The Quiet Rise of AI in Finance: What’s at Stake for Individuals and Businesses

The increasing presence of artificial intelligence (AI) in finance has been a gradual but significant shift over the past few years. While some have touted AI as a revolutionary tool that can automate routine tasks and provide instant answers to complex financial questions, others remain skeptical about its potential impact on decision-making processes.

One key area where AI is making a significant contribution is in data-heavy finance tasks such as bookkeeping, reconciliation, invoice processing, reporting, and compliance. Businesses are already seeing finance teams spend less time on manual interventions, with faster processing times and more timely financial information. According to Pei Fu Hsieh, Co-founder of AI Accountant, this shift has significant implications for individuals looking for simple answers to complex financial questions.

For instance, an individual can ask a question like “How much cash do I have?” or “Who owes me money?” and receive instant answers from an AI system. However, as Swaroop Repaka, VP Product at ClearTax, points out, the role of AI remains limited in judgement-heavy areas such as tax positions, treaty interpretation, and transfer pricing.

The Next Phase: Achieving Larger Goals with AI

As AI adoption accelerates, we can expect to see significant gains in areas such as faster reconciliations, higher input tax credit realization, fewer notices, and greater automation. However, Repaka warns that fragmented data, poorly defined use cases, and treating AI as a software license rather than an operational capability remain key barriers.

The distinction between AI’s role in assisting with preparing or understanding a tax position versus becoming the authority responsible for the taxpayer’s final filing is crucial. While AI can provide instant answers to complex financial questions, it does not replace human judgment and expertise in areas that require accountability and professional expertise.

Redefining Decision-Making Processes

The use of AI in finance has significant implications for decision-making processes at both individual and organizational levels. As Rajosik Banerjee, partner and national head, risk and finance advisory, KPMG India notes, AI is moving beyond automation in finance and becoming a catalyst for process transformation.

Organizations must redesign end-to-end finance processes around AI-enabled workflows to unlock the full potential of AI. This requires human judgment to remain critical for decisions that require accountability and professional expertise. CFOs must ensure AI operates within a robust governance framework supported by clear accountability, transparency, strong controls, and regulatory compliance.

Adoption Inequality and the Need for Governance

The adoption of AI in finance remains uneven across industries and geographies. Deloitte’s research this year showed nearly 40 percent of Indian respondents reporting significant or full AI use compared to 28 percent globally. However, Krishna Dev Pathak, an investment expert, notes that the lack of standardization and governance frameworks has hindered large-scale adoption.

The implementation of AI in finance also raises important questions about data security and regulatory compliance. As organizations increasingly rely on AI for financial decision-making, they must ensure that AI operates within a robust governance framework supported by clear accountability, transparency, strong controls, and regulatory compliance.

The Future of Finance: Where Humans and Machines Intersect

As AI continues to make inroads into finance, we can expect significant changes in the way individuals and businesses approach financial decision-making. While AI has the potential to automate routine tasks and provide instant answers to complex financial questions, its role remains limited in judgement-heavy areas.

However, as Repaka notes, the next phase of AI adoption will focus on achieving larger goals with continuous monitoring of cash leakage, vendor risk, and audit processes. This requires a nuanced understanding of AI’s capabilities and limitations, as well as the need for human judgment to remain critical in areas that require accountability and professional expertise.

The quiet rise of AI in finance has significant implications for individuals and businesses alike. While AI can automate routine tasks and provide instant answers to complex financial questions, its role remains limited in judgement-heavy areas. As we move forward in this new era of finance, humans and machines must intersect to unlock the full potential of AI while maintaining accountability and professional expertise.