The Era of Iterative Finance Transformation Is Over

With the introduction of AI agents, we have entered a new phase of finance transformation—AI-driven finance. This evolution replaces traditional processes and delivers high-value, data-driven outcomes within a cohesive, integrated solution: a truly SaaS-native ERP platform.

The embedded capabilities of AI agents work together to perform tasks such as processing high volumes of data, performing real-time analyses and predictions, or summarizing and presenting information—profoundly reshaping the way finance is performed. Finance is now dynamic, real time, and continuous. AI-driven finance helps enable touchless operations, predictive insights, and collaborative actions, driving unparalleled efficiency and business understanding. Now finance teams can shift their focus to operational oversight, business optimization, and the delivery of reliable, action-oriented insights.

A paradigm shift: AI agents and the future of finance

AI agents combine traditional and generative AI to offer multidimensional capabilities that can execute end-to-end processes with little human intervention. These agents do more than single-point AI software can, since they replace large swaths of traditional, labor-intensive workflows and introduce new capabilities.

Oracle is a driving force behind this change, developing a series of AI agents that reimagine the hands-on work finance does today. AI agents used in combination with each other can be applied to enable CFOs’ teams to achieve higher levels of productivity and efficiency than ever before. CFOs can become more proactive in achieving strategic objectives by using real-time AI-driven insights, predictions, and recommendations, drawing on a broad set of data not previously available. Embedded AI agents can become the backbone of finance and will continue to evolve, introducing new automation and capabilities on a regular basis. The days of iterative finance transformations using point solutions and bolt-on software may become a thing of the past.

The foundation begins with Oracle’s document IO agent, which automates data ingestion and document creation for billing, accounting, and recordkeeping. This includes many processes, such as expense receipt itemization, supplier invoice processing, bank reconciliations, and journal entry creation. The generative AI component lets the agent process data from various formats and languages so it can handle everyday realities, like a new trading partner sending in an order in an entirely different format. The agent continuously improves, so it increases data accuracy and quality through automation with little or no additional configuration needed. This higher-level capability can be applied to increase productivity and improve data completeness, accuracy, and timeliness.

By leveraging the document IO agent, we can now achieve finance outcomes instantaneously, rather than sequentially as manual processes are performed. As data is ingested, foundational agents—such as ledger, payments, account reconciliation, and advanced prediction—work together in near real time to perform reconciliations, create journal entries, match information, provide recommended payment options to optimize working capital, provide updated predictions, and deliver deeper insights and higher value. As a result, finance teams can gain a new perspective drawn from a broader set of data than ever before. Finance teams then introduce their knowledge and expertise to achieve the best recommendations and actions and help continuously improve the AI agents and data for the highest quality and most reliable outcomes. Finance can become more business focused, action oriented, and certainly more valuable.

Other AI agents can deliver data visualization and contextual data exploration, providing the ability to interact with data contextually or via voice recognition and offering AI-driven visualizations and real-time scenario planning. These agents allow finance teams to preview multiple AI-generated visualizations and interact with real-time data, exploring the data behind the analyses more deeply, and in a fraction of the time it would usually take. Importantly, CFOs don’t need data scientists to use these tools effectively.

This foundation of AI agents is expanding at a feverish pace. Coupled with a SaaS platform that provides timely and company-specific data, we believe it will continuously unlock new opportunities for finance organizations.

Finance teams and AI: a powerful collaboration

The role of finance teams will evolve dramatically in this AI-driven era. It should be noted that AI agents, while capable of automating many processes, will augment but never replace experienced finance professionals. AI draws upon and processes a broad set of data in ways not possible before, analyzing and presenting information and trends so that finance teams can apply their professional judgement, strategic insight, and decision-making capabilities. Establishing AI agent centers of excellence will become a best practice, allowing people and AI to work together seamlessly.

Change management will have to become a core competency, as finance teams adopt a framework for continuous updates to process, data, and technology. AI agents can empower teams by allowing them to focus on real-time data and AI-driven outcomes to help improve operations, define actions, and optimize results. Human expertise will always be essential in overseeing AI outputs and steering them toward optimal outcomes.

Why only a true SaaS platform supports AI-driven finance

To realize the vision of AI-driven finance, a truly SaaS native platform is essential. Only an integrated SaaS platform offers the cohesive infrastructure, applications, and data architecture necessary to support continuous AI innovation. Unlike a collection of fragmented applications hosted in a public cloud, a true SaaS platform delivers seamless, real-time data integration and AI capabilities without added complexity.

With the right SaaS native ERP, AI is embedded in the platform itself, making AI easier to adopt without compromising security or data confidentiality and helping deliver lower risk and higher return on investment. AI is designed to work across the entire platform, eliminating the need for bolt-on software or additional IT investments. This integration helps finance organizations focus on best practices from day one, without being hampered by outdated, fragmented technology models. The pace of innovation in finance now demands real-time, connected outcomes—something only a true SaaS platform can achieve.

Further, with generative AI and large language model (LLM) technologies advancing at an unprecedented pace, a SaaS native platform is designed to stay current. Updates adding advancements such as new AI agents come at regular intervals, and companies can accept those upgrades and start using them straight away. By contrast, hosted cloud software requires major system updates—the same old problem faced with on-premises software. Those updates consume valuable time, resources, and budget, so companies often push them later and later. But the further you fall behind, the more savings you leave on the table, and the more costly your update becomes.

And finally, a SaaS native platform helps provide security for customer data by retaining it within the platform and the enterprise database. Companies can rest assured that their data isn’t being shared or used to train any public LLMs. In addition, applying AI to your specific data will help drive higher levels of AI quality, relevance, and reliability.

The time for AI-driven finance is now

AI-driven finance is not just about process improvement; it represents a new mindset for CFOs. AI agents using your data may achieve outcomes beyond what your current capabilities can deliver, allowing you to laser focus on operational efficiency and business results.

The future of finance is clear. The time to embrace AI-driven finance is now.