Generative AI in finance is already driving measurable impact. From natural language reporting to document automation and intercompany workflows, it enables finance teams to reduce close time, improve data accuracy, and shift their focus from manual work to strategic oversight.
The conversation around generative AI in finance is no longer about the future. It’s about what’s already happening.
Finance teams today are under more pressure than ever to close faster, reduce manual work, and maintain accuracy across increasingly complex operations. Generative AI, particularly when designed for finance, is emerging as a reliable co-pilot—not just answering questions, but executing real tasks.
In a recent webinar, Nominal’s CEO and Co-Founder, Guy Leibovitz, and VP of Sales, Lee Greene, showcased how AI is reshaping financial workflows with tools that are available today.
This post breaks down the key takeaways, live use cases, and what finance leaders need to know about adopting AI in 2025.
🎬 Click here to watch the full webinar 🎬
The Role of AI in Accounting
One of the most practical evolutions AI has introduced to accounting is the ability to move seamlessly between structured and unstructured data.
Traditionally, accounting systems have relied on structured inputs—fixed fields, predefined formats, and rigid templates. But much of the financial data organizations rely on today comes in unstructured formats: emails, PDFs, scanned contracts, spreadsheets, and even chat messages.
AI closes this gap. By using natural language processing, computer vision, and pattern recognition, AI systems can extract relevant data from unstructured sources and convert it into structured outputs ready for processing, like journal entries, financial reports, or audit logs.
This turns what was once a manual, error-prone process into a scalable and auditable one.
What Is Generative AI in Finance?
Generative AI refers to AI systems that can create new content or outputs based on patterns they’ve learned from large datasets.
In finance, this means generating narrative insights, journal entries, or visual reports in response to conversational prompts or structured triggers.
What makes this especially relevant today is the operational pressure finance teams face. Traditional systems can't keep up with the pace and complexity of modern business.
Generative AI is being adopted not to replace human professionals but to extend their capacity, enabling them to make better decisions, faster.
Unlike passive assistants that simply retrieve data, generative AI in finance is being used to interpret data, act on it, and deliver clear outcomes: from close-ready journal entries to variance analysis and consolidated reporting.
How can generative AI be used in finance?
Generative AI is increasingly being used in finance to streamline day-to-day operations, reduce human error, and deliver real-time insights.
By transforming how data is processed, interpreted, and acted upon, it allows finance professionals to move from manual input to strategic output.
Teams can automate tasks like report generation, journal entries, and document classification, enabling them to shift focus toward review and decision-making.
In the webinar, several practical applications were demonstrated, showing how these capabilities work in action.
Financial analysis through natural language
Users can ask the system questions like “Show me the group P&L for Q4 and compare it to Q3” and receive real-time answers, without needing to touch a spreadsheet or write a single query.
Automated document processing
The AI converts unstructured documents, such as payroll files or contracts, into clean journal entries. This reduces errors and eliminates the time-consuming task of reformatting data from Excel.
Consolidation support across entities
Agents assist with intercompany eliminations by identifying matches across subsidiaries and suggesting appropriate entries. This speeds up consolidation and reduces reconciliation headaches.
Collaborative human-AI workflows
Every action taken by the AI is auditable and routed for human review. Accountants remain in control, validating the work and approving entries, which preserves compliance without slowing down operations.
You might also like: AI Agents in Finance and Accounting: From Manual Tasks to Strategic Insights
How GenAI Reduces Close Time and Increases Accuracy
Generative AI doesn’t just automate tasks; it transforms the entire rhythm of the finance team. By reducing time spent on manual work, teams can cut close cycles by up to 30% while improving data consistency.
Agents identify errors early, reduce spreadsheet dependence, and unlock time for more valuable analysis and forecasting.
This shift supports a broader transformation: moving finance professionals from “doers” to “reviewers.” Instead of building every report or entry manually, they now oversee and guide AI-driven processes.
Implementing Generative AI in Your Finance Stack
Implementing generative AI in finance starts with identifying the most time-consuming and repetitive processes in your workflow.
Based on the insights shared in the webinar, a natural entry point is document-heavy tasks like payroll processing, lease abstraction, and spreadsheet reconciliation.
These activities are typically high in volume, follow predictable patterns, and benefit significantly from automation.
But successful adoption requires more than just picking the right starting point. Change management is key.
Teams should begin with a controlled rollout—selecting one workflow to automate, closely monitoring results, and training staff to work alongside AI systems. This staged approach helps build confidence and surface any integration challenges early.
Equally important is evaluating the AI tool’s ability to meet enterprise-grade standards. Look for vendors that provide robust audit trails, support human approval checkpoints, and are SOC 1 or SOC 2 certified.
In finance, where compliance and accountability are non-negotiable, these safeguards ensure that automation enhances control rather than introducing new risks.
The Role of the AI Co-Pilot in Modern Finance
“AI should be your co-pilot, not your autopilot. The final decision should still be yours—it’s about enhancing control, not replacing it”
Generative AI should enhance finance teams, not replace them. In the webinar, Guy used a powerful analogy: finance doesn’t need a self-driving car, it needs a GPS. AI should guide, suggest, and assist, but humans remain behind the wheel.
As it takes over the legwork, the controller role evolves. New skills emerge, like configuring AI workflows, interpreting agent feedback, and validating outputs. In five to ten years, understanding how to work with generative AI could be as fundamental as Excel is today.
This co-pilot model ensures that finance remains accurate, strategic, and responsive in a fast-moving business environment.
Generative AI in finance is accelerating the shift from manual processes to intelligent automation.
As teams adopt these tools, they're gaining faster access to insights, reducing reconciliation errors, and eliminating the time sink of spreadsheets and document prep.
The result is a more agile, audit-ready finance function that can operate at scale.
Ready to bring these capabilities into your own workflows? Book a demo with Nominal and see how generative AI can help your team save time, improve accuracy, and focus on what matters most.
