Small changes, big impact: CFOs adopt the new era of digital finance

As artificial intelligence gets more intelligent and accuracy rates increase, the most reserved cohort of corporate India is now open to experimenting with this technology. Chief financial officers, finance heads and leaders have so far been hesitant to deploy AI-based enterprise systems at scale, as they were not confident enough about how AI could deliver on elements of trust, accuracy and a tangible return on investment. However, at a recent roundtable conference organised by FinancialExpress.com and Oracle, CFOs outlined the progress they had made with accepting and deploying AI in their organisations. Two roundtables of some of India’s leading CFOs discussed these two topics: AI-enabled agility – integrating predictive insights into financial planning – and automation and intelligence – transforming finance operations for efficiency and insight.

AI-Enabled Agility: Integrating Predictive Insights into Financial Planning

From a CFO’s perspective, it was interesting to note that the conversation has shifted from “If” they should adopt AI to “How” they can effectively deploy solutions. The concerns many CFOs voiced still centred around eliminating bias and accuracy with predictive analytics. Most CFOs at the table had already deployed or were in the process of deploying enterprise-level AI, not just from an automation perspective, but for improved forecast accuracy with the ability to link vast data sets with non-linear relationships – be it in the field of healthcare, telecom or supply chains in the food business. Over time, AI-enabled systems have become better at predictions, providing the CFOs with the clarity on return-on-investment they need.

One point of concern that was shared was over-reliance on AI predictions. Finance professionals can accept AI as a powerful co-pilot, not a replacement. They advocate balancing automated insights with human judgement. While AI-enabled systems such as Fusion can provide updated reports, human expertise is still critical for decision-making.

Finance professionals pointed out one hurdle they have faced is integrating new AI-driven tools with legacy systems. Data silos, incompatible formats, and a lack of standardised APIs complicate its deployment. Leaders at the table pointed out that for transparency and agility, a single, unified platform for financial forecasting is essential. It eliminates inconsistent user experiences and gives all departments, from marketing to finance, a common, reliable data set.

As regards governance and compliance, most finance leaders have established or are investing in clear policies for data privacy, model validation, and audits to ensure that all AI-driven reporting is explainable and transparent, helping the CFO become more agile and efficient.

Automation and Intelligence: Transforming Finance Operations for Efficiency and Insight

According to Deloitte, globally, nearly 80% of enterprises already use or plan to use some form of finance automation. Against this backdrop, CFOs are recalibrating their role: less of a navigator tracking the past, more of a futurist anticipating the future. This was the clear message from India’s finance leaders at the second roundtable.

The conversation underscored that intelligent automation is no longer about reducing headcount; it is about redeploying human capital to higher-value tasks while machines take over the drudgery of manual data entry, reconciliations, and repetitive reporting. Routine finance tasks such as invoice processing, compliance checks, and reconciliations are increasingly automated, allowing teams to focus on analysis rather than administration. With AI and ML models embedded, systems are becoming predictive, flagging anomalies before they become risks and forecasting with greater accuracy.

The speakers acknowledged that scalable automation solutions exist for immediate challenges but cautioned that pre-built AI tools are not a silver bullet. While they cut deployment time and cost, they still require training on organisation-specific data, and governance frameworks must be layered in. Some leaders stressed that “out-of-the-box AI can accelerate adoption, but without tailoring, it risks being generic.”

As automation penetrates deeper into budgeting and forecasting, CFOs face a dual challenge: improving speed and agility while preserving accuracy and control. Finance leaders agreed that automation cannot come at the expense of governance. Security, data integration, compliance, and auditability remain non-negotiable. A recurring theme during the discussion was the fragmentation of data across systems. Intelligent automation delivers its full value only when it unifies multiple sources of truth into a single view, and without integration, AI risks amplifying silos rather than breaking them down.

However, technology alone does not transform finance. Leadership does. CFOs highlighted the need to foster a culture that embraces automation while ensuring transparency and accountability. Upskilling teams to work alongside AI, setting clear governance standards, and embedding compliance into workflows were cited as critical to sustaining adoption.

As finance functions evolve into real-time intelligence hubs, the depth of AI/ML integration will increasingly correlate with agility in decision-making. Yet, the consensus was clear: CFOs must be selective. Not every process needs automation; not every AI use case adds value. The priority is to align tools with strategic outcomes. In the end, the roundtable echoed a common refrain: Technology will continue to evolve, but it is the finance leader’s vision that determines whether automation becomes merely a cost-cutting lever or a strategic engine for growth.

Participants at the 4th Edition of FE Finance Leadership Dialogue