Finance teams are under growing pressure to forecast more frequently, explain performance faster and make greater use of AI — without destabilizing the ERP systems, spreadsheets and established controls that already underpin financial operations.
A new partnership between Sikich and Datarails is taking aim at that challenge. The companies will combine Sikich’s industry, technology and advisory expertise with Datarails’ FP&A technology to help organizations modernize planning, reporting and financial analysis while retaining existing systems and familiar finance workflows.
The collaboration is initially focused on digitally regulated industries including life sciences, insurance and legal services, where the demand for faster financial insight has to be balanced against governance, accuracy and operational continuity.
Rather than positioning AI-driven planning as a replacement for ERP or Excel, the partnership reflects a more pragmatic direction emerging across enterprise finance: adding intelligence around established systems of record while reducing the manual processes that continue to sit between them.
Modernizing FP&A Without Replacing the Finance Stack
For many organizations, ERP modernization does not automatically solve the challenges finance teams face outside the core transactional system.
Data may reside in ERP and other operational platforms, while forecasting models, management reports and scenario planning continue to depend heavily on spreadsheets. As organizations become more complex, that model can create problems around manual consolidation, version control, data refreshes and the amount of time required to assemble recurring reporting packages.
Sikich and Datarails are approaching the issue without requiring finance teams to abandon Excel.
Datarails’ platform is designed to connect financial and operational data while applying AI across planning and reporting processes. Its capabilities include automating consolidation and data refreshes, supporting variance analysis, and generating management and board reporting from current financial data.
The objective is to shift finance resources away from assembling the reporting deliverable and toward understanding the business implications behind it.
“Organizations need financial planning processes that can evolve with the complexity of their businesses without disrupting the systems and workflows their teams already rely on,” said William Tamulynas, Principal at Sikich.
Tamulynas said combining Sikich’s industry and technology experience with Datarails’ AI capabilities could help finance teams remove more of the manual assembly work from reporting and spend more time on decision-making.
ERP Remains the System of Record
One of the more significant aspects of the partnership is what it does not attempt to replace.
Sikich and Datarails say the combined approach can complement existing ERP environments, including NetSuite, allowing businesses to strengthen FP&A processes while keeping their established systems of record in place.
That distinction matters as AI becomes more deeply embedded in finance technology.
ERP systems remain responsible for much of the governed transactional data on which finance depends. But planning, forecasting and management analysis frequently require information from multiple systems, entities and operational sources. The resulting gap between recording transactions and interpreting their implications has created space for a growing layer of financial intelligence around the ERP core.
For organizations with multi-entity or multi-currency operations, that layer becomes particularly important. Frequent reforecasting, consolidated planning and scenario analysis can become increasingly difficult when finance teams have to manually gather and reconcile information before analysis can begin.
The Sikich-Datarails partnership is designed to address that middle ground: preserving the transactional foundation while creating a more connected planning environment around it.
AI in Finance Raises the Importance of Governed Data
The announcement also points to a wider question facing CFOs as generative and analytical AI move into financial workflows: what data should AI be allowed to work from?
For regulated businesses in particular, producing an answer quickly is not sufficient. Finance teams need confidence that analysis is based on consistent information and that the underlying numbers remain controlled and traceable.
Datarails positions its FinanceOS platform as a governed foundation for financial and operational data, allowing AI capabilities to work from the same information finance teams already use.
“Sikich understands the pressure finance teams in regulated industries are under to report faster without losing control of the numbers,” said Didi Gurfinkel, CEO and Co-founder of Datarails.
According to Gurfinkel, the goal is to allow teams to continue working in Excel while AI operates from a common financial data foundation.
This approach illustrates an important shift in the enterprise AI discussion. The question for finance leaders is increasingly moving beyond whether AI can generate a forecast, summarize a variance or produce a report. The more consequential issue is whether those capabilities can be introduced without creating another disconnected layer of information or weakening financial governance.
Excel’s Role in the AI-Era Finance Function
The continued role of Excel is another notable element of the partnership.
Despite years of finance transformation and the expansion of cloud ERP, spreadsheets remain deeply embedded in planning and analysis. Finance professionals have built models, reporting structures and working practices around them, making wholesale replacement both technically and organizationally difficult.
Instead of treating that familiarity as something that must be eliminated, the partnership takes the position that modernization can happen around existing ways of working.
That could prove increasingly relevant as finance technology vendors look to accelerate AI adoption. The success of new tools will depend not only on their technical capabilities but also on how effectively they fit into the processes employees already understand.
For CFOs, the challenge is therefore less about choosing between spreadsheets, ERP and AI than determining how those layers should interact — and where governance should sit between them.
From Financial Reporting to Continuous Decision Support
The broader direction is toward a finance function in which reporting, planning and analysis become less dependent on periodic manual assembly.
Automated data refreshes can shorten the distance between transactional activity and management insight. AI-assisted variance analysis can help teams investigate changes more quickly, while flexible scenario planning can give decision-makers a clearer view of how different assumptions could affect future performance.
But achieving that transition does not necessarily require organizations to replace their existing ERP infrastructure.
The Sikich and Datarails partnership instead reflects a more incremental model for finance transformation: maintain the systems that govern core transactions, connect the data surrounding them, and introduce automation and AI where they can reduce manual work and improve analysis.
For ERP leaders, that is a notable development. As AI reshapes financial planning, the ERP system may remain firmly at the center of the enterprise data architecture while a more intelligent layer develops around it.
The emerging finance stack is therefore unlikely to be defined by AI replacing ERP or spreadsheets outright. It may instead be defined by how effectively organizations connect all three — ERP as the trusted system of record, familiar tools as the working environment, and AI as an increasingly active layer of analysis and decision support.
ERP News Editorial Team
The ERPNews Editorial Team covers global developments in ERP (Enterprise Resource Planning), enterprise software, cloud platforms, AI, automation, and digital transformation, providing independent news and editorial analysis for senior business and technology leaders. Our reporting focuses on market signals, strategic shifts, and enterprise impact across the ERP and enterprise technology ecosystem.
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