The path to AI ROI in F&A – from pilots to outcomes

Artificial intelligence (AI) is everywhere in Finance and Accounting discussions, yet nowhere near enough in Finance and Accounting results.

A recent magentIQ webinar poll found 62 percent of finance leaders are “researching and experimenting,” 11.3 percent are running pilots, and fewer than 5 percent have AI in production.

The problem is not a lack of ambition. It is the chasm between experimentation and execution. As Ian Barkin, co-founder of magentIQ, said: “95 percent of AI projects fail… and what we tend to find is projects don’t fail because of the tools being used. It’s because of everything else.”

Infographic: State of Agentic AI in Finance & Accounting (click image to enlarge)

That “everything else” includes process clarity, data quality, governance, and organizational readiness. According to Deloitte, 74 percent of companies get stuck at the pilot stage, while BCG reports that just 4 percent generate real value from AI initiatives.

The question for CFOs is straightforward: How do you cross that chasm and achieve measurable ROI?

Why pilots stall

The panelists were clear that AI pilots in isolation rarely scale. “Most pilots stall because they automate tasks in isolation,” explained David Brain, magentIQ’s co-founder. “The wins we see come from outcome-focused sprints where AI agents and human operators work together, end to end.”

Finance leaders often underestimate the foundational work required. “Companies just operationally aren’t ready for this stuff,” Barkin added. That misalignment leads to disillusionment when tools fail to meet inflated expectations.

Kelly Dunn, who leads Finance Transformation at Georgia Pacific, described the internal pressure her team faces: “Folks are asking daily what we’re doing with generative AI or agentic AI. We’re trying to resist the emphasis around solutions and just focus on what the problems are we’re trying to solve.”

The lesson: problem-first, outcome-driven design is the only way to translate experiments into enterprise adoption.

Watch the full webinar here

Measuring ROI: cashable and non-cashable benefits

ROI in Finance and Accounting must be both financial and operational. Brain highlighted the importance of broadening the lens: “It’s great to not only look at what are the direct savings that can be made, but also what the freed-up capacity can relate to within your team, and what a quicker month-end could mean to the broader business.”

This aligns with CFO research from PwC, which shows that “accelerating the close” and “improving data accuracy” rank among the top five priorities for finance transformation. Faster closes and more reliable data do not only reduce costs-they improve agility, decision-making, and compliance.2

Timelines that matter

A common executive question is how soon ROI can be realized. Munir offered a practical benchmark: “In an expense review workflow, we have been able to deliver value within three months. But if we’re talking about an end-to-end month-end process… it can take anywhere from six to nine months as a minimum.”

These timelines contrast sharply with traditional ERP or system integration projects, which can stretch for years. Agile experimentation, combined with human oversight, enables Finance teams to see results faster and build confidence incrementally.

How to move From pilots to outcomes

Three principles stand out for Finance leaders who want to move beyond experiments:

1. Anchor in outcomes – Define the destination first. Barkin summarized it as: “If you solve the problems, you create an outcome… you’re trying to pick your destination before you pick the tools and the journey you take.”
2. Embrace experimentation, but manage risk – Dunn reflected: “We absolutely picked the wrong first use case for our first experiment, but we learned a ton along the way.” Structured pilots, with clear metrics and human-in-the-loop oversight, turn failures into stepping stones.
3. Orchestrate AI with people – As MIT Technology Review has noted, “The most successful agents today are specialized, not general-purpose… they’re good at well-defined goals in known environments.” This is why a multi-agent workforce-AI for repetitive tasks, humans for context and compliance-delivers sustained ROI.

A new operating model for F&A

The implication is that Finance cannot treat AI as just another tool. It requires a new operating model. By blending global talent with AI, magentIQ has shown that it can deliver “40 plus percent savings at the very beginning of a journey,” Barkin said. And critically, those savings are matched by increased adoption success, because the teams delivering the work also identify where AI fits best.

The result is not a collection of pilots, but an orchestrated system of people and AI agents working together-what magentIQ calls a multi-agent workforce.

The bottom line

Most AI pilots in Finance and Accounting fail because they focus on tools instead of outcomes. The path to ROI requires experimentation with purpose, measurement that goes beyond cost, and orchestration of AI and people.

As Dunn put it: “Fall in love with your problem, not your solution.” For Finance leaders, that is the guiding principle that turns experiments into outcomes-and hype into measurable return.

Key takeaway for F&A leaders

AI ROI in Finance and Accounting is achieved not by running more pilots, but by running the right ones. Anchor in outcomes, measure both cashable and non-cashable benefits, and orchestrate AI with people. The future of Finance is not AI-only-it is AI + People, working better together.