5 AI Finance Trends You Need to Know for Next Year

AI is top of mind for most finance professionals. And it impacts many of the decisions and plans they make.

That’s according to Deloitte’s latest Finance Trends report. This isn’t too surprising as AI is part of many conversations, concerns and hopes in nearly every workplace these days.

Whether AI investment or deployment keeps you up tonight, it’s helpful to know what your colleagues in Finance are feeling, fearing and doing.

Trends Report Details

That’s why this trends report is helpful. Deloitte surveyed 1,434 finance leaders — CFOs or executives one level below — from 26 countries, representing some of the world’s largest companies. Researchers also did one-on-one interviews with 12 finance executives to learn how the trends are playing out across their organizations.

Here are their top five findings:

1. Finance at Center of Corporate Decision-Making

Because so many organizations plan tech investments — across divisions, departments and locations — finance is getting the key questions. And they’ll be expected to have valuable insight for the best decision-making.

The demand is already climbing. When asked what responsibilities are outside the traditional scope of finance, respondents said in the past three years they have taken on:

• AI and technology capital allocation (54%)
• AI trust, including ensuring reliable, accurate and explainable AI outputs (48%), and
• Oversight of AI and technology spending and cost controls (48%).

“At its core, finance provides a measurement function and measurement is a critical feature for making sure there is value and benefit from AI investments,” Tim Deacon, Executive VP and CFO at Sun Life, told the Deloitte researchers. “It’s table stakes, but it gets the finance function, and the CFO, a seat at the table to help drive value creation.”

2. Responsibly Adopting AI as Trusted Intelligence

Last year, most finance pros focused on whether AI could be embedded in their workflows. This year: 77% are comfortable with agentic solutions doing more than providing recommendations. They’re comfortable with AI doing some autonomous decision-making.

The caveat: 85% are not comfortable with AI fully taking over critical decisions.

Still, many finance pros want more: 42% say their ambitions exceed current capabilities because they need to build stronger controls before scaling to a high level of automation.

Bottom line: More decisions in Finance will be AI-powered, but with strong human oversight for higher-risk activities such as regulatory reporting and tax issues.

“These findings underscore the need for CFOs to establish clear decision-making frameworks and controls to make human-led, AI-powered finance transformation successful,” the researchers noted.

3. Managing AI Cost Complexity

New technology has always brought more cost and complexity. Nearly two-thirds of finance pros expect AI costs and complexity to rise substantially throughout next year. That will lead to more sophisticated AI cost-management practices.

Here’s what finance pros say makes it most difficult to forecast, allocate and govern for AI costs:

• Uncertain regulatory or compliance requirements (20%)
• Complex cloud and vendor billing for AI compute (19%), and
• Integrating usage data with ERP and finance systems (15%).

“AI costs can be difficult to manage and predict,” the researcher noted. “Token consumption may be the most visible usage metric, but other factors, such as workload type, data center capacity, and hosting strategy, can affect the cost of generating and scaling AI outputs in nonlinear and potentially volatile ways.”

4. Fear of Existing and Potential Risk Remains a Driver

While AI and evolving technology are at the top of finance pros’ priorities, so is their concern and responses to the risks involved.

When it comes to external risk factors, finance pros’ top concerns are:

• Cyber threats and AI-driven risks (31%)
• Economic uncertainty (29%), and
• Geopolitical tensions (24%).

Related, nearly two-thirds of finance pros felt tech sovereignty — organizational or national independence and ownership of data, vendors and supply chains — is their strategic differentiator. They want to use it to gain trust, resilience and long-term value in their markets. More than 80% believe it will reshape their technology-related capital allocation decisions through 2027.

5. Rewriting the Funding Playbook

Finance pros anticipate that they’ll diversify how they’ll fund tech budgets. For now, 66% of them say they use internally driven processes that put measurement at the forefront. That includes:

• Stage-gate process, where funding starts with a pilot and more funding may be added if goals are met at each stage) ( 27% )
• Formal capital approval process, requiring quantified ROI and a business case (25% ), and
• Executive or board mandates drive investment decisions without having a measurement process in place to gauge success (23% ).

But finance pros admit these processes can be too slow for fast-moving tech investments. So many plan to explore a variety of technology funding mechanisms, such as:

• Equity, sovereign wealth and institutional investors (30%).
• Internal capital expenditure or balance sheet funding (29%)
• Managed service arrangements with shared efficiency targets (26%)
• Vendor or partner co-investment (24%)
• Acquiring a startup with the needed capabilities (23%)
• SVP or co-investment with outside partners (20%), or
• Debt of asset sale (16%).

“These emerging funding pathways point to a broader shift in what finance is being asked to enable: greater flexibility, visibility, and speed in how technology investments are structured and deployed to maximize value creation,” the researchers noted.