AI与区块链融合财务软件趋势
The Evolution of Enterprise Financial Software in the Super AI Era: From Automation to Autonomous Trust
超人工智能时代企业财务软件的演进：从自动化到自主信任
Executive Summary
执行摘要
The global financial infrastructure is currently navigating an inflection point of historical magnitude, driven by the convergence of two powerful technological vectors: Artificial Intelligence (AI) and Distributed Ledger Technology (DLT). For over four decades, the enterprise software stack has been predicated on a model of static data storage and manual reconciliation—a paradigm rooted in the "Systems of Record" (SOR) architecture established in the 1980s. This legacy framework, while foundational, has resulted in a fragmented landscape of data silos, operational latency, and capital inefficiency.1 As organizations enter the "Super AI" era, the demand for predictive intelligence, autonomous execution, and cryptographic trust is precipitating the collapse of this traditional stack.
This comprehensive research report provides an exhaustive analysis of this transformation. It delineates the trajectory from the rigid, data-centric architectures of the past to the emerging "Systems of Intelligence" (SOI) and "Systems of Agents" that promise to reimagine how work is performed. Furthermore, it explores the critical role of blockchain technology in establishing "Triple-Entry Accounting"—a revolutionary upgrade to the 500-year-old double-entry method—and the tokenization of Real-World Assets (RWA), which bridges the gap between traditional finance and the digital economy.2 By synthesizing these advancements, the report outlines a future state of "Continuous Accounting and Auditing," where financial reporting is no longer a periodic burden but a real-time, immutable stream of truth.4
全球金融基础设施目前正处于历史性的转折点，这一转折由两股强大的技术力量推动：人工智能 (AI) 和分布式账本技术 (DLT)。四十多年来，企业软件堆栈一直建立在静态数据存储和手动对账的模型之上——这一范式植根于 20 世纪 80 年代建立的“记录系统” (SOR) 架构。这一遗留框架虽然是基础性的，但导致了数据孤岛、运营延迟和资本效率低下的碎片化格局 1。随着组织进入“超人工智能”时代，对预测智能、自主执行和加密信任的需求正在促使这一传统堆栈瓦解。
本综合研究报告对这一转型进行了详尽的分析。它描绘了从过去僵化的、以数据为中心的架构到新兴的“智能系统” (SOI) 和“代理系统”的轨迹，这些系统有望重新构想工作方式。此外，本报告探讨了区块链技术在建立“三式记账法”——对已有 500 年历史的复式记账法的革命性升级——以及现实世界资产 (RWA) 代币化中的关键作用，后者弥合了传统金融与数字经济之间的鸿沟 2。通过综合这些进步，本报告勾勒了“连续会计和审计”的未来状态，在这种状态下，财务报告不再是定期的负担，而是实时、不可篡改的真理流 4。
1. The Historical Architecture: The Tyranny of Systems of Record
1. 历史架构：记录系统的暴政
1.1 The Genesis of Data Storage and the "Jenga" Stack
1.1 数据存储的起源与“积木”堆栈
To understand the magnitude of the current disruption, one must first deconstruct the architectural legacy that governs modern enterprise. Starting in the 1980s, the primary objective of software was singular: the utility of storage. This era gave birth to Systems of Record (SOR), massive databases designed to manage three critical domains of corporate data: customer relationships (CRM), employee information (HCM), and company assets (ERP).1 Giants such as SAP, Oracle, and Salesforce rose to dominance by solving the problem of digital memory.
However, these systems were engineered for the database administrator rather than the end-user. They forced humans to conform their complex, nuanced workflows into rigid database fields. As noted in the research, "Systems of Record force humans to squeeze their workflows into rigid database fields," prioritizing data integrity over usability.1 This misalignment created a fundamental friction: the "Source of Truth" (SOT) became distinct from the operational reality. While an SOR stores original data, it often fails to act as a true SOT for decision-making, which requires the aggregation and interpretation of data typically found in data warehouses or Business Intelligence (BI) tools.6
为了理解当前颠覆的规模，必须首先解构通过现代企业治理的架构遗产。从 20 世纪 80 年代开始，软件的主要目标是单一的：存储的效用。这一时代诞生了记录系统 (SOR)，这是一种旨在管理企业数据三个关键领域的大型数据库：客户关系 (CRM)、员工信息 (HCM) 和公司资产 (ERP) 1。SAP、Oracle 和 Salesforce 等巨头通过解决数字记忆问题而崛起并占据主导地位。
然而，这些系统的设计是为数据库管理员而非最终用户服务的。它们迫使人类将其复杂、细微的工作流程硬塞进僵化的数据库字段中。正如研究指出的那样，“记录系统迫使人类将其工作流程挤压进僵化的数据库字段”，优先考虑数据完整性而非可用性 1。这种错位造成了根本性的摩擦：“单一事实来源” (SOT) 与运营现实脱节。虽然 SOR 存储原始数据，但它往往无法作为决策的真正 SOT，决策需要通常在数据仓库或商业智能 (BI) 工具中发现的数据聚合和解释 6。
1.2 The Failure of Additive Complexity
1.2 叠加复杂性的失败
In an attempt to rectify the usability and collaboration deficits of SORs, enterprise leaders engaged in a decades-long game of "Jenga"—layering additional software on top of a precarious foundation.
Systems of Engagement: Introduced to facilitate communication (email, chat, collaboration apps), these systems inadvertently generated "sprawling, unusable data" that could not easily be reconciled with the structured fields of the SOR.1
Systems of Intelligence (Early Gen): Added to provide analytics, these often delivered "illusory analytics" because the underlying data was fragmented across the previous two layers.1
This additive approach resulted in digital dysfunction. Instead of boosting productivity, each new layer added complexity and maintenance overhead. The user interface (UI) became a barrier rather than a bridge. Valuable context regarding financial transactions—such as the risk signals in a customer's behavior or the negotiation details in an email thread—remained trapped in Systems of Engagement, never reaching the financial ledger.1
为了纠正 SOR 在可用性和协作方面的缺陷，企业领导者进行了长达数十年的“抽积木”游戏——在不稳定的基础上叠加额外的软件。
参与系统： 引入这些系统是为了促进沟通（电子邮件、聊天、协作应用程序），但它们无意中产生了“庞杂、不可用数据”，无法轻易与 SOR 的结构化字段协调 1。
智能系统（早期）： 添加这些系统是为了提供分析，但由于底层数据分散在前两层中，它们通常提供的是“虚幻的分析” 1。
这种叠加方法导致了数字功能障碍。每一层新层非但没有提高生产力，反而增加了复杂性和维护开销。用户界面 (UI) 成了障碍而非桥梁。关于金融交易的有价值背景信息——例如客户行为中的风险信号或电子邮件线程中的谈判细节——仍然被困在参与系统中，从未到达财务分类账 1。
Table 1: The Traditional Enterprise Stack Hierarchy
表 1：传统企业堆栈层级
2. The AI Paradigm Shift: Systems of Intelligence and Agents
2. AI 范式转变：智能系统与代理
2.1 From Passive Records to Active Intelligence
2.1 从被动记录到主动智能
The integration of advanced Artificial Intelligence marks the transition from static Systems of Record to dynamic Systems of Intelligence (SOI). Unlike their predecessors, modern SOIs do not simply store data; they actively interpret it to generate value. These platforms analyze vast datasets to identify trends, patterns, and anomalies, feeding these insights back into operations to enable better planning.6
A critical evolution here is the shift from reactive reporting to proactive experience design. For instance, AI-enabled CRM tools now utilize predictive lead scoring, real-time personalization, and sentiment analysis. These capabilities allow organizations to anticipate customer needs and financial risks before they manifest as transactional failures.7 The SOI layer effectively bridges the gap between the chaotic data of engagement systems and the rigid structures of record systems, creating a "dynamic context graph" that unifies disparate fields such as fraud, risk, and compliance.8
先进人工智能的整合标志着从静态记录系统向动态智能系统 (SOI) 的过渡。与前辈不同，现代 SOI 不仅仅存储数据；它们主动解释数据以创造价值。这些平台分析海量数据集以识别趋势、模式和异常，将这些洞察反馈回运营中以实现更好的规划 6。
这里的一个关键演变是从被动报告向主动体验设计的转变。例如，AI 赋能的 CRM 工具现在利用预测性线索评分、实时个性化和情感分析。这些能力使组织能够在客户需求和财务风险表现为交易失败之前对其进行预测 7。SOI 层有效地弥合了参与系统的混乱数据与记录系统的僵化结构之间的差距，创建了一个统一欺诈、风险和合规等不同领域的“动态上下文图谱” 8。
2.2 Unifying Silos: The Sardine Case Study
2.2 统一孤岛：Sardine 案例研究
The power of SOI is best illustrated through the unification of traditionally siloed financial functions. In the legacy model, payment processing, fraud detection, and compliance verification were handled by separate teams using separate tools, necessitating manual handoffs and creating latency.
Sardine, an innovative fintech platform, demonstrates the SOI capability by consolidating these functions. It combines payment flows, device intelligence, behavioral signals, and third-party risk indicators into a single, real-time decision engine. This allows for "autonomous decision-making," creating a unified view that would previously have required the coordination of multiple departments.8 This is not merely an efficiency gain; it is a structural transformation where the software itself acts as the operational manager, enforcing rules and managing risk dynamically.
SOI 的力量通过统一传统上孤立的财务职能得到了最好的体现。在遗留模型中，支付处理、欺诈检测和合规验证由使用不同工具的不同团队处理，需要手动交接并造成延迟。
Sardine 是一个创新的金融科技平台，通过整合这些功能展示了 SOI 的能力。它将支付流、设备智能、行为信号和第三方风险指标结合到一个单一的实时决策引擎中。这允许“自主决策”，创建一个统一的视图，而这在以前需要多个部门的协调 8。这不仅仅是效率的提升；这是一个结构性的转变，软件本身充当运营经理，动态地执行规则和管理风险。
2.3 The "System of Agents": Collapsing the Stack
2.3 “代理系统”：堆栈的瓦解
The ultimate trajectory of this evolution is the System of Agents. While Systems of Intelligence enhance existing workflows, Systems of Agents threaten to dismantle the traditional enterprise stack entirely. These are autonomous digital workers powered by generative AI that do not just assist humans but perform end-to-end tasks independently.1
Enterprise software has historically been limited by the human interface—the need for a user to click buttons and fill fields. Systems of Agents bypass this bottleneck by interacting directly with the underlying data and APIs. They can navigate the unstructured data of engagement systems and the structured rules of record systems to execute complex financial workflows—such as procurement, invoice reconciliation, and audit preparation—without human intervention.1 This represents the "collapse" of the Jenga stack: the separate layers of Record, Engagement, and Intelligence are fused into a cohesive, agentic framework where the "software" as a distinct tool disappears, replaced by an intelligent service that simply gets the work done.
这一演变的最终轨迹是代理系统。虽然智能系统增强了现有的工作流程，但代理系统威胁要完全拆除传统的企业堆栈。这些是由生成式 AI 驱动的自主数字工人，他们不仅协助人类，而且独立执行端到端任务 1。
企业软件历史上一直受限于人机界面——即用户需要点击按钮和填写字段。代理系统通过直接与底层数据和 API 交互来绕过这一瓶颈。它们可以浏览参与系统的非结构化数据和记录系统的结构化规则，以执行复杂的财务工作流——如采购、发票对账和审计准备——而无需人工干预 1。这代表了“积木”堆栈的“瓦解”：记录、参与和智能的独立层级融合为一个内聚的代理框架，在这个框架中，“软件”作为一个独特的工具消失了，取而代之的是一个仅仅把工作做完的智能服务。
3. The Trust Protocol: Blockchain and Triple-Entry Accounting
3. 信任协议：区块链与三式记账法
3.1 The Limitations of Double-Entry Accounting
3.1 复式记账法的局限性
While AI and Agents revolutionize the speed and intelligence of financial operations, they do not inherently solve the problem of trust. For 500 years, the business world has relied on Double-Entry Accounting. This system records every transaction as a debit and a credit within a single entity's private ledger. Its primary flaw is its isolation: Company A’s books are private, and Company B’s books are private. There is no shared reality.
This isolation necessitates a "Four Eyes" principle (internal dual approval) and costly external audits to verify that the private ledgers of counterparties match. Reconciling these disparate ledgers is a manual, labor-intensive process prone to error and fraud.9 In a world of autonomous AI agents executing transactions at high speed, the latency and opacity of double-entry accounting become a critical vulnerability.
虽然 AI 和代理彻底改变了财务运营的速度和智能，但它们并没有从根本上解决信任问题。500 年来，商业世界一直依赖复式记账法。该系统将每笔交易作为借方和贷方记录在单个实体的私人分类账中。其主要缺陷在于其孤立性：A 公司的账簿是私有的，B 公司的账簿也是私有的。不存在共享的现实。
这种孤立性需要“四眼”原则（内部双重批准）和昂贵的外部审计来验证交易对手的私人分类账是否匹配。核对这些不同的分类账是一个手动的、劳动密集型的过程，容易出错和发生欺诈 9。在一个自主 AI 代理高速执行交易的世界里，复式记账法的延迟和不透明成为了一个关键的弱点。
3.2 Triple-Entry Accounting: The Cryptographic Revolution
3.2 三式记账法：加密革命
The solution lies in Triple-Entry Accounting, a concept popularized by Ian Grigg and enabled by blockchain technology. This system does not discard double-entry but enhances it by adding a third, immutable component: a cryptographically secure entry on a decentralized ledger.2
The mechanism functions as follows:
Step 1 (Internal): The transaction is recorded as a debit/credit in the internal systems of both parties (just like double-entry).
Step 2 (External): Simultaneously, a "third entry"—a digital receipt or token—is generated and cryptographically signed.
Step 3 (Verification): This third entry is published to a shared blockchain ledger. The network verifies the transaction against smart contract rules.
Step 4 (Immutability): Once confirmed, the entry is locked and visible to both parties (and auditors). It cannot be unilaterally altered.9
Table 2: Double-Entry vs. Triple-Entry Accounting
表 2：复式记账法与三式记账法对比
This architecture creates a "Shared Source of Truth" external to both companies. It effectively extends the "Four Eyes" principle beyond the walls of the organization, ensuring that the counterparty's record matches the originator's record in real-time.10 Fraud becomes exponentially more difficult because altering the books would require altering the immutable blockchain history.9
这种架构创造了一个独立于两家公司的“共享事实来源”。它有效地将“四眼”原则扩展到组织围墙之外，确保交易对手的记录实时匹配发起人的记录 10。欺诈变得极其困难，因为更改账簿需要更改不可篡改的区块链历史 9。
4. The Asset Revolution: Real-World Asset (RWA) Tokenization
4. 资产革命：现实世界资产 (RWA) 代币化
4.1 Digitizing the Physical Economy
4.1 实体经济的数字化
As the accounting layer evolves, so too does the nature of the assets being accounted for. Real-World Asset (RWA) Tokenization represents the convergence of traditional financial instruments and blockchain technology. It is the process of converting ownership rights of tangible assets—such as real estate, commodities, art, and debt instruments—into digital tokens on a blockchain.3
This transformation is driven by the need to unlock liquidity in historically illiquid markets. The World Economic Forum projects that by 2027, 10% of global GDP (approximately $10 trillion) will be stored on blockchain networks.12 By "putting assets on-chain," organizations can create a "digital vault" where ownership is tracked transparently and immutably.13
随着会计层级的演变，被核算的资产性质也在发生变化。现实世界资产 (RWA) 代币化代表了传统金融工具与区块链技术的融合。这是将房地产、大宗商品、艺术品和债务工具等有形资产的所有权转换为区块链上的数字代币的过程 3。
这一转变是由释放历史上流动性不足市场的流动性需求推动的。世界经济论坛预测，到 2027 年，全球 GDP 的 10%（约 10 万亿美元）将存储在区块链网络上 12。通过“将资产上链”，组织可以创建一个“数字金库”，在其中透明且不可篡改地追踪所有权 13。
4.2 The Tokenization Mechanism and Ecosystem
4.2 代币化机制与生态系统
The process of tokenization is rigorous, involving distinct stages to ensure legal and technical compliance:
Asset Representation: Defining the asset and its valuation.
Token Issuance: Creating the smart contracts that govern the token.
Data Integration: Linking the token to real-world data (via oracles like Chainlink) to track performance or value changes.14
Compliance & Custody: Ensuring KYC/AML checks are embedded in the token's transfer logic and securing the private keys.12
A diverse ecosystem has emerged to support this infrastructure:
Tokenization Platforms: Companies like Brickken, Polymath, and Securitize provide the SaaS infrastructure to issue and manage security tokens.3
Custodians & Wallets: Entities like Onyx (by J.P. Morgan) offer bank-grade security for digital assets.
Marketplaces: Platforms like ADDX and Ownera facilitate the trading of these fractionalized assets, connecting issuers with a global pool of investors.3
代币化过程是严格的，涉及不同的阶段以确保法律和技术合规：
资产表示： 定义资产及其估值。
代币发行： 创建管理代币的智能合约。
数据集成： 将代币与现实世界数据（通过 Chainlink 等预言机）链接，以跟踪绩效或价值变化 14。
合规与托管： 确保 KYC/AML 检查嵌入代币的转账逻辑中，并保护私钥 12。
一个多元化的生态系统已经出现以支持这一基础设施：
代币化平台： Brickken、Polymath 和 Securitize 等公司提供 SaaS 基础设施来发行和管理证券代币 3。
托管人与钱包： 像 Onyx (J.P. Morgan 旗下) 这样的实体为数字资产提供银行级安全性。
市场： ADDX 和 Ownera 等平台促进这些碎片化资产的交易，将发行人与全球投资者池连接起来 3。
4.3 Benefits: Liquidity, Transparency, and Efficiency
4.3 效益：流动性、透明度与效率
The implications of RWA tokenization extend far beyond simple digitization:
Fractionalization & Liquidity: High-value assets can be sliced into smaller tokens, lowering the barrier to entry. For example, Hamilton Lane reduced the minimum investment for its Private Infrastructure Fund from $5 million to just $500 via a tokenized feeder fund.15
Programmatic Management: Smart contracts can automate lifecycle events. A tokenized bond can automatically pay coupons to holders, or a real estate token can distribute rental yield, reducing administrative friction and cost.15
Consolidated Settlement: Tokenization collapses the distribution, trading, clearing, and settlement steps into a single layer, enabling near-instant settlement and reducing counterparty risk.14
RWA 代币化的影响远超简单的数字化：
碎片化与流动性： 高价值资产可以被分割成更小的代币，从而降低进入门槛。例如，Hamilton Lane 通过代币化联接基金将其私人基础设施基金的最低投资额从 500 万美元降低到仅 500 美元 15。
程序化管理： 智能合约可以自动化生命周期事件。代币化债券可以自动向持有者支付息票，或者房地产代币可以分配租金收益，从而减少管理摩擦和成本 15。
整合结算： 代币化将分销、交易、清算和结算步骤整合到一个单一层中，实现近乎即时的结算并降低交易对手风险 14。
5. The Operational End-State: Continuous Accounting and Auditing
5. 运营终态：连续会计与审计
5.1 The Death of the Periodic Close
5.1 定期结账的消亡
The convergence of AI Agents (for execution) and Triple-Entry Blockchain (for verification) renders the traditional "periodic close" obsolete. In the legacy model, accountants work frantically at the end of the month to reconcile books, a process known as the "periodic close." This results in management relying on financial data that is weeks old.
Continuous Accounting disrupts this by processing and verifying transactions in real-time. Because Triple-Entry Accounting ensures that the transaction is cryptographically verified at the moment of execution, there is no need to wait for end-of-month reconciliation. The books are effectively "closed" every day, or even every minute.4 This allows for Continuous Reporting, where internal and external stakeholders can view the financial health of the organization in real-time via standardized formats like XBRL.5
AI 代理（用于执行）和三式记账区块链（用于验证）的融合使得传统的“定期结账”过时。在遗留模型中，会计人员在月底疯狂工作以核对账簿，这一过程被称为“定期结账”。这导致管理层不得不依赖数周前的财务数据。
连续会计通过实时处理和验证交易打破了这一局面。由于三式记账法确保交易在执行时刻经过加密验证，因此无需等待月底对账。账簿实际上每天甚至每分钟都在“结账” 4。这允许连续报告，内部和外部利益相关者可以通过 XBRL 等标准化格式实时查看组织的财务状况 5。
5.2 Continuous Auditing and Corporate Accountability
5.2 连续审计与企业问责制
The shift to real-time data necessitates a shift to Continuous Auditing. Instead of retrospective sampling—where auditors check a small percentage of transactions months after they occurred—auditors can now monitor the flow of transactions continuously.
Internal Auditors benefit significantly as they are familiar with the organization's procedures and can shift their focus from error detection to strategic risk management.16
External Auditors can leverage the blockchain's transparency to verify the existence and accuracy of transactions without demanding physical paperwork. The "immutable audit trail" provided by the ledger builds a stronger layer of trust.9
However, the success of this model depends on Corporate Accountability. As research indicates, the applicability of continuous auditing is intrinsically linked to the management mentality of the enterprise. Organizations that embrace a culture of transparency and strategic risk management are best positioned to leverage continuous auditing for competitive advantage.17
向实时数据的转变需要向连续审计转变。审计师现在可以连续监控交易流，而不是进行回顾性抽样——即审计师在交易发生数月后检查一小部分交易。
内部审计师受益匪浅，因为他们熟悉组织的程序，可以将重点从错误检测转移到战略风险管理 16。
外部审计师可以利用区块链的透明度来验证交易的存在和准确性，而无需索取实物文件。分类账提供的“不可篡改的审计轨迹”建立了更强大的信任层 9。
然而，这种模式的成功取决于企业问责制。正如研究表明的那样，连续审计的适用性与企业的管理心态有着内在的联系。拥抱透明文化和战略风险管理的组织最有条件利用连续审计获得竞争优势 17。
6. Conclusion: The Unified Financial Stack
6. 结论：统一的财务堆栈
The enterprise financial software landscape is undergoing a total reconstruction. The "Jenga" stack of the past—characterized by disconnected Systems of Record, Engagement, and Intelligence—is collapsing. In its place, a unified, intelligent, and trust-minimized architecture is emerging.
Key Takeaways:
From Record to Agent: We are moving from systems that store data (SOR) to systems that understand data (SOI) and finally to systems that act on data (Agents).
From Trust to Truth: The reliance on fallible manual reconciliation (Double-Entry) is being replaced by cryptographic certainty (Triple-Entry), creating a shared, immutable source of truth.
From Static to Liquid: Real-World Asset tokenization is unlocking trillions of dollars in value, making assets programmable, fractional, and liquid.
From Periodic to Continuous: The friction of the monthly close is vanishing, replaced by continuous accounting and auditing that provides real-time visibility into financial health.
For enterprise leaders, the path forward is clear. It is no longer sufficient to merely "digitize" existing processes. The imperative is to adopt Systems of Agents that can navigate the complexity of modern data, and to integrate Blockchain protocols that ensure the integrity of that data. Only by fusing the autonomy of AI with the immutability of the Ledger can organizations thrive in the Super AI era.
企业财务软件格局正在经历彻底的重构。过去那种以断开的记录、参与和智能系统为特征的“积木”堆栈正在瓦解。取而代之的是，一个统一的、智能的、信任最小化的架构正在出现。
主要结论：
从记录到代理： 我们正在从存储数据的系统 (SOR) 转向理解数据的系统 (SOI)，最后转向对数据采取行动的系统（代理）。
从信任到真理： 对容易出错的手动对账（复式记账）的依赖正在被加密确定性（三式记账）所取代，从而创造了一个共享的、不可篡改的事实来源。
从静态到流动： 现实世界资产代币化正在释放数万亿美元的价值，使资产变得可编程、碎片化和具有流动性。
从定期到连续： 月度结账的摩擦正在消失，取而代之的是连续会计和审计，提供对财务状况的实时可见性。
对于企业领导者来说，前进的道路是清晰的。仅仅“数字化”现有流程已不再足够。当务之急是采用能够驾驭现代数据复杂性的代理系统，并整合确保数据完整性的区块链协议。只有将 AI 的自主性与分类账的不可篡改性融合在一起，组织才能在超人工智能时代蓬勃发展。
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