Businesses are increasingly adopting AI-powered financial management, yet the actual outcomes often fall short of expectations. A mid-sized manufacturer, for example, spent millions on process automation and integrated finance-IT systems to boost collaboration and decision-making. In reality, only the finance department drove the initiative, with other business units showing minimal involvement, leading to a significant disconnect between the system and actual operations. The company ultimately rated the transformation as "poor."

A professor specializing in corporate financial digitalization, who conducted field research on over 100 companies, notes that this scenario is widespread. His findings reveal that while more than 80% of surveyed firms have pursued financial digitalization for over a year, less than 20% believe it has substantially improved efficiency, risk control, or decision-making value. This highlights a stark contrast between high adoption rates and low effectiveness.

Regulatory bodies are also taking steps to address this. On July 19, Zhang Juan, Deputy Director of the Accounting Department at the Ministry of Finance, announced during the World Artificial Intelligence Conference that the ministry is drafting guidelines to accelerate accounting digitalization. The guidelines aim to coordinate efforts in areas like regulatory framework, data standards, practical application, talent development, and overall strategic design.

The Difficulties Are Many

Most companies have their own unique struggles with financial digitalization. The CFO of a large local state-owned investment group explained that years ago, they purchased a comprehensive digital financial system intended to unify data across all departments to enhance analytical and decision-making capabilities. In practice, the four core systems—finance, engineering, financing, and HR—remained completely isolated. A lack of unified coding standards for clients and projects led to chaotic data and severe data silos. Consequently, the finance department had to dedicate two staff members for nearly a week each month to manually reconcile and organize data, making the much-heralded digital finance vision nothing more than a mirage.

Another medium-sized engineering company invested millions in a full suite of smart financial analysis systems, but failed to assign any specialized digital personnel to operate it. This left features like early-warning alerts and business dashboards idle. Furthermore, the company never conducted any post-implementation review to assess whether the system improved business operations or fund management, making it impossible to gauge the return on investment. Meanwhile, they continue to pay substantial annual maintenance fees for the system, which has effectively become a showpiece.

The professor adds that these challenges are far from isolated. His research shows that about 70% of surveyed companies suffer from severe data fragmentation, with systems unable to share information. Fewer than 10% report smooth cross-departmental collaboration. Over 80% admit they lack the hybrid talent skilled in both finance and digitalization. More than half of the companies have not established a quantifiable evaluation framework for digital finance, making it difficult to scientifically measure its value, which often leads to initiatives that "start with a bang and end with a whimper."

The root causes are four common pitfalls: prioritizing one-off project delivery over long-term iterative maintenance, causing a gap between implementation and application; lacking top-down, enterprise-wide reform design and leadership, which creates cross-departmental barriers; failing to invest in developing or hiring specialized digital finance talent, which hinders system optimization; and lacking a full-cycle management mechanism of "planning, execution, evaluation, and optimization," with no regular reviews or scientific performance assessments.

Liu Jie, the CFO of a pharmaceutical distribution company, found that her company exhibited these same issues. Two years ago, they introduced a digital finance system to integrate data from procurement, warehousing, logistics, and sales, aiming to shift from post-event recording to real-time analysis and strategic support. Over the past two years, Liu Jie observed that only the finance department was actively pushing the project. Sales and warehousing departments resisted cooperation, continuing their old habit of entering transaction data 3-7 days late. This prevented the smart risk control models from having real-time data, rendering the early-warning functions useless. She repeatedly escalated these issues to senior management, but no dedicated task force was formed, nor was data collaboration incorporated into departmental performance metrics.

Liu Jie says that since the beginning of this year, the system's application has nearly stalled, and negative consequences are mounting. Due to delayed data entry, the company has been unable to efficiently allocate business revenue for operational expenses, forcing it to borrow over 30 million yuan from banks to manage cash flow, incurring nearly one million yuan in extra interest. Senior management has repeatedly asked the finance department to strengthen fund management and reduce borrowing. Liu Jie finds this difficult because the current system cannot accurately reflect the company's full cash flow. A large amount of business revenue remains trapped in branch accounts and cannot be quickly consolidated for use, making it impossible to replace bank loans.

These bottlenecks create a vicious cycle: missing data standards lead to poor processes, which breed business unit resistance, worsening cross-departmental collaboration, breaking the value creation loop, hindering digital talent development, and preventing deeper application of the technology. Unless this cycle is broken, corporate financial digitalization will remain stagnant.

In his survey of over 100 companies, the professor noted that about 51% privately admitted their digital finance transformation had only achieved basic automation, failing to penetrate core business scenarios. Another 31% said it remained at a showcase or pilot stage, lacking deep integration with actual workflows. Some companies, finding the investment huge with minimal business returns, are even considering reverting to manual processes.

The CEO's Role is Critical

To overcome these obstacles, companies have tried various solutions, such as phasing system expansion based on real business needs, building a unified data base and standardizing processes to break down silos, implementing top-down cross-departmental coordination mechanisms, fostering layered talent development, establishing performance evaluation loops focused on value output, and implementing tiered data security controls. However, the success of these solutions hinges on whether the CEO treats it as a top-priority project, not just the finance department's job.

Zhou Ye, Chairman and CEO of Huifu, deeply understands this. Six years ago, when his payment institution began its digital transformation, he stated that the finance department should not just be a management unit but a part of the business operations. He mandated that financial management software, functions, and permissions be embedded into all business processes. Zhou Ye found that the key to successful implementation is the CEO's overall leadership. Over the past six years, he has constantly communicated with all departments, requiring them to cooperate, correct course, break down barriers, and standardize data governance.

"I often tell employees that in traditional operations, financial management is like a car's rearview mirror; I only learn last month's financial data on the fifth working day of this month, leading to decision-making delays. But in the digital finance era, it's like a car's smart navigation system, allowing the company to understand ongoing operations in real-time and make faster, better decisions," Zhou Ye said.

He adds that the CEO faces significant tests during this process: first, they must abandon old operational thinking and view the transformation from a strategic perspective of how digital finance can enhance business capabilities. Second, they must be willing to spend money, including on system iteration and talent acquisition. "For payment institutions, digital finance has another layer of importance," Zhou Ye noted. As client companies have diverse revenue channels and complex fund scheduling needs, digital finance can drive business model innovation by embedding AI tools into all processes.

Huifu's clients now need to collect payments from dozens of online and offline channels, both domestic and international. They want a unified payment solution and need to know where money comes from, where it's stored, and how to schedule it intelligently. This has transformed payment companies from terminal collectors into the starting point for clients' digital finance journeys. Huifu uses its Doujin system to connect clients' business-side VAM accounts with their financial-side TMS systems, enabling granular accounting by store, channel, and product line. This allows every transaction to be traceable, with automated cross-platform order reconciliation, bank statement matching, and automatic generation of accounting vouchers, solving problems like scattered accounts, heavy manual workload, and fragmented data.

Wang Lihong, Chairman of Subway China's Board, values how digital finance supports strategic transformation. Driven by its strategy to deeply penetrate the Chinese market, Subway China now has over 700 directly operated stores and nearly 500 franchise stores. "Two and a half years ago, we had only single-digit direct stores. In June, we were opening nearly one new store per day," Wang Lihong said. These thousands of stores generate a massive volume of small, high-frequency transactions from various online and offline channels, including discount coupons and promotional codes. This creates a complex environment for each store's revenue collection, accounting, risk control, and tax compliance, posing significant challenges to financial management and the market expansion strategy.

To meet these challenges, Wang Lihong drove the creation of an integrated smart financial system to automate accounting, risk control, and fund allocation. Throughout the process, she extensively communicated with all business units, helping them understand the system is not just a tool but a comprehensive system ensuring accurate front-end sales and back-end financial processing. She also spent considerable time getting departments to improve data collection and sharing, shifting the system's role from reviewing past performance to predicting future trends, thus enhancing decision-making efficiency. "The entire management team is very supportive. They realize AI is more efficient than manual work, and digital transformation is an inevitable trend," she said. To address employee concerns about AI replacing their jobs, the company adjusted roles, implemented multi-skilling in finance, and encouraged programmers to transition into product roles.

The professor concludes that to solve the "high adoption, low effectiveness" bottleneck, CEOs must recognize that AI is reshaping corporate competition. Future core competitiveness will depend on intelligent decision-making, data governance, and organizational synergy. Only when CEOs fully grasp the real value of digital finance for their company's future can they confidently lead the effort to integrate finance and business, manage data across its lifecycle, cultivate talent, redesign processes, and create a closed-loop performance system, turning the promise of digital finance into reality.