CFOs enlist AI agents for speed, trust and explainable insight

AI agents take on finance's rote work - so leaders can focus on strategy

AI-driven agents are moving from slideware to real workflows. Finance teams are shifting routine reporting and reconciliations to embedded assistants that work inside their planning and reporting platforms.

The payoff is straightforward: fewer clicks, faster cycles, and cleaner handoffs. That frees capacity for analysis, scenario planning, and growth initiatives.

Prophix's take: conversational agents built for the office of the CFO

According to Geoffrey Ng, chief AI and trust officer at Prophix Software, the company's Prophix One Intelligence delivers "a conversational natural language interface that truly understands the office of the CFO." Through its copilot interface, finance teams interact with agents that tap connected data sources to produce explainable outcomes.

Ng discussed the approach and new AI products with theCUBE's Rob Strechay during "The Future of Finance. Revealed." event. The focus: make day-to-day finance work simpler while improving decisions.

What the agents do today

• Budgeting and modeling assistance built into the Prophix One platform.
• Enterprise-wide personnel planning and operating expense planning - the high-friction work that ties up analysts.
• Faster reporting cycles with fewer manual steps and clearer, auditable outputs.

Early users should expect speed and usability gains first. Deeper insight follows as agents learn from connected, governed data.

Trust and responsible use aren't optional

"We've embedded responsible AI into our platform from the ground up," Ng said. "Our customers know when AI is being used, how it benefits them and what its limits are. Trust is non-negotiable for us."

This lines up with industry guidance on risk, transparency, and human oversight. For reference, see the NIST AI Risk Management Framework for common controls and testing practices here.

Playbook: how finance leaders should get started

• Identify 3-5 high-friction workflows (personnel planning, OPEX, monthly reporting) as pilot candidates.
• Connect clean, governed data sources first; add broader datasets only after controls are proven.
• Define human-in-the-loop review and disclosure so users know when AI is used and where its limits sit.
• Set clear acceptance criteria: cycle time, accuracy, explainability, and user effort (clicks/steps).
• Train analysts on prompts, exceptions, and approvals; publish a simple "when to trust vs. verify" guide.

Metrics to track

• Cycle time reduction for budgets, forecasts, and close tasks.
• Manual touch reduction (clicks/steps) per report or model update.
• Forecast variance and error rates before vs. after agent adoption.
• User adoption and exception rates (how often humans override or correct agent output).
• Audit findings tied to model lineage, explainability, and data access.

Risks and guardrails

• Data leakage: enforce role-based access, masking, and strict environment boundaries.
• Over-reliance: require review on material outputs and define thresholds for manual escalation.
• Explainability: keep prompts, data sources, and agent steps logged and retrievable.
• Change management: update policies, controls, and documentation with each new agent skill.

The bottom line

AI agents are taking on the repetitive tasks that slow finance down. The win is speed with control - and the chance to reassign talent to decisions that move the business.

If you want practical training and tool comparisons built for finance teams, explore these resources: AI tools for finance and courses by job.

Context

Ng shared these insights during an exclusive broadcast on theCUBE, SiliconANGLE Media's livestreaming studio, as part of "The Future of Finance. Revealed." event.

(* Disclosure: TheCUBE is a paid media partner for "The Future of Finance. Revealed." event. Neither Prophix Software Inc., the sponsor of theCUBE's event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE