Finance
The New Era of Finance Runs on Agents
Agentic AI is helping finance teams close faster, catch risk sooner, and spend less time recording the past.
Max Wessel
SVP of Product, Workday
Workday
Picture this: An executive team sits around a boardroom table, debating whether to pivot capital into a new region. The information they need is scattered across three different systems, trapped in offline spreadsheets, or weeks out of date. At the critical moment, they turn to the CFO with a single question: Can we afford this?
Finance has always been expected to do two things: keep an accurate record of what happened and help the business decide what to do next. Closing the books, chasing exceptions, auditing spend after it’s committed—that essential work is where nearly all the hours go. The forward-looking part of the job–architecting strategy, modeling scenarios, and steering executive decisions–gets whatever time is left over.
That’s the imbalance agentic finance corrects.
An agent-native financial system helps finance teams reclaim time. Agents can deliver an always-on insight layer, enforcing autonomous controls at the point of intent, and driving a continuous close ensures less of finance’s time goes to record-keeping and more goes to decision-making.
That means the strategy is no longer the afterthought – it’s the focus.
Report
AI Agents Are Here—But Don’t Call Them Boss
What Got Us Here Won’t Get Us There
Finance has gotten very good at the record-keeping half of that job. Over the last 15 years, the average close has gone from ten days to six. Finance cost as a percentage of revenue has been cut roughly in half.
But the tools have barely evolved. When the rest of the business shifted to the cloud, much of finance stayed squarely in legacy software—and for good reason. There was no room for error.
For decades, the biggest cost in finance hasn’t been software – it’s been human effort. The endless hours spent pulling audit samples, reconciling accounts, and rebuilding plans. That work is slow, rigid, and prone to error.
In finance, almost right is wrong.
Agentic AI changes the ROI. The primary gain isn’t just efficiency. It also means less manual effort, fewer errors, less rework. In finance, almost right is wrong. The real value is what finance can build with the strategic time it reclaims.
What Agentic Finance Looks Like
Agents now sit alongside finance teams, anticipating bottlenecks, advising on tradeoffs, and executing low-level tasks that consumed our attention.
When agents operate within an agent-native environment, reimagining workflows across the same rules, processes, and business context as the people they work with, three structural shifts occur. Agents can:
Automate audit-ready evidence collection. Instead of a quarter-end scramble to pull samples and prove compliance, agents continuously gather evidence, flag anomalies, and prep compilation packages in minutes.
Understand and plan for change as it happens. Planning tied to an annual calendar is dead. The business doesn’t move once a year. It moves every day. With agentic AI, finance teams can see changes as they happen, understand what they mean, and make better decisions faster.
Control and predict spend. Agents patrol your financial ecosystem continuously. They enforce policy at the point of intent, catch out-of-bounds spend before cash leaves the building, and orchestrate workflows.
The business doesn’t move once a year. It moves every day.
What’s Required to Succeed
On its own, AI is a powerful guessing machine. It reasons, predicts, and generates based on likelihoods, which means its answers can vary and its accuracy depends on what it knows about the task at hand.
Core finance, by contrast, demands exactness. It runs on rules, controls, and audit trails that must be 100% accurate.
An agent is only as good as its context.
An agent is only as good as its context. For agents to do real finance work, they need the right data, the right permissions, and the right policies in front of them at every step. Getting the right context starts with a robust, multidimensional data foundation like what’s at the core of Workday’s financial system, coupled with agents that ensure accuracy and orchestrate real-time closing and reconciliation.
When governance is built into a platform from the start, every agent action is permission-aware, policy-driven, and auditable, so the agent works from accurate context and produces results that finance teams can trust.
A Different Kind of Value
Until now, most AI conversations in finance started and ended with efficiency. But closing faster isn’t just about cutting operational overhead – it’s about opening up strategic velocity.
It means forecasts grounded in live operational context. Risks caught while they are still forming. Controls that get stronger with every transaction.
When our agents act, every action is permission-aware, policy-driven, and auditable.
Finance has always carried a dual mandate: Record what happened, and help decide what’s next. As autonomous agents take on the heavy machinery of the record, finance teams are finally liberated to shape the future.
Report
AI Agents Are Here—But Don’t Call Them Boss
A gap between effort and impact is the real ROI problem. Discover the solution.