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Future of AI in Finance: From RPA and IPA to Agentic Automation

Finance operations have steadily evolved from manual, fragmented processes to system-driven workflows supported by automation and controls. Yet, despite this progress, challenges such as delayed period closes, growing exception queues, and constant manual follow-ups remain common. This signals a deeper need—not just for automation, but for systems that can actively manage work toward outcomes.

The future of AI in finance is no longer defined by how many tasks are automated, but by how intelligently work progresses across systems. Traditional automation approaches like RPA and IPA focus on execution and interpretation, but they still depend heavily on human intervention to move work forward during exceptions or unique scenarios.

Future of AI in Finance


Robotic Process Automation (RPA) excels at handling repetitive, rule-based tasks such as data entry and reconciliations. Intelligent Process Automation (IPA) builds on this by interpreting semi-structured data using OCR and machine learning to classify invoices, emails, and documents. However, both approaches often pause when decisions, coordination, or exception resolution is required.

This is where agentic automation reshapes the future of AI in finance. Agentic AI systems operate with goal-oriented autonomy. They continuously track open items, monitor deadlines, understand dependencies, and proactively prompt or escalate actions before delays occur. Instead of waiting for triggers, these systems actively coordinate work across finance processes such as AP/AR, close, and compliance.

By providing context-rich handoffs to humans only when judgment is required, agentic automation reduces friction, minimizes follow-ups, and strengthens operational discipline. Finance teams gain earlier risk visibility and more predictable outcomes—without replacing human decision-making.

As finance organizations look ahead, the future of AI in finance lies in systems that ensure continuity of work, surface risks early, and keep processes moving toward completion, not just automation for speed.


This post is adapted from an original article that explores the future of AI in finance operations, detailing the shift from RPA and IPA to agentic automation, and how autonomous, outcome-driven systems transform AP/AR, close, and finance controls.

Read the full article here:
https://saxon.ai/blogs/future-of-ai-in-finance-operations-from-rpa-and-ipa-to-agentic-automation/

Location: Dallas, TX, USA

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