Accuracy beats cost: Why US finance leaders are rethinking AI and outsourcing

This article is a submission by Acquire Intelligence, an innovative call center, back-office, and BPO services provider headquartered in Australia. Acquire Intelligence is a global business outsourcer with 9,500+ staff and 17 years’ experience in delivering deliver intelligent contact center and back-office functions for global businesses across many industries.

For years, finance transformation conversations focused heavily on cost reduction, process automation, headcount reduction and cutting of operational expenses.

But Acquire Intelligence’s most recent survey to over 500 U.S. top finance leaders on AI + Outsourcing tells a different story.

About the survey

When asked about the biggest challenge in finance operations today, 36% of US finance leaders ranked accuracy and error risk as their #1 concern, ahead of cost pressures, scalability, and even technology adoption itself.

That shift matters because in today’s finance environment, a single reporting error, reconciliation issue, or data inconsistency can cost way more than any short-term savings generated through automation alone.

Finance leaders are no longer asking, “How do we make finance cheaper?”.

They’re asking, “How do we make reporting more accurate?”.

And the answer sits between AI, human oversight, and operational support.

The hidden cost of inaccuracy

Modern finance teams operate in an environment that processes large amount of data, several systems and complex workflows. But more technology doesn’t automatically mean more accuracy.

According to Gartner, poor data quality costs organizations an average of $12.9 million annually. Gartner also highlights that inconsistent data across systems remains one of the biggest barriers to reliable operations.

In finance, these issues show up everywhere:

• Reporting inconsistencies
• Invoice mismatches
• Payroll errors
• Compliance risks
• Duplicate or incomplete records

Even small inaccuracies create costly consequences, especially when AI systems rely on that same data to generate insights and automate decisions.

As AI adoption accelerates across finance functions, the stakes get even higher.

AI amplifies both efficiency and risk

AI is transforming finance operations faster than ever before. From forecasting and reporting to accounts payable and reconciliation, finance teams are using AI to improve productivity and decision-making.

But finance leaders are also recognizing a critical reality, AI is only as reliable as the data and processes behind it.

A recent KPMG finance AI report found that 48% of finance leaders cite the accuracy of AI-generated outputs as a top concern as AI scales across organizations.

Another global KPMG study found that organizations with stronger governance and assurance practices achieved significantly higher error reduction rates compared to those without them.

This shows that many finance teams are already experiencing how AI can automate repetitive work well but without human oversight, clean data, and structured workflows, it can also scale mistakes faster.

That’s why leading companies are moving away from “AI-only” thinking and toward a more balanced operational model.

Why outsourcing is becoming part of the accuracy strategy

Traditionally, outsourcing was viewed primarily as a labor arbitrage strategy. Today, finance leaders increasingly need operational support teams that can:

• Validate AI-generated outputs
• Manage exceptions and escalations
• Maintain data quality
• Support reconciliations
• Improve reporting consistency
• Monitor compliance workflows

In other words, AI handles repetitive tasks while humans handle judgment, validation, and quality control.

This hybrid approach is becoming essential as finance teams try to scale without increasing operational risk.

According to Forrester research on finance automation, organizations are seeing value from automation through improved productivity and operational efficiency but governance, compliance, and process design remain critical to achieving sustainable ROI.

The future of finance is “AI + Human Precision”

The finance teams getting ahead in 2026 won’t necessarily be the ones with the most AI tools. They’ll be the ones with the most trusted operations.

The goal isn’t to remove people entirely from finance operations but to remove friction, reduce avoidable errors, and allow finance teams to focus on higher-value strategic work.

How Acquire helps finance teams reduce error risk

At Acquire, we help businesses build finance operations that are not only more efficient but more accurate, scalable, and resilient.

Our approach combines AI-powered workflows with experienced and seasoned offshore finance support teams to help organizations reduce operational friction without sacrificing quality or control.

That includes support across:

• Accounts payable and receivable
• Reconciliation and reporting
• Payroll administration
• Invoice processing and validation
• Data management and exception handling
• Finance operations support

Rather than replacing finance teams, we help strengthen them.

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