How enterprise finance is moving towards touchless operations powered by AI

Enterprise AI is rapidly reshaping finance and procurement, moving beyond productivity assistants towards autonomous workflows embedded within core business operations. As organisations look to modernise finance, supply chain and procurement, the conversation is shifting from automating individual tasks to enabling AI systems that can orchestrate end-to-end business processes while operating within enterprise governance frameworks.

At the same time, CFOs are balancing the benefits of AI-driven automation with growing expectations around compliance, auditability and regulatory accountability. The challenge is no longer whether AI can automate finance operations, but whether it can do so securely, transparently and within established financial controls.

In an exclusive interaction with Express Computer, Madhukar Uniyal, Senior Director – Solutions Engineering, Applications, Oracle India, discusses how AI is transforming enterprise finance, procurement and executive decision-making, and why governance remains central to enterprise AI adoption.

Finance is moving from systems of record to systems of outcome

According to Uniyal, enterprise AI adoption has entered a new stage.

While organisations initially experimented with AI through isolated pilots, enterprises are now deploying specialised AI agents across finance, supply chain, human resources and customer experience to automate operational processes and improve business outcomes.

He says finance teams are increasingly embracing what he describes as “touchless operations”, where AI agents assist with accounts payable, financial planning, invoicing and reporting while reducing manual intervention.

“We are seeing enterprises move away from traditional systems of record towards systems of outcome, where AI agents help execute business processes rather than simply recording transactions.”

Beyond functional automation, Uniyal also sees AI supporting executive leadership by bringing together information from finance, manufacturing, sales and workforce systems to provide enterprise-wide operational visibility for CXOs.

AI is reshaping finance workflows

Within finance, Uniyal believes several processes are already demonstrating tangible business value.

Among the most mature use cases are automated invoice processing, GST compliance, predictive cash-flow management and continuous financial planning.

Rather than relying on manual processing and spreadsheet-driven planning cycles, finance teams are increasingly using AI to ingest supplier invoices, validate tax information, forecast liquidity requirements and identify financial anomalies in real time.

He notes that these capabilities enable finance leaders to shorten processing cycles while improving decision-making around working capital and cash management.

Procurement is becoming faster and more intelligent

Procurement is also undergoing significant transformation.

Uniyal points out that AI is reducing the manual effort involved in supplier onboarding, request-for-proposal (RFP) creation, vendor evaluation and contract analysis.

Instead of manually reviewing historical procurement documents, AI systems can generate sourcing documents, analyse supplier performance, compare proposals and identify contractual risks within minutes.

Similarly, purchase approvals are becoming increasingly streamlined through intelligent workflow routing that automatically directs requests to appropriate approvers based on organisational policies.

He believes these capabilities allow procurement teams to focus on strategic sourcing rather than administrative coordination.

Enterprises still want humans in control

Despite growing confidence in AI, Uniyal says enterprises remain cautious about allowing autonomous systems to make financial decisions independently.

In conversations with CFOs, he finds organisations are comfortable allowing AI to automate processes only when those systems operate within the same governance framework applied to finance teams.

Role-based access controls, approval hierarchies, segregation of duties and comprehensive audit trails remain essential before organisations allow AI to progress from providing recommendations to executing business actions.

“Finance leaders are comfortable adopting AI when it follows the same governance, approval limits and accountability structures that already exist within their organisations,” adds Uniyal.

Rather than removing people from financial decision-making, AI currently serves to accelerate analysis while maintaining human oversight for critical business decisions.

Governance remains the foundation for enterprise AI

As AI becomes embedded across sensitive enterprise functions, governance continues to be one of the most important considerations for technology and finance leaders.

Uniyal points to multiple layers of governance that organisations increasingly expect from enterprise AI deployments.

These include encryption, role-based access controls, segregation of duties, preventive access governance, continuous financial controls and fraud detection mechanisms.

He argues that governance now extends beyond application-level security to encompass the entire technology stack, including infrastructure, enterprise applications and operational workflows.

At the same time, he notes that the rapid growth of AI is also increasing cybersecurity risks.

As AI capabilities expand, organisations face more sophisticated cyber threats, making continuous security management increasingly difficult for individual enterprises to handle independently.

Regulatory expectations continue to rise

The governance conversation is also being shaped by evolving regulatory requirements.

Uniyal says enterprises, particularly those operating in regulated industries such as banking and financial services, are paying closer attention to compliance expectations issued by regulatory authorities.

According to him, organisations increasingly expect enterprise AI platforms to support local regulatory requirements while providing evidence, auditability and operational transparency throughout AI-enabled business processes.

AI is strengthening strategic financial planning

Looking beyond operational automation, Uniyal expects AI to play a growing role in financial planning and analysis.

Real-time scenario modelling, continuous forecasting and AI-assisted planning are allowing finance teams to evaluate business scenarios more dynamically than traditional planning cycles.

Rather than relying solely on periodic budgeting exercises, enterprises are increasingly moving towards continuous planning supported by AI-driven insights that help leaders respond more quickly to changing business conditions.

As enterprise AI adoption accelerates, Uniyal believes the next phase of digital transformation will be defined not simply by automating finance processes but by enabling AI to work securely within enterprise governance frameworks. Organisations that successfully combine automation, governance and human oversight, he asserts, will be best positioned to move beyond isolated AI deployments towards enterprise-wide operational transformation.