AI Reality Check: CFOs Highlight the Biggest Challenges for Mid-Sized Organizations

Anurag Bhagania, CFO, OneSource Specialty Pharma

Published on Financial Express CFO
Source: AI Reality Check: CFOs Highlight the Biggest Challenges for Mid-Sized Organizations

The finance leaders suggest that while AI promises significant gains for finance, its success will be determined less by the sophistication of algorithms and more by the strength of data, governance and organizational capability that supports them.

Artificial intelligence is increasingly finding its way into finance functions. As per CFOs, the real challenge lies not in the technology itself, but in preparing organizations to use it effectively.

We asked about the single biggest obstacle to AI adoption in mid-sized organizations today and responses from finance leaders point to a common theme: AI’s success will depend on strong data foundations, governance, skilled talent and enterprise-wide integration rather than standalone technology deployments.

Mandeep Mehta, Group CFO, PB Fintech says the biggest barriers for mid-sized organizations are ensuring data security and privacy while building a workforce capable of using AI responsibly. He believes that without the right talent and governance, organizations will struggle to unlock AI’s full potential.

Manoj Bansal, Vice President – Finance & Accounts, Bharti Realty, echoes the importance of foundational readiness. Fragmented financial and operational data spread across multiple ERP systems, billing platforms and spreadsheets remains the biggest obstacle, he puts forth and adds, “Before organizations can derive value from AI, they must invest significantly in cleaning, structuring and centralizing data—an effort that itself represents a major financial challenge.”

From a pharmaceutical manufacturing perspective, AI can act as a strategic enabler of operational excellence rather than merely an automation tool. Anurag Bhagania, CFO, OneSource Specialty Pharma Limited, says meaningful AI adoption begins with integrated, high-quality data across manufacturing, quality, supply chain and finance, backed by governance, data integrity and regulatory compliance. “Without this digital foundation, AI cannot generate trusted business outcomes.”

When it comes to returns on investment, finance leaders see AI making the biggest impact in areas that improve decision-making. Mehta expects the strongest ROI over the next two years to come from forecasting, planning, scenario simulations, risk management, treasury operations and M&A analysis through faster insights and improved operational efficiency.

AI’s greatest value, as says Bhagania, lies in reducing manual, documentation-intensive work while strengthening reporting, analytics and decision-making. According to him, in a highly regulated industry, AI can improve documentation accuracy, compliance monitoring, quality reporting and forecasting, while enhancing cash flow visibility and capital allocation.

Looking ahead, the CFOs also differ in where they would prioritize AI investments.

Mehta says he will focus on developing teams that can work effectively with multiple AI models. As specialized models emerge, he believes organizational agility will depend on people who know how to select and apply the right model for each business need.

Bhagania, meanwhile, is investing in enterprise-wide AI capabilities that connect business functions rather than creating isolated use cases. For him, AI is ultimately about building a more agile, intelligent organization capable of delivering speed, quality, regulatory excellence, and stronger customer outcomes.