SAP commissioned IDC to explore this topic and write this guest blog where IDC analyst Heather Herbst shares her insights on how high-quality, well-governed data gives CFOs a lever for financial performance and growth.

More than half of organizations today recognize that data quality is the linchpin for accurate AI results and financial performance. Yet as digital and AI transformations accelerate, many finance leaders find themselves grappling with fragmented data, slow reporting cycles, data without operational context, and inconsistent definitions across departments. The stakes are high: 44% of organizations report that data quality issues are a major contributor to AI projects failing to reach production, according to IDC's AI-Ready Data Storage Infrastructure Special Study: Worldwide Survey Read-Out of Findings (July 2025); organizations with robust data governance see up to three times greater ROI from their AI investments.

For finance professionals and IT buyers, the challenge is clear: Unlocking the full value of AI and digital initiatives hinges on trusted, well-governed data. CFOs are uniquely positioned to lead the charge, driving enterprise-wide transformation through disciplined data management, strategic governance, and cross-functional collaboration.

Why Data Quality Is the Foundation for AI Success

As organizations invest in AI, the importance of clean, complete, and timely data cannot be overstated. According to the IDC survey cited above:

• 52% of organizations view data quality as the most critical factor for accurate AI results.
• 55% call data quality the primary contributor to AI project success.

The same study projects that every $1 spent on AI solutions today could generate ~$5 in economic value by 2030 through increased productivity, reduced error rates, and optimized resource allocation.

Modern data platforms help mitigate the risk of fragmented systems, enhancing data accuracy and consistency for strategic decision-making and regulatory compliance.

Finance as the Catalyst for Enterprise Transformation

CFOs are increasingly stepping into the role of data and AI champions, bringing discipline and governance to the core of business operations. Traditionally, inconsistent definitions such as “account” in finance versus “customer” in sales have created competing versions of the truth, slowing down reporting and decision-making. When finance leads data initiatives, it establishes a unified approach that shifts the focus from manual reconciliation to delivering actionable insights. As a result, the top technology investment area for enterprise intelligence over the next 18 months is data management, closely followed by AI. Finance-led data initiatives ensure data is unified, governed, and trusted, enabling AI initiatives to accelerate real business impact.

Despite the promise of AI, data challenges remain a top concern for CFOs and IT buyers. IDC's 2024 Office of the CFO Survey found that a significant 58% of CFOs cited data challenges as a major barrier to effective AI and digital transformation, while 43% identify revenue recognition and accounting management (both closely tied to data quality) as top areas needing improvement. Siloed data was an obstacle for 55% of organizations, and issues such as inaccurate financial data and a lack of real-time visualization continued to slow reporting and increase manual reconciliation, according to IDC's AI-Ready Data Storage Infrastructure Special Study: Worldwide Survey Read-Out of Findings (July 2025).

To overcome these hurdles, an integrated business framework is essential for unifying financial and operational data with business context, enabling intelligent automation, and strengthening compliance. IDC's research found that organizations with AI-ready data experience 5x higher customer retention, 1.6x profit improvement, and 1.5x operational efficiency. Trusted data with context enable explainable, governed AI for forecasting and automation, connecting risk, performance, and strategy for better decisions. Ultimately, finance is elevated from a reporting function to strategic orchestration, positioning the CFO as the architect of enterprise data and value creation.

Actions to Take

Finance leaders need to champion data governance, integration, and cross-functional collaboration to drive effective decision-making. To do that, they must:

• Lead enterprise-wide data standards and establish a single source of truth.
• Invest in governance frameworks with embedded ownership, lineage, and controls.
• Prioritize data quality efforts on metrics tied to margin, cash flow, and compliance.
• Align with the CIO and Chief Data Officer to co-own data strategy and accountability.
• Treat context-rich, governed data as a financial asset fueling performance and resilience.

CFOs have an opportunity to drive measurable improvements in financial performance, operational efficiency, and AI success. By leading data quality and governance initiatives, finance teams can unlock enterprise-wide value, build trust in AI-driven insights, and position themselves as strategic leaders in the age of digital transformation.