What AI in finance really means for fast-growth companies

Why scaling AI operations needs smarter spend management

AI is a powerful lever to automate workstreams and boost productivity, but many companies are getting sticker shock from token costs. As AI gets embedded in more core functions across the company and token consumption multiplies, it gets more urgent to control other company spend where you can. AI in finance, particularly for a commercial card program, enables you to automate, analyze, and optimize operations.

AI creates both challenges and opportunities for finance leaders 

Businesses often focus on AI tooling and integrations but may not think much about what the token usage will look like at scale. The per-call cost of generative AI tools (with budget large language models (LLMs) priced under $.50 per million tokens) can seem insignificant at first – until you realize how many calls even basic agentic workflows make in a day.

For example, software development teams may use LLMs to generate code, classify bugs, and run continuous loops to solve engineering problems. Life science innovators may be running raw scientific text, patent documents, and clinical trial notes through agentic AI systems to structure it into databases for faster, easier extraction. And marketing, PR and HR teams are tapping AI to generate content and campaigns.

Cost pressures are increasing, with no signs of letting up. In fact, Goldman Sachs Research forecasts that “Agentic AI is expected to drive a 24-fold increase in token consumption by 2030."

Finance teams are evaluating their options to control AI spending. We’re seeing some companies pull back and revoke licenses. Others are setting token budgets for projects or departments. There are also technical solutions like model routing, that routes tasks to the most cost-effective LLM for processing. These tactics all help to bring financial discipline to AI usage. However, there’s a broader strategic opportunity to control operating costs.

As you work to tackle rising token costs, integrating AI in finance helps your teams work more efficiently and gain greater control over other areas of business spend like cloud subscriptions, infrastructure costs, supplies and travel. 

How AI spend management is reducing manual finance work

In high-growth companies, managing spend gets more complicated with more employees, more vendors, and offices in new locations. The finance team must approve, review, categorize and reconcile volumes of spend data across multiple payment methods. AI spend management integrated in your commercial card program can provide a significant lift by taking over repetitive manual work that slows teams down.

AI for finance teams can automate expense reporting tasks such as matching receipts to card transactions, categorizing expenses, routing approvals and flagging purchases that may fall outside company policies. You can even automate real-time alerts during purchase flows to stop off-policy spend before it happens.

And using an AI-powered mobile app, employees can submit expenses and receipts on the fly. It automatically generates expense reports in the spend management platform, so your finance team doesn’t waste time chasing receipts or correcting miscoded transactions. Instead, they can easily capture accurate, real-time spend data to better manage cash flow and close books faster.

Reducing inefficiencies is crucial to offset the growth costs that are harder to control. AI spend management can make finance more strategic, from card limits based on roles and use cases, to spending analytics for more precise budget allocation and forecasting.  

Why AI for finance teams still depends on human judgment

The real value of automated spend management is to free up your finance team so they have the time and insights needed to make high-stakes decisions. AI can help them see patterns faster and better understand what impacts cash position from month to month. It informs (but does not replace) the valuable human expertise needed for pivotal decisions like approving major purchases, negotiating vendor contracts, or extending runway.

Centralizing spend on a single commercial card program helps make that human judgment sharper. It unifies transaction data across teams to turn daily spend into financial intelligence. AI provides the assist to increase visibility and track performance metrics. In turn, those insights enable your finance leaders to understand how well spend is supporting growth, and where to make changes to get more value from your card program.

How AI in finance helps fast-growth companies operate smarter

Maximizing efficiency with AI is the functional aspect, but the end game is how it can give your business competitive advantages. AI financial management capabilities help your employees stay focused on meeting milestones, while reducing burn rate so you can go farther, faster.

For tech companies, that might mean expanding into new markets without letting operating costs outrun revenue growth. AI in finance makes it easier to identify where spend drives momentum and how to avoid expense leakage. A biotech firm might gain more traction for research and clinical trials by replacing inefficient processes with cost-saving automation.

AI spend management equips finance teams to help guide business growth, not just process the expenses behind it. For innovation economy companies, that means fewer distractions, sharper decisions and more room to invest in what matters most.

Need more agility to power your business? Learn about SVB commercial cards that are built for fast-growing innovation companies.