Artificial Intelligence (AI) is no longer a buzzword reserved for tech conferences — it is now embedded in the way modern finance teams operate. According to KPMG’s latest Global AI in Finance study, 71% of companies worldwide already use AI in some form across finance, and nearly 100% expect to adopt it within the next three years. The global market of FinOps is more than $40 billion.
Importantly, finance is not evolving in isolation — it is among the top three functions globally with the highest AI-driven transformation potential, alongside customer service and supply chain. This means CFOs have a unique opportunity to embed AI as part of a larger organisational transformation, rather than treating it as a standalone finance project.
Why AI Is Needed in Finance Operations
The finance function has always been data-intensive, compliance-driven, and process-heavy. While digitalisation has brought speed, it hasn’t solved the complexity challenge. Companies adopting AI in finance are seeing up to 40% faster decision cycles — a competitive edge that’s hard to ignore. Avenues in which AI can help –
Operational Efficiency — Automated data entry, invoice processing, and workflow approvals.Data Insights & Forecasting — Predictive models for revenue, expenses, and market scenarios.Risk & Compliance — Proactive fraud detection, anomaly spotting, and real-time regulatory checks.Strategic Planning — Scenario modelling for M&A, capital allocation, and treasury optimisation.Talent Transformation — Upskilling finance professionals for high-value analytics and advisory roles.Cost savings and optimization — Leaner employee organisation can help in reducing costs and bring P&L efficiency.Source: Capgemini Research Institute, AI-powered business operations survey, February — March 2025
Current AI Use Across Finance
AI adoption is uneven across finance sub-functions, but momentum is accelerating:
Accounting & Financial Planning — Nearly two-thirds of companies are already piloting or widely using AI, leveraging real-time analytics and predictive reporting.Treasury & Risk Management — Around half of organisations use AI for cash-flow forecasting, credit risk assessment, and fraud prevention.Order-to-Cash (O2C) — AI is enabling automated invoice generation, intelligent payment reminders, dynamic credit scoring, and predictive collections to improve working capital cycles.Procure-to-Pay (P2P) — Intelligent procurement bots, supplier risk analysis, contract compliance monitoring, and automated payment scheduling are streamlining procurement and vendor payments.Tax Operations — Still lagging, but set to accelerate with generative AI’s ability to interpret complex regulations.Audit & Assurance — AI enables anomaly detection, real-time auditing, and predictive risk analysis.
Importantly, leaders — the top 24% of companies — use AI in twice as many finance use cases as the rest, including administrative automation, performance evaluation, and AI-generated financial scenarios.
Companies Driving AI in Finance
While global tech giants like Microsoft, SAP, and Oracle are embedding AI into enterprise finance platforms, a wave of AI-first startups is reshaping the landscape:
Bluecopa — Hyderabad-based platform offering AI-powered finance operations automation for CFO offices, reducing reporting times from days to minutes.HighRadius — Specialises in AI-driven receivables, treasury, and cash management solutions, widely used by Fortune 500 companies.Arya.ai focuses on AI models for risk assessment, cash flow forecasting, and financial analytics, useful for banks and large firms.AppZen — Uses AI for expense audit automation, compliance, and spend optimisation.Trullion — Automates lease accounting and revenue recognition with AI-based data extraction.Zeni — Offers startups an AI-powered finance team, from bookkeeping to CFO insights in real-time dashboards.
These companies are building solutions that remove manual bottlenecks, improve accuracy, and allow finance leaders to focus on strategic decisions.
The Way Forward — From Pilots to Scale
Over the next three years, several trends will define AI in finance operations:
Generative AI Goes Mainstream — Moving beyond pilots to enterprise-wide adoption in financial reporting, forecasting, and tax compliance.AI Finance Agents — Autonomous AI assistants collaborating across departments, geographies, and systems.In-House AI Expertise — CFOs building AI capability within finance teams instead of relying solely on central IT or external vendors.Governance & Assurance — Strong frameworks to ensure AI’s transparency, ethical use, and compliance with evolving regulations.Increased Budgets — AI spend projected to rise from 8.5% to 13.5% of IT budgets globally.
Conclusion
AI is no longer an experiment for finance — it is a strategic imperative. The early adopters are seeing outsized ROI, faster decision-making, and stronger talent retention.
The winners in this new era will not be those who merely use AI but those who embed it across all finance functions, combine it with strong human expertise, and build governance that inspires trust.
In finance, as in business at large, the shift has begun. The question is no longer “Should we adopt AI?” — it is “How fast can we scale it?”
LoEstro Advisors is an investment banking firm specializing in sell-side fundraise and M&A advisory, along with a strong consulting arm.
Over the last four years, we have grown to be one of India’s largest (in terms of M&A transactions) homegrown boutique investment banks, with $1billion + worth of combined deals closed across education, healthcare, consumer, and technology sectors.
