workers, which affect the adoption of Smart ledgers in SMEs. Hence, similar findings can be expected in the UK SME sector; thus, following the hypothesis, H1 is formulated.

H1: There is a statistically significant predictive relationship of smart ledgers with the error reduction bookkeeping in small and medium-sized business organisations.

According to (Arabi, 2024), a blockchain-based Smart Ledger can be a potential substitute for the traditional accounting information recording system. For accounting purposes, transactions were recorded using three main mechanisms: double-entry accounting, judgment accounting, and ERP systems. However, it is important to note that every mechanism has limitations and weaknesses (Demirkan et al., 2020; Zhang et al., 2021). (Azman et al., 2021; Sharma et al., 2022) also reported similar results: the embracement of blockchain technology is mostly driven by features such as increased security and privacy, enhanced transparency and auditability, inalterability of records, greater cost-effectiveness, real-time transaction processing, and flexibility.

Furthermore, (Shalhoob et al., 2024) outline those big data analytics (BDA) helps to advance error identification and avert fraud in accounting processes. Conducting a desk study using a secondary data-collection method, the findings revealed that BDA improves fraud detection by combining data from diverse sources and employing advanced algorithms to detect anomalies. Eliminates false positives and enhances accuracy, which leads to the formation of hypothesis H2. In addition, (Musiliu et al., 2024) conducted an empirical investigation of Nigerian Banks. The researcher collected data from 300 employees of 14 banks in the region using a survey design. Analysing data using inferential statistics such as correlation and regression analysis techniques, the findings revealed that Smart Ledger with distributed ledger technology (DLT) positively and significantly impacts error reduction in accounting data and enhances its reliability and accuracy.The findings imply that, practically, big data analytics (BDA) in smart ledgers and DLTs guides for enhancing financial precision, fraud prevention, compliance with regulations, data-driven decision-making, and professional training for accountants.

(Arabi, 2024) maintained that Smart Ledgers based on blockchain technology can replace traditional accounting systems because they overcome the weaknesses of double-entry accounting, judgment accounting, and ERP systems. This was reiterated by (Sharma et al., 2022) who added security, transparency, and auditability to the framework of adoption drivers. These characteristics improve perceived usefulness TAM wise; hence provides incentive to use in the case where accuracy and reliability is relevant. (Shalhoob et al., 2024) provided a conceptual framework for how big data analytics (BDA) can enhance fraud detection by detecting anomalies across a variety of datasets. Nevertheless, their desk-based method has not been empirically validated and cannot therefore be used in practice. Conversely, (Musiliu et al., 2024) empirically showed using primary survey data gathered on Nigerian banks that distributed ledger technology (DLT) minimises accounting errors and increases the accuracy of the data. However, due to the high degree of digitisation and the presence of stringent banking regulation, the findings cannot be transferred to SMEs. Smart ledgers and BDA are strategic resources from an RBV perspective; however, their value depends on sectoral and contextual differences.

(Shalhoob et al., 2024) use a desk-based secondary analysis approach to provide a broader conceptual overview of how BDA improves fraud detection in accounting data; however, the lack of primary data limits its empirical validation and specificity to the context. In contrast, (Musiliu et al., 2024) provide primary data and statistical validation indicating that DLT-integrated smart ledgers tend to decrease accounting errors in Nigeria. Though the higher digitisation levels of the financial sector and regulatory requirements in banking tend to expand perceived effectiveness, likened to less regulated industries such as SMEs. The primary restraint in both studies is the lack of industry-wide diversity, as the results are derived from the banking industry or conceptual models, which limits their applicability to SMEs with lower digital maturity and integration. Therefore, a similar relationship can be tested in the context of UK SMEs, which leads to the formation of H2;

H2: Smart ledger automation has a statistically significant association with error reduction in the processes of accounting and bookkeeping across SMEs.

Moreover, with regard to the relationship amid real-time compliance monitoring through AI-integrated ledgers on regulatory adherence, several studies hold conclusive findings. For instance, according to (Xu et al., 2021), the blockchain network integrated into automated ledgers enables the secure, real-time retrieval of accounting data.In this perspective, (Grigg, 2024; Sarwar et al., 2023) unveiled that smart ledgers enabled with blockchain technology allow for the storage of data in incontrovertible, changeable, and transparent ledgers, which cannot be altered deprived of authorisation, which ensures the integrity of accounting data fed into journal entries.

On the other hand, (Chou et al., 2021) revealed that the smart contracts-based ledgers through blockchain allow for to update or change of accounting records on a timely basis, grounded on predefined policies established using financial reporting frameworks like IFRS and GAAP. The journal ledgers and entries are automatically updated in response to changes in accounting figures, transactions, inventories, or specific cost heads in the accounting system (Bawamohiddin et al., 2023). As a result of this automated procedure, (Elumilade et al., 2021) found that manual intervention is reduced, thereby ensuring the maintenance and accuracy of accounting records in line with financial reporting standards, leading to regulatory compliance and the avoidance of misrepresentation in accounts. This further reduces manual intervention, ensuring the maintenance and updating of accounting records ensuring real-time monitoring and compliance with financial reporting standards.

Several studies confirm that AI-integrated ledgers play an important role in real-time compliance monitoring. (Xu et al., 2021) mentioned the possibility of blockchain to provide and ensure real-time accounting information, and (Grigg, 2024) highlighted the advantages of transparency and immutability, which ensure the integrity of the information. In contrast, (Chou et al., 2021; and Bawamohiddin et al., 2023) confirmed that smart contracts can be updated in line with the IFRS and GAAP to reduce the likelihood of misrepresentation. However, these results are context-dependent, and most of the evidence is based on large companies rather than SMEs. Grounded in the Technology Acceptance Model (TAM), the perceived usefulness of smart ledgers underpins the development of hypothesis H3. Hence, similar results can be observed in the context of UK SMEs; based on these findings, the following hypothesis (H3) has been developed.

H3: There is a statistically significant relationship of the adoption of Smart ledgers enabled with blockchain technology on real-time compliance monitoring in SMEs.

Task-Technology Fit (TTF) Theory, according to which technology has a positive impact on performance when it aligns well effectively the tasks it is envisioned to support. Smart Ledgers, also supported by blockchain and AI, that perform data entry and validation (blockchain) and accuracy-based bookkeeping (Elumilade et al., 2021). Process efficiency and decreased complexity manifest through the mediating construct of hassle-free bookkeeping, which helps reduce accounting errors (Narang & Jain, 2024). The mediating role is explained by the fact that Smart Ledgers are not designed to avoid errors but guarantee automated, streamlined processes that reduce manual interference (Musiliu et al., 2024). In a similar vein, (Dashkevich et al., 2024; and Grigg, 2024) found that distributed ledger technologies also increase information accuracy by eliminating redundancy and human error. Therefore, hypothesis H4 is formulated to investigate how the pragmatic advantages of Smart Ledgers support effective bookkeeping to minimize accounting errors.

H4: There is a statistically significant mediating role of hassle-free bookkeeping in the relationship between Smart Ledgers and Error Reduction.

In addition, the Technology Acceptance Model (TAM) cites two factors, perceived usefulness and ease of use, as important motivational factors to adopt the technology. It is the perception of the usefulness of Smart Ledgers, specifically their automation, because when the process of bookkeeping becomes hassle-free (Bawamohiddin et al., 2023), the effects of using Smart Ledgers are manifold. According to (Elumilade et al., 2021), a comprehensible and hassle-free bookkeeping system improves users’ perceptions of ease of use and inclines them to fully embrace technology. This convenience enables automating tasks that involve ordinary accounting practices, such as real-time ledger updates and transaction records (Musiliu et al., 2024). Therefore, it can be stated that hassle-free bookkeeping is the attribute that establishes a rapport between Smart Ledgers and automation. Consequently, H5 is developed, which echoes the fundamental claim of TAM that the decision to utilize technology, such as smart AI-enabled or distributed ledger technology, improves automation by enabling hassle-free bookkeeping.

H5: There is a statistically significant mediating role of hassle-free bookkeeping in the relationship between Smart Ledgers and automation.

The Contingency Theory of Management Accounting presupposes that the form of accounting systems and their effectiveness depend on technological development, organizational requirements, and regulatory conditions (Bawamohiddin et al., 2023). Smart Ledgers (including DLTs) are stated to provide technological support for compliance and real-time monitoring when implemented by SMEs (Elumilade et al., 2021). However, in bookkeeping, this can only be realized when the process is effective and less complex (Narang & Jain, 2024). It can also be stated that bookkeeping facilitates this relationship by enabling an organization to process data smoothly, make timely updates, and archive documents in a well-organized fashion, which are key components of compliance in rapidly evolving regulatory environments (Pan & Lee, 2020). In this way, the H6 hypothesis is developed to suggest that Smart Ledgers do not directly contribute to real-time compliance but rather help streamline internal accounting workflows. This is in line with contingency theory, which mentions that effectiveness comes about when technologies get correspondingly aligned to organisational processes and environment.

H6: There is a statistically significant mediating role of hassle-free bookkeeping in the relationship between Smart Ledgers and real-time monitoring and compliance.

Research Gaps

Notwithstanding the growing interest in integrating IoT, blockchain, and AI into the bookkeeping process and accounting systems, substantial research gaps persist that the current research aims to address. At first, while (Nofel et al., 2024) explore automation using smart contracts and blockchain-enabled ledgers, empirical evidence on the causal effects of smart ledgers on bookkeeping reliability and accuracy in the SME context is scarce. Secondly, while (Zhang et al., 2021) explore the significance and effect of big data analytics and XBRL on real-time updates of accounting data, ensuring accuracy and monitoring, there is a lack of amalgamated frameworks that empirically and critically assess the impact of smart ledgers on error detection, automation, and regulatory compliance. Thirdly, none of the studies above, have integrated and analysed the mediating effect of hassle-free bookkeeping driven by smart ledger adoption, resulting in error reduction, automation, and real-time monitoring, and compliance. Therefore, this study aims to bridge these research gaps by developing empirical evidence on the effectiveness of integrating smart ledgers for hassle-free bookkeeping and to drive error detection, accuracy, and compliance in the accounting process across SMEs. The study’s conceptual framework is shown in Fig. (1).