AI in Accounting: Better Data, New Opportunities for Companies 

XRechnung, ZUGFeRD, and other CEN-compliant formats are now the standard for domestic B2B e-invoices. While e-invoicing presents new challenges for companies, it also opens up enormous opportunities, especially when combined with artificial intelligence (AI).

The switch to machine-readable formats enables automated processing of invoice data, unlocking a wide range of applications for AI. From many conversations with our customers, we know that the topic of e-invoicing currently causes more headaches than euphoric celebrations in most companies. That’s why we want to move past the stress of transitioning to new invoice formats and take a broader look at the topic: the immediate future of invoice processing. 

With the transition to e-invoicing, payment processes will become more cost-effective, faster, and less error-prone. E-invoicing is also expected to have a profound impact on corporate accounting within just a few years. But how so? With the complete shift to digital e-invoice formats, the reliability of invoice data increases to nearly 100%. In turn, this serves as the perfect basis for completely reimagining accounting processes by incorporating artificial intelligence.

Opportunities for AI in accounting with e-invoices

The higher the quality of the data, the better AI models can be trained. As structured data sets, e-invoices provide the ideal data foundation for AI training. In particular, bookkeeping processes could be significantly improved in many areas. Here’s an overview of where we see opportunities in the near future:

• Automation of accounting processing: Accounting processes can be significantly accelerated and made more efficient by automating the processing of e-invoices. Manual activities such as data entry, account assignment, and posting can be largely automated. 
• Improved financial planning and analysis: By analyzing structured accounting data, companies can gain detailed insights into their finances and make informed, data-driven decisions. AI helps to identify trends, make forecasts, and identify risks. 
• Fraud detection: AI can be used to detect fraudulent activities in accounting, for example, by recognizing unusual patterns or suspicious transactions. 
• Optimization of cash flow management: By automating invoice processing and analyzing financial data, companies can better plan and manage their cash flow.  
• More efficient supplier management: Companies can better understand and optimize their supplier relationships by analyzing invoice data. 
• Process optimization: By analyzing invoice data and the associated processes, companies can identify inefficiencies and optimize their operations. 

For these reasons, the combination of AI and e-invoices creates a multitude of opportunities for companies that go far beyond the digitalization of invoice workflows. The automated processing and analysis of invoice data using AI models provides accounting departments with intelligent tools that can take the handling of invoice data to a new level. Let’s delve deeper into the possibilities already on the horizon. 

AI and E-Invoices: Concrete Use Cases

Automation is the keyword, with excellent prospects in store for accounting and bookkeeping. Artificial intelligence and e-invoicing promise greater efficiency in accelerated billing processes and improved forecasting of a company’s financial transactions.

Automation of routine tasks

AI systems can automatically capture invoices and independently extract the information contained within them. This process not only includes reading amounts and payment terms; it also includes identifying suppliers, items, and taxes. Significant opportunities for efficiency arise, particularly in the following stages of invoice processing:

• Automated invoice verification: AI can automatically check invoices for formal correctness, compliance with orders and contracts, and plausibility. 
• Automated account assignment: AI can automatically assign invoices to the correct accounts, thereby accelerating the posting process. 
• Predictive analytics: AI can analyze historical billing data to forecast future cash flows and financial trends. 

This way, data collection in accounting will become even more automated in the coming years than is already possible today through the use of digital tools. Instead of spending time on cumbersome routine tasks, accountants will have more time to concentrate on more complex tasks. 

Challenges Facing AI in Accounting

Despite the numerous emerging benefits, companies face a range of challenges. Four key areas of action can be identified here, which decision-makers in companies should focus on to ensure they take advantage of AI in accounting.

• Data quality: High data quality is crucial for the successful implementation of AI. Companies must ensure that their data is clean, complete, and consistent. 
• Integration into existing systems: The integration of AI solutions into existing accounting systems can pose challenges. It is vital to choose compatible and flexible solutions. 
• Data protection and data security: When processing billing data, the applicable data protection regulations and security standards must be complied with. 
• Acceptance among employees: It is helpful to involve employees in the change process at an early stage and convince them of the benefits of AI.

The Bottom Line: AI Will Fundamentally Change Accounting

The German e-invoicing mandate combined with AI offers companies enormous potential to optimize financial processes, enhance data quality, and unlock new business opportunities. Businesses that engage with these technologies early on can gain competitive advantages and strengthen their future viability. We advise that you connect with software solution providers and AI experts to analyze individual requirements and implement the right solutions. After all, data-driven decision-making will be a crucial success factor in an increasingly digitalized economy.