What CFOs Should Be Asking About AI Agents

The artificial intelligence agent boom could mark a structural change in how enterprise software is designed, delivered and valued.

Nearly every major platform that powers the back office or customer-facing front end now promises a future in which reliable, semi-autonomous software “workers” can handle everything from invoice processing and forecasting to lead qualification and service triage.

SAP is pushing agentic AI deeper into its ERP suite. Oracle is rolling out AI agents for customer service and marketing. Salesforce is packaging industry-specific copilots and autonomous workflows into its ecosystem. AWS, Google Cloud and Microsoft Azure each offer their own toolkits for building agentic systems at scale.

For chief financial officers, the benefits pitch includes productivity gains, reduced manual labor, faster workflows and, eventually, lower operating costs. However, the new agentic wave brings a different set of questions from the cloud or automation cycles of the last decade. AI agents are not merely features added to existing software; they are becoming strategic components that cut across finance, operations, procurement, HR, sales and IT.

With providers increasingly claiming that their agents, above all others, are indispensable, CFOs must get sharper about interrogating not just the technology but the business model behind it.

Read also: Building Inside Legacy Systems Helps CFOs Capture New Payments Value

In the early days of enterprise AI, each vendor’s models, copilots and assistants felt differentiated. Today, the opposite is happening. As foundational models converge in quality and become accessible through every cloud platform, the AI agents built on top of them can start to look similar. Invoice-matching bots, forecasting copilots, service agents and customer-engagement recommenders may ultimately differ less by the intelligence behind them and more by the interface wrapped around them.

CFOs should start from a contrarian assumption that a portion of what vendors are calling AI agents could instead be termed as foundational model wrappers from one of the main foundational AI model providers, like OpenAI, Anthropic or Google.

The question then becomes whether a particular agent truly differentiates a provider, or whether it simply replicates capabilities available elsewhere at lower cost or with greater flexibility. Executives should be pressing their providers on the depth of proprietary data their agents can tap into, the uniqueness of model fine-tuning applied to industry-specific workflows, and whether the vendor’s roadmap shows genuine innovation or just repackaged automation.

According to the PYMNTS Intelligence report “Time to Cash: A New Measure of Business Resilience,” 70% of firms surveyed already use at least one AI tool to manage cash flow. The most advanced, those using agentic AI, capable of autonomous decision-making, have automated up to 95% their accounts receivable processes, compared to just 38% among firms without AI integration.

At the same time, CFOs should be scrutinizing not only what a vendor claims its agents can do but also where they can operate. An isolated agent is a feature; an ecosystem of complementary agents is a platform. The Time to Cash report also found that 97% of firms still use spreadsheets, but their CFOs are trying to quit.

See also: How AI Is Supercharging the Tools CFOs Already Trust

AI agents thrive on context, like data from transactional systems, signals from workflow tools, logs from communications apps and outputs from analytic platforms. Yet most enterprise software ecosystems remain siloed. If integration layers remain immature, any AI agent will be little more than a productivity add-on inside one isolated module.

Adding to that reality, as underscored by data in the September edition of The CAIO Report from PYMNTS Intelligence, “How Agentic AI Went From Zero to CFO Test Runs in 90 Days,” none of the CFOs surveyed were willing to grant full, unfettered access to internal data and action permissions to agentic AI systems, and only 8.3% would allow moderate access.

One of the most confusing aspects of the current agent boom is pricing. A crucial, often-overlooked question is whether the vendor is charging for the agent and the underlying compute. This dual monetization can make operating costs unpredictable and lock organizations into consumption-based pricing they cannot easily manage.

Every CFO has lived through cycles of technology hype, like RPA that overpromised end-to-end automation, analytics platforms that never delivered true self-service and cloud migrations justified on cost savings that didn’t always materialize.

AI agents risk falling into the same pattern unless organizations ask harder questions early.

The ultimate question transcends pricing, integration and ROI. CFOs must determine whether AI agents support or distort the company’s long-term operating model. The CFOs who navigate this moment effectively may not be those who adopt the most agents, but those who ask the sharpest questions.

Read also: How 16 Industry Leaders Are Putting AI to Work in B2B Payments

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