Finance AI at scale: Technology enabling finance transformation

Reasons for finance transformation

Finance leaders, especially those managing complex or global operations, have a lot on their plates. On the one hand, they need to achieve a variety of goals: from improving forecasting accuracy and supporting decision-makers with data insights to ensuring compliance and adhering to cybersecurity standards. On the other hand, they contend with numerous challenges, such as reducing risk, cutting costs, and even modernizing complex legacy systems.

Finance automation software and various technologies that benefit from the use of AI in finance can help CFOs and other finance leaders achieve those goals and overcome the challenges. The key is to understand how to put together a solid platform that supports AI-enabled end-to-end processes, so that you can develop a blueprint for finance transformation that aligns with your unique goals.

At SAP, finance management has long been recognized as the backbone of efficient business operations and is quickly becoming a strategic driver for growth in enterprises. We understand the importance of providing finance leaders with the right tools to drive finance automation and modernization. In this practical guide to finance transformation, we:

• Break down the most common challenges and goals that can be addressed by implementing finance AI and other technologies.
• Discuss practical use cases of finance AI and the realistic benefits of finance transformation.
• Analyze proven business results that we’ve seen some of our customers achieve with SAP, finance modernization stories, and real-world examples of customer adoption.
• Address some of the common misconceptions about finance AI and answer a few frequently asked questions about finance transformation.

This guide provides actionable insights into AI-supported finance transformation.

Modern challenges finance leaders face

Some of the most common finance challenges include:

• Slow financial close
• Inaccurate financial forecasting
• Lack of transparency and siloed information
• Decision-making that needs real-time insights
• Compliance complexity
• Cybersecurity and data protection demands
• Complex legacy systems
• Rising costs
• Imperative to reduce risk

Let’s break down a few of these in more detail and highlight how technologies like SAP Cloud ERP Private can help address these challenges and finance transformation.

Slow and manual financial close processes due to a lack of visibility

Legacy ERP systems, manual processes, and siloed data make it difficult to close the books quickly and accurately. This, in turn, delays decision-making, increases costs, and introduces certain compliance risks as teams feel rushed and overwhelmed. The most typical causes are:

• Manual processes: Email-based approvals, manual data gathering and entry, and spreadsheet-based reconciliations.
• Data siloing: Data is spread across legacy ERP systems, subsidiaries, or even business units.
• Lack of standardization: Accounting policies, data governance, and workflows vary across business units.
• Limited visibility: Controllers can’t identify delays until it’s too late due to a lack of end-to-end process integration and visibility
• Scale: Massive volume and complexity of processes create an overwhelmingly large workload.

Technology highlight

Technologies that can help address these problems include finance automation software, a unified data landscape, and a comprehensive, enterprise-grade suite of solutions that integrate end-to-end—not just within finance, but across the entire supply chain, procurement, HR, and other key business functions. In large, complex organizations, the most effective solution is often to move from legacy ERPs, especially on-premises systems, to a modern platform and solutions, such as SAP Cloud ERP Private.

At SAP, accounting software and solutions for financial close are considered integral to the core financial management and enterprise management processes. These not only improve the overall efficiency of close processes, but also help establish better end-to-end visibility. Serving as a single source of financial truth and made more accessible, thanks to AI-enhanced user guidance, they support decision-makers and accelerate entity and group close with finance automation.

Complex compliance, cybersecurity, and regulatory demands

Keeping up with changing regulations requires significant manual effort and increases the risk of errors. At the same time, failing to keep up with these demands can cause serious consequences, such as:

• Cost increase: Fines and penalties for regulatory violations, spikes in audit costs, and even restrictions posed by regulators can make incidents of non-compliance very costly.
• Reputational damage: Compliance issues or a known cybersecurity failure (such as a data breach) can reduce investor confidence, erode customer and partner trust, and even undermine talent acquisition.
• Operational strain: Leadership dealing with crisis management, teams working around restrictions imposed by regulators, all under increased scrutiny—these are just a few of the knock-on effects of non-compliance.

Technology highlight

Governance, risk, and compliance (GRC) solutions can help. However, it’s important to select those that are integrated, automated, and embedded. What does that mean? They must work with the entire suite of finance management solutions you use, or better yet, be embedded, so compliance and cybersecurity measures are built in rather than added as an afterthought. Deep, AI-supported finance automation and integrated risk assessment can help shift to proactive control and minimize the risk of human error.

Additionally, dedicated cybersecurity solutions are employed to identify, analyze, and neutralize cyberattacks, thereby protecting sensitive business data and applications. Enterprise threat detection typically requires real-time security information and event management (SIEM) capabilities.

High operational costs

A number of inefficiencies can cause unnecessarily high costs in financial management:

• Legacy ERP: Highly tailored, outdated solutions and customization-heavy systems are expensive to maintain and slow to adapt to changing business needs, making integration of new technologies unjustifiably costly.
• Manual operations: From quote-to-cash to travel and expense management, from treasury and working capital optimization to contract management—a lack of intelligent, AI-supported finance automation denies finance teams a strong advantage and, ultimately, results in higher operational costs.
• Difficulty getting business insights: CFOs are under constant pressure to provide sharper, actionable insights to drive business growth and manage risk. Without the right tools to collect, process, and analyze data in real time, finance leaders must dedicate more time and resources to provide accurate insights quickly. Inaccurate forecasting can result in lost business opportunities.

Technology highlight

There are a number of ways to reduce costs. A powerful in-memory platform that provides real-time insights and advanced analytics would enable faster, more informed financial decisions and support accurate financial forecasting.

Another approach is made possible by the increasing use of AI in finance. Intelligent, AI-supported finance automation software would make a wide range of tasks more efficient. It can be especially effective if you opt for platforms that offer comprehensive financial management functionality, supporting complex, multinational operations, global compliance, and industry-specific requirements. Finance operations and challenges can vary significantly by industry.

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Benefits of finance transformation and use cases for finance AI

When we talk about finance transformation that relies on technology supported by embedded AI, we speak from experience—specifically, the experience of our customers who have achieved tangible results with SAP Cloud ERP Private and other offerings from SAP (accounting software, business data cloud solutions, and more).

The benefits of finance transformation we typically see include:

• Improved accuracy: Forecasts become more precise and accurate, business insights more reliable, and compliance and regulatory processes less vulnerable to human error.
• Accelerated delivery: Financial close tasks are completed faster, real-time financial insights support agile and confident decision-making, and modernization projects take less time.
• Reduced costs: Intelligent finance automation makes operations more efficient without compromising on compliance, and
• Better visibility: Real-time, end-to-end visibility into working capital, liquidity, and treasury operations enables faster decision-making and better control over spending.
• Smarter planning: Supported with sharper business insights and real-time visibility, finance leaders can make plans with confidence and adjust strategy quickly if needed.

Real-world examples from companies using solutions from SAP: Finance transformation stories

BT Group: Finance transformation with SAP

Pfizer: Automating complex financial closing cycles while simplifying regulatory reporting

Amadeus: Combining a finance transformation with migration to the cloud

The finance AI momentum

For the vast majority of organizations, embedded AI has become a key factor in ERP investment decisions—and with good reason. The use of AI for financial analysis is just one example of many. Embedded AI copilots and predictive modeling enable smarter decision-making through real-time financial insights, while AI-enhanced automation has use cases such as:

• Accelerating closes
• Supporting planning
• Simplifying compliance
• Increasing real-time visibility

To show CFOs how SAP Cloud ERP Private with embedded AI delivers trusted data for customer-specific finance AI scenarios, helps drive ROI, and accelerates finance transformation, we will host a live SAP webinar. Join us on January 29 to analyze real-world examples, ask questions, and see how CFOs use finance AI to accelerate closing, forecasting, and decision-making.

FAQs