Data Maturity Drives 2x Higher AI Trust for CFOs, Lucanet Research Reveals

New research reveals that fragmented data infrastructure is costing mid-market and enterprise organizations millions, undermining the efficacy of financial AI investments. For fintech professionals, the findings highlight that while 81% of budgets are set to expand, operational success depends on eliminating legacy spreadsheet reliance and establishing a single source of truth before deploying advanced automation.

What was announced

Lucanet and Ascend2 Research surveyed 425 senior finance leaders across six international markets to assess enterprise AI readiness. The report identifies a significant "operational leak" caused by disconnected technology stacks and a persistent reliance on legacy tools. Despite 78% of finance teams having deployed an enterprise ERP platform, 36% continue to rely heavily on manual spreadsheets. This fragmentation has tangible consequences: 61% of organizations reported direct financial losses or unexpected costs due to unoptimized infrastructure. For 44% of those affected, losses exceeded €500,000 in the last 12 months, while 20% saw damages surpass €1 million.

Confidence in data remains a primary hurdle for strategic execution. Only 47% of finance leaders fully trust the data used for major business decisions, and 37% lack confidence in their overall technology stacks due to integration gaps and scalability limits. However, the presence of a single source of truth significantly shifts these figures, making leaders nearly twice as likely to be very confident in their technology stack compared to those without one (81% versus 42%).

While 95% of leaders trust AI-generated recommendations to some degree, strong confidence is limited to 45% overall. The research highlights that the fastest ROI for AI is currently found in automated narrative reporting (36%), cash flow prediction (33%), and anomaly detection (33%). Geographic priorities vary, with Germany focusing on auditability and internal controls (42%), while the UK (49%) and Netherlands (40%) prioritize data accuracy.

The companies involved

Lucanet is a global provider of financial performance management solutions, specifically designed for the "Office of the CFO." The company has established a significant market presence, recently surpassing €200 million in Annual Recurring Revenue (ARR) as it continues its international expansion, including a recent move into the Japanese market. Lucanet focuses on simplifying complex financial processes through a unified platform that integrates consolidation, planning, and reporting, aiming to replace manual workflows with automated systems.

Ascend operates as a financial operations platform, particularly prominent within the insurance sector. The company recently expanded its capabilities and market reach through a merger with Honor Capital, a move aimed at creating a comprehensive financial operations ecosystem for insurance professionals. Together, these organizations represent a segment of the fintech market dedicated to moving enterprise finance away from manual, spreadsheet-based workflows toward automated, data-driven environments. By combining Lucanet’s focus on CFO-level strategic tools with Ascend’s operational infrastructure, the research reflects the broader industry push toward "autonomous finance" and the necessity of robust data governance in high-stakes corporate environments.

What FF News has reported before

FF News has closely followed the evolution of both companies as they lean into automation and global growth. In June 2026, we covered how Lucanet Unveils AI Agent Family to Drive Autonomous Finance for the Office of the CFO, marking a significant step toward integrating generative AI into core financial workflows. This followed news of the company's global growth strategy as Lucanet Brings Its CFO Solution Platform to Japan, Advancing Global Growth Strategy as ARR Surpasses €200 Million. Additionally, we reported on the infrastructure side of the market when Ascend and Honor Capital Announce Agreement to Merge, Creating the First Complete Financial Operations Platform for Insurance, highlighting the trend of consolidation in financial operations technology.

What this means

This research underscores a sobering reality for the "AI-first" movement: the enterprise finance sector is hitting a ceiling imposed by legacy debt. The fact that over a third of enterprises still lean on spreadsheets despite having ERPs suggests that the "last mile" of financial data remains stubbornly manual. This puts immense pressure on traditional ERP vendors to improve native integration or risk being sidelined by specialized middleware that can provide the "single source of truth" leaders crave. For the broader market, the focus is shifting from the glamour of predictive AI to the unglamorous but essential work of data hygiene and infrastructure hardening. The open question is whether firms will use their expanding budgets to fix these foundations or continue to layer expensive AI on top of broken processes.