The controller’s guide to AI finance solutions

The role of financial controllers is evolving.

According to a recent EY survey, 86% of controllers say their role will significantly change over the next 5 years, with 40% saying the focus will move from value protection to value creation.

“AI is shifting controllers from managing transactions to designing the systems that manage them,” says Ariege Misherghi, SVP & GM of AP, AR, and Accountant Channel at BILL. “That’s a fundamentally more strategic role.”

AI finance solutions help facilitate this change.

In this guide, we’ll explore the new role of controllers, discover what AI means for your business, provide tips for leading the transition, and offer key takeaways to make the most of AI tools.

Here’s what we’ll cover:

The new role of controllers

Traditionally, controllers were tasked with overseeing Accounts Payable (AP), Accounts Receivable (AR), and payroll.

Today, their role has expanded to include driving value and creating growth.

While regulatory compliance, operational efficiency, and accurate reporting remain critical controller functions, long-term financial strategy now falls under their purview.

Evolving expectations require controllers to be tech-savvy, forward-thinking, and capable of leading their teams through significant change.

“Change management is just as critical as technology adoption,” states Misherghi, and it must be carefully balanced with choosing from a myriad of potential options. With more data generated at every level of the organization, however, it’s easy for controllers to get bogged down in the details.

Artificial intelligence offers a new approach. More importantly, it offers a now approach.

Intelligent tools aren’t the future—they’re already reshaping the way organizations report and manage financial data.

What AI means for finance

While the Machine Learning (ML) algorithms that underpin AI tools are often complex, they facilitate simple functions.

At their core, AI solutions mimic basic human decision-making, in turn allowing the automation of key tasks.

Consider your month-end financial reconciliation. When data was largely single-source and single-format, this process was relatively straightforward.

Teams could collect and report data using a set of simple and familiar processes.

The advent of cloud-based resources, connected finance tools, and evolving regulatory expectations, however, makes this process much more complicated.

Even experienced teams may struggle to complete tasks accurately and on time.

Finance AI solutions automate these processes, giving staff time to focus on specific areas of improvement.

These tools can also help with other data-intensive tasks such as coding new invoices, predicting approvals, and flagging errors.

How controllers can lead the transition

AI is here to stay.

Controllers can choose to follow the pack or lead the transition.

Here are four ways controllers can take charge of AI implementation.

1. Identify areas for automation

Despite best efforts, 88% of AI initiatives fail to reach production.

One common culprit? Unclear objectives.

Controllers can lead the way to effective AI use by identifying key areas for automation. “They are becoming the designers of intelligent workflows, guiding AI systems that do the work, learn from it, and get better over time,” says Misherghi.

For example, AP processes offer a great starting point because they often depend on manual processes and legacy tools.

AI can help teams quickly collect and curate key data sources while reducing error rates.

2. Collaborate with IT and ops teams

IT and ops teams will use AI tools with or without c-suite direction.

Unchecked, this can lead to fragmented processes and siloed data sources that undermine the goal of AI processes.

By establishing clear lines of communication early, controllers can create a culture of collaboration that focuses on finding mutually beneficial solutions.

3. Build internal trust

AI can’t do everything. Instead, intelligent tools excel at specific tasks, such as data collection, error identification, and process automation.

By helping teams understand what AI can replace—and where humans remain essential—controllers can build internal trust and boost user adoption.

“AI isn’t replacing accountants,” says Misherghi. “It’s replacing repetitive accounting work.

Controllers who embrace this shift are building the finance teams of the future.”

4. Establish processes to audit and oversee AI decisions

AI decisions aren’t perfect.

Inaccurate or biased data sources can lead to AI outputs that are confidently wrong; seemingly sensible but predicated on poor conclusions.

Controllers can help reduce this risk and increase user confidence by establishing processes to audit and oversee AI decisions.

Effective audits require two components.

First, data sources must be regularly reviewed to ensure integrity and relevance.

Second, outputs must be validated to ensure accuracy.

Consider an AI tool designed to review invoices and automate payment processes.

Its accuracy can be checked by comparing automated invoice generation to an invoice produced using standard finance software.

If AI numbers are incorrect, this could indicate a problem with data sourcing or an issue with ML algorithms.

The sooner these issues are identified, the better for businesses’ bottom lines and users’ confidence.

The payoff: Benefits of smarter, leaner, and more strategic teams

Taking the lead on AI offers big benefits for business operations, including:

Reduced manual effort

The less time staff spend on manual tasks, the more time they can spend on data analytics, strategy planning, and business partnerships.

Increased productivity

AI tools help improve productivity by streamlining complex processes such as general ledger reconciliation and invoice verification.

Instead of taking on these tasks from start to finish, staff can review AI outputs and make changes as needed.

Enhanced creativity

Finance isn’t a static function.

New ideas can create long-term value — if teams have the time and space to pursue them.

AI makes this possible by letting staff focus on long-term goals rather than short-term operations.

Accelerated close times and reduced errors

Controllers and their teams can accelerate close times and reduce error risks by syncing clean data into solutions such as Sage Intacct.

Improved visibility into spend

Data visibility drives improved decision-making.

Data complexity, however, can obfuscate key insights.

AI tools are ideally suited to collect, curate, and process large data sets.

This allows controllers to track spending, revenue, and overhead in real time and make data-driven decisions.

Top controller takeaways

So, what does all this mean for controllers?

Given the potential scope and scale of AI, it’s easy to get bogged down in the details—here are four takeaways to help streamline your AI adoption.

1. Start small, think big

Artificial intelligence can have a huge impact on financial processes.

It can streamline complex operations, free up time for staff to develop new processes, and reduce the risk of accounting errors.

Doing too much, too soon, however, can negatively impact employee adoption.

Put simply, people prefer familiar tools and applications.

While AI may outperform current solutions, going all-in, all at once, puts controllers at risk of serious staff pushback.

Instead, start small and think big.

Give users a chance to explore what AI tools can do, and offer them as beneficial options rather than must-use solutions on the path to more in-depth adoption.

2. Take your time

This ties into the first takeaway: there’s no rush.

You don’t have to overhaul your entire back office overnight.

Take your time to evaluate multiple AI solutions, connect with vendors, and explore what AI-enabled AP, AR, and invoicing processes can do for your bottom line.

Choosing a slow and steady approach also makes it easier to pivot if current solutions aren’t working as intended.

3. Make an immediate impact

The best way to make a positive impression with AI is to make an immediate impact.

For example, AP automation from BILL offers AI-enabled invoice entry that reduces manual data entry and errors, and automated approval workflows that enable teams to review documents anywhere, any time.

“Finance leaders who embrace AI aren’t just working faster—they’re shaping the strategic direction of their companies,” says Misherghi on the speed and depth of impact an AI-savvy controller could make.

4. Focus on future-ready finance functions

Powered by frameworks such as GenAI and Natural Language Processing (NLP), AI-enabled financial applications are rapidly evolving.

For controllers, changing markets require forward thinking.

It’s not just about what AI can do now, but how automated frameworks can scale alongside expanding financial databases.

While controllers remain the gatekeepers of financial accuracy, they now play a critical role as strategic leaders at the center of operational change.

AI finance solutions pave the way for improved automation, increased productivity, and enhanced visibility.

Misherghi puts it simply: “Great controllers won’t just adopt AI tools. They’ll lead the transformation by designing how those tools shape their team’s work and decisions.”

Request a personalized demo of BILL’s AI-powered AP automation and see how it can streamline your workflows and empower your team.