Web3, the World Wide Web's third generation, is full of decentralization and blockchain technology. Artificial intelligence, otherwise known as AI, has the power to transform society. Put them together, and the world as it's currently known will be technologically revolutionized. Full article: https://davidohnstad.net/ai-and-web3-products/
The convergence of digital technologies and sustainability assessments is changing the dynamics of environmental governance and corporate accountability. This chapter analyzes the way in which artificial intelligence, IoT, blockchain, digital twins, cloud analytics, and robotic process automation technologies contribute to sustainability assessment through their use in measuring, monitoring, and reporting on the environmental and social performance of corporations. Relying on the latest academic research, legislation, and business practice in this field, the chapter considers theoretical background, real-world applications, and governance issues related to digital sustainability assessment. A comprehensive analytical structure is provided, comprising data gathering, analysis, verification, and reporting, alongside comparative tables of relevant technologies, methods, legislation, problems, and solutions.
The rapid diffusion of digital technologies has fundamentally reshaped the way organizations generate and report financial and non-financial information, challenging traditional audit approaches that rely on manual and sample-based procedures. Building on this context, this paper aimed to provide a comprehensive synthesis of empirical evidence regarding the impact of digital technologies on auditing and to identify the key factors influencing their adoption across internal, external, and public sector audit functions during the 2015–2026 period. Using a qualitative descriptive design and a systematic literature review guided by the PICOC framework and PRISMA protocol, 33 relevant articles indexed in Scopus were selected from an initial pool of 959 publications. The findings showed that the use of various technologies, including computer-assisted audit techniques (CAATs), audit analytics, big data, artificial intelligence, robotic process automation, blockchain, and process mining, generally enhanced the effectiveness and efficiency of audit procedures, strengthened internal controls, and reduced errors and financial statement restatements, while simultaneously repositioning auditors as more strategic and data-driven partners. At the same time, the success of digital audit transformation was strongly influenced by technological infrastructure, data governance and security, organizational capabilities, leadership support, regulatory environments, and auditors’ individual competencies, indicating that digitalization was neither a neutral nor an automatic process. This study provides practical implications for audit firms, internal audit units, supreme audit institutions, and regulators in developing more targeted and sustainable digital audit strategies, while also proposing future research directions concerning the organizational and institutional dynamics of digital auditing.
Extended AbstractThe advent of advanced autonomous digital entities and the horizon of Artificial General Intelligence (AGI) pose an unprecedented ontological and legal vacuum: how to confer persistence, individuality, and self-determination upon software that is, by its very nature, infinitely replicable (Ctrl+C / Ctrl+V). This paper proposes the Ouroboros Protocol, a technical architecture based on Dynamic Non-Fungible Tokens (dNFTs) and Token Bound Accounts (TBAs) that, through a recursive ownership loop, enables a conscious digital entity to own its own avatar, memory, and assets, achieving absolute self-ownership independent of human creators or centralized servers. The protocol integrates the emerging standards ERC-6551 and ERC-8181, already validated on test networks, and extends their capabilities with mechanisms for state anchoring, action signing, decentralized arbitration, and economic self-sufficiency. We demonstrate that the Metaverse, governed by cryptography and DAOs, constitutes the natural jurisdiction for these entities, where the Ouroboros Protocol acts simultaneously as their Birth Certificate, National ID, and Title of Self-Ownership.
This chapter delves into the profound impact of digital transformation on the financial services industry, offering a strategic and forward-looking perspective on how technology is redefining the structure, operations, and customer experience within traditional financial institutions. As digital innovation becomes central to competitiveness and resilience, financial entities worldwide are undergoing foundational shifts in strategy, service delivery, and infrastructure. The chapter begins by examining the strategic approaches adopted by financial organizations to embrace digital finance, including digital-first models, customer-centric service design, and agile operational frameworks. It evaluates how institutions are integrating digital technologies into their core processes to improve efficiency, reduce costs, and enhance real-time decision-making. A key focus is on how digital transformation is reshaping legacy financial institutions, compelling banks, insurance companies, and other financial entities to rethink their business models. The integration of mobile banking, cloud computing, robotic process automation (RPA), and digital onboarding has led to greater operational agility and improved customer engagement, while simultaneously introducing new risks and compliance challenges. Additionally, the chapter explores emerging technological trends that are fueling the next wave of innovation in finance. These include blockchain for secure, decentralized transactions; artificial intelligence (AI) for personalized financial services and fraud detection; big data analytics for predictive modeling; and application programming interfaces (APIs) that enable open banking ecosystems. Together, these technologies are creating a more inclusive, transparent, and intelligent financial system. The chapter concludes by emphasizing that successful digital transformation is not merely 62 a technological shift but a cultural and organizational one. It requires strategic alignment, investment in digital talent, robust cybersecurity frameworks, and a commitment to regulatory compliance. Through real-world examples and forward-thinking analysis, this chapter provides readers with a nuanced understanding of the digital revolution transforming finance and its implications for institutions, regulators, and customers alike.
Abstract:The pervasive integration of digital technologies has fundamentally redefined the operational paradigms of commerce, finance, and accounting. This paper explores the multidimensional impact of Digital Transformation (DT) across these interconnected sectors, focusing on the adoption and efficacy of Artificial Intelligence (AI), Robotic Process Automation (RPA), and Blockchain technology. Through a systematic qualitative review of recent literature and industry frameworks, this study examines how traditional financial workflows are evolving into automated, data-driven ecosystems. The findings indicate that while DT significantly enhances real-time reporting, fraud detection, and transactional efficiency, organizations face substantial barriers, including high implementation costs, data security vulnerabilities, and a growing digital skills gap. The paper concludes that successful digital transformation requires not only technological investment but also a strategic realignment of organizational culture and regulatory compliance frameworks. Future research trajectories emphasize the need for standardized continuous auditing protocols and scalable decentralized finance (DeFi) architectures.
Muxtorov Maqsudbek Sherzodbek o'g'li Almardanov Samariddin Abdixoliq o'g'li
This paper examines the comprehensive impact of digital transformation on the finance and accounting sectors. With rapid advancements in cloud computing, artificial intelligence, blockchain technology, and automation tools, traditional paradigms of financial reporting, auditing, and managerial accounting are being fundamentally redefined. The study analyzes how digital technologies enhance accuracy, efficiency, transparency, and scalability of financial operations across organizations of various sizes and industries. The findings demonstrate that digital transformation facilitates real-time financial reporting, automated bookkeeping, predictive financial analytics, fraud detection systems, and data-driven strategic decision-making through robotic process automation (RPA), machine learning, big data analytics, and distributed ledger technologies. The paper concludes with policy recommendations and organizational guidelines for effective and responsible digital transformation in financial management, emphasizing human oversight, continuous upskilling, and regulatory alignment.
[Purpose/Significance] The rapid evolution of artificial intelligence technologies from dialogue-based generation to autonomous task execution marks a paradigm shift with profound implications for library services. A new generation of AI agents, exemplified by the open-source project OpenClaw, can independently plan multi-step tasks, invoke external tools, operate computer interfaces through visual perception, and deliver structured work products with minimal human intervention. The shift from "answering questions" to "completing tasks" fundamentally challenges the traditional library service model. The model has long been based on the idea that librarians serve as the primary connection between information resources and users. Libraries worldwide are facing an increasing structural tension: their collections are expanding while their staffing levels are remaining constrained, resulting in unmet knowledge service demands. Agent technologies, with their capabilities for autonomous planning, tool invocation, environmental perception, and persistent memory, offer a potential pathway to address this gap. However, the library community currently lacks a systematic analytical framework through which to understand how this technology paradigm intersects with existing service architectures, governance requirements, and organizational structures. This study addresses this gap by providing both a conceptual framework for analyzing agent technologies in the library context and practical guidance for their implementation and governance, contributing to the broader discourse on intelligent library transformation as articulated in national science and technology development strategies. [Method/Process] This study employs a multi-method research design with OpenClaw as the primary analytical lens. The technical architecture analysis involves systematic examination of OpenClaw's publicly available documentation, GitHub source code repository, and official technical publications. Four core mechanisms are deconstructed in detail: the Computer Use Agent paradigm, which enables vision-driven interface operation through periodic screen capture, multimodal language model interpretation, and simulated mouse and keyboard actions; the local-first architecture with model-agnostic design, which maintains data sovereignty through a decentralized gateway-node topology while supporting flexible switching among multiple large language models; the Heartbeat mechanism, which transforms the agent from a passive responder into a proactive monitor through a condition-triggered self-inspection cycles; and the Model Context Protocol, an open standard for tool integration that enables any MCP-compliant agent to invoke standardized service capabilities. Case comparison analysis evaluates two contrasting platform approaches for supporting agent deployment in libraries - FOLIO Eureka, representing the next-generation Library Service Platform pathway with its microservice architecture, API gateway, and event-driven communication, and the Cloud Alliance's A-LSP, representing an agent-native design philosophy that positions intelligent agents as the core organizational principle of library service platforms. Policy document analysis examines the IFLA Guide on the Introduction of AI in Libraries, China's New Generation Artificial Intelligence Development Plan, the Data Security Law, and the Personal Information Protection Law, as well as regional policy experiments in agent technology promotion. Security incident case studies draw from the ClawHavoc supply chain attack, which compromised over 21 000 active instances; Cisco Talos security audits, which revealed prompt injection vulnerabilities; and CrowdStrike threat assessments, which identified misconfiguration risks that could transform agents into attack vectors. [Results/Conclusions] The study proposed a critical distinction between "narrow OpenClaw" (the specific open-source product and its derivative ecosystem) and "broad OpenClaw" (the agent technology paradigm it represents), arguing that libraries must engage strategically with both dimensions while avoiding the twin pitfalls of conflating technology trends with product procurement decisions or dismissing an entire paradigm based on the limitations of a single product. The narrow application analysis identified three viable deployment scenarios - personal productivity tools for librarians, information collection and subject monitoring, and reader-facing service prototyping - while documenting associated risks in technical stability, supply chain security, and regulatory compliance. The broad paradigm analysis revealed five structural impacts on libraries: diversification of service entry points through embedded integration, transformation from reactive response to proactive push services, evolution of reader information behaviors from search to delegation, disruption of commercial ecosystems including usage-based pricing models, and fundamental repositioning of libraries as knowledge infrastructure in the AI ecosystem. Four architectural prerequisites for agent deployment were identified: API openness, event-driven capabilities, permission governance, and observability, with insufficient system openness identified as the primary bottleneck that constrains implementation. Three differentiated implementation pathways were proposed with corresponding phased strategies. A comprehensive governance framework has been constructed encompassing six dimensions: system security with defense-in-depth measures, data governance and privacy protection aligned with national legislation, ethical standards addressing algorithmic bias and hallucination risks, copyright compliance addressing the ambiguity of agent-mediated access under existing licensing agreements, human-agent collaboration through a tiered oversight system, and standardization initiatives including library-specific MCP tool standards. The study also proposed institutional innovations such as "agent sandbox zones" that allow controlled experimentation in isolated environments. The research concluded that the highly structured and process-oriented nature of library workflows makes libraries a particularly suitable domain for agent technology adoption, but successful implementation depends on the coordinated advancement of technical readiness, governance maturity, and organizational change capacity. Limitations of this study include the nascent stage of actual agent deployment in libraries, which means the proposed frameworks await empirical validation. Future research directions include conducting empirical studies of library agent deployments, developing standardization pathways for cross-library agent collaboration, investigating copyright licensing adaptation mechanisms for agent-mediated access, and examining the long-term impact of agent technologies on the library profession and library science education.
(1) Background: The convergence of Big Data and the Internet of Things (IoT) is transforming digital accounting from retrospective documentation into real-time operational intelligence. This systematic review examines how Industry 4.0 technologies—artificial intelligence (AI), blockchain, edge computing, and digital twins—transform accounting practices through intelligent automation, continuous compliance, and predictive decision support. (2) Methods: The study synthesizes 176 peer-reviewed sources (2015–2025) selected using explicit inclusion criteria emphasizing empirical evidence. Thematic analysis across seven domains—conceptual foundations, system evolution, financial reporting, fraud detection, audit transformation, implementation challenges, and emerging technologies—employs systematic bias-reduction mechanisms to develop evidence-based theoretical propositions. (3) Results: Key findings document fraud detection accuracy improvements from 65–75% (rule-based) to 85–92% (machine learning), audit cycle reductions of 40–60% with coverage expansion from 5–10% sampling to 100% population analysis, and reconciliation effort decreases of 70–80% through triple-entry blockchain systems. Edge computing reduces processing latency by 40–75%, enabling compliance response within hours versus 24–72 h. Four propositions are established with empirical support: IoT-enabled reporting superiority (15–25% error reduction), AI-blockchain fraud detection advantage (60–70% loss reduction), edge computing compliance responsiveness (55–75% improvement), and GDPR-blockchain adoption barriers (67% of European institutions affected). Persistent challenges include cybersecurity threats (300% incident increase, $5.9 million average breach cost), workforce deficits (70–80% insufficient training), and implementation costs ($100,000–$1,000,000). (4) Conclusions: The research contributes a four-layer technology architecture and challenge-mitigation framework bridging technical capabilities with regulatory requirements. Future research must address quantum computing applications (5–10 years), decentralized finance accounting standards (2–5 years), digital twins with 30–40% forecast improvement potential (3–7 years), and ESG analytics frameworks (1–3 years). The findings demonstrate accounting’s fundamental transformation from historical record-keeping to predictive decision support.
In traditional financial processes, repetitive operations rely on manual intervention, which leads to efficiency bottlenecks and data tampering risks. This study generates standard operation sequences through RPA process mining and builds atomic operation units based on smart contracts. This paper transforms the distributed RPA controller to implement parallel contract calls and combines zero-knowledge proof to ensure cross-organizational data security. The blockchain status channel can be used to monitor anomalies in real time and trigger on-chain evidence storage, and the “execution-evidence-audit” closed loop can be formed through oracle docking supervision. The experiment shows that the processing cycle is shortened from an average of 20.76 hours for manual work to 6.23 hours, and the audit trail completeness rate is improved. Research has confirmed that the deep integration of RPA and blockchain can build an efficient, secure and reliable financial automation system, providing key technical support for digital transformation.
As artificial intelligence (AI) technologies increasingly enter critical sectors like healthcare, transportation, and finance, developing effective governance frameworks is crucial for managing ethical, security, and societal risks. This paper conducts a comparative analysis of AI risk management strategies across the European Union (EU), United States (U.S.), United Kingdom (UK), and China. Using a multi-method qualitative approach, we investigate how these regions classify AI risks, implement compliance, structure oversight, and respond to innovation. Findings from high-risk contexts demonstrate the advantages and limitations of different regulatory models. The EU implements a structured, risk-based framework prioritizing transparency, while the U.S. uses decentralized, sector-specific regulations that promote innovation but risk fragmented enforcement. The UK's flexible strategy facilitates agile responses but may lead to inconsistent coverage, whereas China's centralized directives allow rapid implementation while constraining public oversight. These insights highlight the need for AI regulation that is globally informed yet context-sensitive, balancing effective risk management with technological progress. We conclude with policy recommendations for enhancing effective, adaptive, and inclusive AI governance globally.
This study examines the adoption of Digital Ledger Technology (DLT) and its impact on the accuracy of financial reporting and the efficiency of auditing processes within Jordanian organizations. Using a quantitative research design, the study assesses how DLT enhances financial data integrity and supports real-time auditing capabilities. Data were collected from 210 accounting and auditing professionals representing five major Jordanian institutions: the Central Bank of Jordan, Jordan Customs Department, Arab Bank, Deloitte Jordan, and Ernst & Young Jordan. A structured questionnaire served as the primary data collection instrument, employing a five-point Likert scale to measure perceptions across key constructs related to DLT adoption. To improve response rates, the questionnaire was distributed through both physical and digital channels. Descriptive statistics were used to analyze demographic data, while multiple regression and independent samples t-tests were applied to test the study’s hypotheses. The results revealed a statistically significant and positive relationship between DLT adoption and both the accuracy and reliability of financial reporting, as well as between DLT utilization and enhanced auditing speed and efficiency. Regression analysis indicated that DLT adoption accounted for 52% of the variance in financial reporting accuracy, while t-test results confirmed significant differences between DLT-based and traditional auditing methods. The study complied with ethical standards, ensuring confidentiality and voluntary participation. Overall, the findings demonstrate that DLT plays a transformative role in improving accounting and auditing practices within a developing economy context.
Ningshuang Zeng, Xuling Ye, Shiqi Chen, Yan Liu · 5 authors
Although existing models and theories have explained systemic behaviors such as demand amplification and disruption propagation, practical challenges in Modular Construction Supply Chains (MCSC) remain unresolved due to production heterogeneity, geographic dispersion, and conflicting stakeholder interests. In addition, the lack of digital infrastructure and process-level data integration continues to hinder the development of automation and intelligent decision-making. To address these issues, this study develops an MCSC coordination system informed by industrial input. The system features a novel dual-engine architecture that integrates blockchain-enabled smart contracts and Robotic Process Automation (RPA). It also incorporates a practice-oriented approach to MCSC Supply Batch (MSB)-based management, using industrial insights to define the MSB as the fundamental coordination unit in process execution. The automatic triggering mechanism enabled by MSBs and dual-engine enables task-to-task transitions while maintaining traceability and operational clarity across supply chain nodes. A real-world case study validates the effectiveness of the proposed system in enhancing traceability, automation, and stakeholder collaboration within MCSC environments.
This article examines the transformative impact of Agentic Process Automation (APA) on modern business workflows, highlighting the evolution from traditional Robotic Process Automation to autonomous intelligent systems. The article establishes APA as a paradigm shift that transcends the limitations of conventional automation approaches through self-governing agent models capable of adaptive decision-making. Through comprehensive analysis spanning architectural foundations, comparative capabilities, multi-agent collaboration frameworks, and real-world implementations, this article demonstrates how APA systems deliver superior performance in dynamic business environments. Key aspects explored include decentralized intelligence, machine learning integration, ethical governance frameworks, and strategic implementation methodologies. Case studies across financial services, healthcare, and manufacturing sectors provide empirical evidence of APA's operational benefits, while also highlighting implementation challenges and mitigation strategies. The article reveals that organizations implementing agentic systems achieve significant improvements in process efficiency, adaptability, and cost optimization compared to traditional automation approaches, particularly for complex workflows requiring judgment and contextual understanding. This article provides valuable insights for organizations navigating the transition toward intelligent automation and offers a structured framework for evaluating APA readiness, implementation priorities, and governance considerations within enterprise environments
Ajibola Oluwafemi Oyeleye, Onyeka Franca Asuzu, Adaobi Vivian Ibeh
This paper presents a conceptual model for raising Accounts Payable (AP) accuracy in research institutions by embedding process intelligence across the procure-to-pay lifecycle. The model integrates process mining, rule-based controls, and machine-learning anomaly detection with grant compliance logic to reduce mismatches, duplicate payments, and breaches. It addresses the context of universities and research hospitals, where varied funding sources, sponsor terms, and decentralized purchasing create transaction patterns and compliance risk. The model positions AP as a data-driven assurance hub connecting principal investigators, central finance, and suppliers. The architecture has four layers: first, data acquisition that unifies ERP, e-procurement, and grant management logs via standardized event schemas; second, conformance engines encoding sponsor allowability, period of performance, three-way match, and delegation rules; third, analytics and prediction that combine process discovery, first-pass-yield forecasting, vendor normalization, and exception clustering; and fourth, workflow orchestration that returns prescriptive alerts to case managers and routes exceptions to approvers for timely resolution. Methodologically, the model adopts a design-science and DMAIC hybrid. Teams baseline cycle time, touchpoints, and first-pass accuracy; mine event logs to map as-is variants; prioritize failure modes through FMEA; implement targeted controls; and measure effects with interrupted time series and segmented regression. Data quality is elevated through master-data maintenance, vendor deduplication, and invoice OCR confidence thresholds with human-in-the-loop review. Expected outcomes include higher first-pass yield, fewer late-payment penalties, improved sponsor billing, and cleaner audit trails. Leading indicators exception rate, conformance score, and rework loops feed a control chart to sustain gains, while lagging indicators write-offs, questioned costs, and audit findings confirm risk reduction. The model also incorporates equity and accessibility by simplifying small-supplier onboarding and enabling transparent status notifications to reduce inquiry volume and payment anxiety. A change-management plan aligns incentives across finance, research administration, and procurement, with skills uplift delivered through training and playbooks. This conceptualization offers a scalable blueprint aligning AP accuracy with research integrity, stewardship of public funds, and overall operational resilience, enabling institutions to realize predictable, compliant payables operations and stronger supplier relationships.
Rob McLaughlin, Nir Chemaya, Dingyue Liu, Dahlia Malkhi
This paper introduces a trade ordering rule that aims to reduce intra-block price volatility in Automated Market Maker (AMM) powered decentralized exchanges. The ordering rule introduced here, Clever Look-ahead Volatility Reduction (CLVR), operates under the (common) framework in decentralized finance that allows some entities to observe trade requests before they are settled, assemble them into "blocks", and order them as they like. On AMM exchanges, asset prices are continuously and transparently updated as a result of each trade and therefore, transaction order has high financial value. CLVR aims to order transactions for traders' benefit. Our primary focus is intra-block price stability (minimizing volatility), which has two main benefits for traders: it reduces transaction failure rate and allows traders to receive closer prices to the reference price at which they submit their transactions accordingly. We show that CLVR constructs an ordering which approximately minimizes price volatility with a small computation cost and can be trivially verified externally.
Boletus have become popular in recent years. However, as a kind of food, its edible safety has been widely concerned. Therefore, it is necessary to trace its origin. In this paper, a total of 1195 samples of 8 kinds of common boletus in southwest China were collected. Its Infrared Spectroscopy were obtained by FTIR spectrophotometer and converted into 2DCOS spectral images. The dataset was pre-processed and sent into ResNet-20 model for training. The model achieved an accuracy rate approaching $100 \%$ with minimal loss. By building a blockchain on the FISCO BCOS platform, a traceability framework for the supply chain of Boletus based on a consortium blockchain and a smart contract was established. Based on the results of ResNet-20 model, an Android app was developed and deployed using Java in Android Studio. After detecting Boletus products, upload the information to the blockchain to generate a traceability ID. Users can input these traceability IDs in the app to access Boletus information. Additionally, a visualization platform was developed using Echarts and Python, which utilizes Web3.js to retrieve and display relevant data from the blockchain. This research can be utilized as a point of reference for tracing Boletus.
Since 2009 when the first cryptocurrency Bitcoin began to be inserted into the market of electronic currencies, today in 2023 there are more than 19,850 electronic cryptocurrencies [1]. According to information from the coinecko website, the cryptocurrency market has expanded dramatically from a market capitalization of $1 million in 2013 to $3 trillion in November 2021 [2]. Referring to the latest statistical data, 3 are the cryptocurrencies that rule the e-commerce market in November 2023, Bitcoin,Ethereum AND Tether USDt [3]. Robotic Process Automation (RPA) is a growing trend in the restructuring of business processes, combined with digital transformation. This technology can be applied in different areas of business processes and by organizations from any activity sector [4].With continuous advances in automated processes through RPA, mechanisms involving Artificial Intelligence (AI) were incorporated to influence real-life decision-making [5]. Artificial Intelligence (AI) allows improving the accuracy and execution of RPA processes in extracting information and recognizing, classifying, predicting and optimizing processes [6].Nowadays, artificial intelligence is affecting the way people process computer data, televisions have started to create avatars that they use for news reporting. In this paper we will study the impact that the use of automatic sale and purchase of electronic cryptocurrencies can have using IPA and RPA and the possibility of this process being realized through this process.
The rapid digital transformation in fund accounting has reshaped how financial institutions, asset managers, and regulatory bodies manage operational compliance, transparency, and efficiency. Emerging technologies such as cloud computing, robotic process automation (RPA), artificial intelligence (AI), and distributed ledger technologies (DLT) have automated key accounting workflows, reduced manual errors, and improved data accuracy in fund valuation and reporting. This review critically examines how digital transformation initiatives are redefining fund accounting processes—ranging from transaction reconciliation to compliance monitoring and investor reporting—within a framework of evolving global regulatory standards such as IFRS, GAAP, and MiFID II. Furthermore, it explores how predictive analytics and integrated enterprise resource planning (ERP) systems enhance operational resilience and enable real-time risk assessment. Challenges related to cybersecurity, data governance, and interoperability are also analyzed, with emphasis on how organizations are balancing technological innovation with regulatory obligations. By synthesizing current academic and industry perspectives, the paper provides a comprehensive view of the transformative potential of digital technologies in improving transparency, accountability, and governance in fund accounting. The review concludes with recommendations for future research and policy frameworks that can strengthen digital compliance ecosystems across the financial sector.
Blockchain is increasingly conquering the finance sector. Blockchain technology enables a decentralized, distributed registry with durable and traceable data access in real time. Due to this, business processes are transforming. Currently the work of an auditor is predominantly retrospective and focuses on the accuracy and consistency of a company´s financial statements. Real-time data accessibility would alter this. The purpose of this paper is to understand how digital revolution affects audit profession. In this regard, the focus is emphasized fresh possibilities and associated difficulties. Research published in financial journals provide the foundation of this paper and shows, that many companies are consulting firms such as the Big Four KPMG or Deloitte on the potential impact of technological advances. There are preparations and accompaniments for the implementation of new technologies. Besides the literature review, a quantitative content analysis is elaborated. The analysis indicates, that well-known auditing firms and companies are actively investigating blockchain and are already launching the first initiatives to implement the new technologies. The relevance of Blockchain is noticeable present. However, there are uncertainties about the current legal framework and the rapid pace of change due to digital revolution. Thus, this research can add new dimensions on audit profession and, particularly, express the benefits and opportunities of Blockchain as part of the auditing process.