Sunil Padiyar is the Chief Technology Officer (CTO) of Trintech, a global leader in AI Financial Close solutions.
For all the noise around generative AI, the true transformation inside the Office of Finance is only beginning to take shape. And it’s not because AI is simply speeding up workflows. It’s because it’s changing how finance teams think, act and make decisions.
For decades, organizations automated around the edges—accelerating reconciliations here, standardizing journal workflows there. Helpful, yes. Transformative? Not quite. Automation didn’t fundamentally change how the close operated; it just made some steps faster.
AI is finally breaking that ceiling.
The shift underway is far bigger than replacing manual steps. It’s a move from reactive, error-prone processes to proactive operations driven by intelligence. The finance team of the future won’t just process transactions—it will interpret them, learn from them and act on insights in real time. And critically, it will do so with AI as a partner, not a replacement.
From Automation To Agentic Finance
There’s a misconception that “AI-powered finance” means giving free rein to autonomous systems. No CFO wants that. Finance leaders want intelligence that understands accounting rules, respects controls and can explain every decision it makes.
This is why agentic workflows are emerging as the next evolutionary step.
In this model, AI doesn’t operate in isolation. It works inside a governed, human-in-the-loop process—triggering actions, reasoning over data, drafting outputs, routing for approvals and creating its own audit trail as it goes. Think of it as AI that doesn’t just predict, but initiates, documents and collaborates.
These agentic workflows are already reshaping the financial close:
• Reconciliations are classified and routed automatically.
• Journal entries are drafted from ERP data with supporting evidence attached.
• Variances come with explanations grounded in contextual ERP insights.
• Exceptions aren’t just identified—they’re escalated with recommended resolutions.
• Audit narratives are generated with full lineage and reasoning.
The result: Teams see fewer exceptions, higher accuracy and earlier visibility into risk. AI becomes the connective tissue across the close, accelerating work while preserving governance and oversight.
This is how you safely innovate without losing control.
The Foundation: Trustworthy Data And Finance-Grade Governance
Every successful AI deployment in finance rests on one truth: AI is only as good as the data it learns from.
Accounting teams have long battled messy extracts, inconsistent mappings and siloed data. These issues didn’t just slow automation—they capped its potential.
Modern finance organizations are now embracing data-as-a-service (DaaS) architectures: unified, governed data layers that normalize information across ERPs, entities and geographies. When this foundation is in place, AI isn’t guessing. It’s reasoning over reliable, reconciled data.
And here’s the critical point: AI built for finance must be designed with finance’s rules, constraints and risk profile—not retrofitted from a general-purpose platform.
This is where leading organizations separate themselves. They’re embedding intelligence directly into workflows rather than bolting it on later. That ensures every recommendation is explainable, secure and fully traceable back to its source.
Embedded, Explainable And Auditable By Design
The next stage of AI maturity in finance isn’t about adding more tools. It’s about making intelligence the backbone of the financial close.
Early AI experiments lived on the sidelines: a chatbot over here, a classification model over there. Useful, but limited. The real value emerges when AI is woven into the workflow itself—reading ERP data, enforcing controls, drafting outputs and automatically documenting every step.
An AI-generated journal entry, for example, shouldn’t just “look correct.” It should:
• Show the reasoning that led to the entry.
• Attach all supporting documents.
• Validate the entry against internal controls.
• Log every decision in a narrative that auditors can follow.
That’s how trust is built. Not by removing humans from the loop, but by giving them complete visibility into how recommendations were formed.
Finance doesn’t tolerate black boxes; nor should its AI.
Responsible AI: Transparency, Privacy And Control
Trust also extends to how AI learns and behaves.
Finance leaders are rightly cautious about data privacy and compliance. Responsible AI means:
• Models learn from outcomes and workflow patterns, not from customer financial data.
• Every action is logged, explainable and attributable.
• Organizations decide where and how AI runs, from on-premises to controlled cloud environments.
• Sensitive data remains protected under the same standards governing the financial close itself.
This approach aligns with emerging global standards for governance and transparency. It ensures AI strengthens enterprise trust rather than introducing new risk.
The CFO’s New Force Multiplier
Today’s finance teams face unrelenting pressure: faster closes, tighter compliance, more complex operations. AI provides the leverage needed to meet these demands head-on.
By removing repetitive tasks and surfacing insights automatically, AI enables accounting professionals to redirect their time toward higher-value work—analyzing results, managing risk, advising the business.
Across reconciliations, journal preparation and variance analysis, early adopters are seeing: double-digit reductions in exceptions, higher data accuracy, significantly shorter close cycles and hours returned to teams for strategic analysis.
But the real turning point comes when CFOs can quantify these gains—measuring hours saved, errors reduced and financial impact. That’s when AI stops being a pilot and becomes a strategic advantage.
A Real-Time, Insight-Driven Office Of Finance
When governed data, agentic workflows and embedded intelligence converge, something powerful happens: Finance begins to operate in real time.
Exceptions are detected instantly. Risks surface proactively. Insight replaces hindsight.
When I speak with finance leaders, the same theme comes up again and again: They’re not pursuing AI for efficiency alone. They’re pursuing it for confidence—to trust their numbers, make faster decisions and bring clarity to the business.
This is the Office of Finance of the future. One where AI doesn’t replace people but empowers them to deliver unprecedented accuracy, agility and confidence.
The organizations that embrace this partnership, where data, people and intelligence operate in unison, will define the next era of financial leadership.
AI isn’t making finance less human. It’s giving finance professionals the space to be more strategic, more insightful and more impactful than ever before.
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